Jot Fall2012

Fall 2012

THE SAUDI ARAMCO JOURNAL OF TECHNOLOGYA quarterly publication of the Saudi Arabian Oil CompanyJournal of Technology

Saudi Aramco

Appraising the Performance of Cyclic Production Scheme through ReservoirSimulation, a Case Studysee page 2

Application of a Newly Developed Workflow to Design and Optimize MRC andSmart Well Completionssee page 22

On the Cover

A pie chart map shows the reduction in water production for

some wells due to the cyclic production scheme.

The cyclic production mode calls for shutting in the wells for aperiod of time followed by production for another period of timeand repeating the process onward.

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Fall 2012

THE SAUDI ARAMCO JOURNAL OF TECHNOLOGYA quarterly publication of the Saudi Arabian Oil CompanyJournal of Technology

Saudi Aramco

Contents

Appraising the Performance of Cyclic Production Schemethrough Reservoir Simulation, a Case Study 2Tareq M. Al-Zahrani

Coiled Tubing Operational Guidelines in Conjunction with MultistageFracturing Completions in the Tight Gas Fields of Saudi Arabia 7Mohammed A. Al-Ghazal, Saad M. Driweesh, Abdulaziz M. Al-Sagr, J. Tate Abel, Stuart Wilson and Bryan Johnston

Prediction of Collapse Phenomena in Pipelines Using Fiber Bragg Grating (FBG) Sensor Technology 16Bander F. Al-Daajani, Waleed A. Al-Obaid, Bassam A. Al-Matar, Dr. Ihsan M. Al-Taie, Wasim A. Jweihan and Thierry Cherpillod

Application of a Newly Developed Workflow to Design and Optimize MRC and Smart Well Completions 22Dr. Shamsuddin H. Shenawi, Wahyu Hidayat, M. Methgal Al Shammari,Khalid A. Nasser, Abdulhamed A. Al-Faleh, Dr. Umar A. Al-Nahdi,Yahya A. Ghuwaidi and Nabil Mekki

Black Powder Inhibitors - Performance Study 30Dr. Abdelmounam M. Al-Sherik, Dr. Arnold L. Lewis, Abduljalil H. Rasheed and Ali A. Al-Jabran

Representative Prediction of Geological Facies and Rock-Type Proportion Distributions with Novel Beta Field Characterization 37Dr. Jose A. Vargas-Guzman and Dr. K. Daniel Khan

X-ray Diffraction Technique Application in Evaluating the Damage of a Gas Turbine Blade 46Dr. Shouwen Shen, Dr. Alaaeldin H. Mustafa, Dr. Gasan Alabedi, Dr. Syed R. Zaidi, Dr. Husin Sitepu and Dr. Ihsan M. Taie

Coiled Tubing Fill Clean Out and Near-Wellbore Acidizing of Plugged Stand-Alone Screens: Highly Successful Campaign in Saudi Arabian Gas Wells 52Murtadha J. Al-Tammar, Khalid S. Al-Asiri, Saad M. Al-Driweesh,Mohammed A. Asiri and Nahr M. Abulhamayel

Estimating Horizontal Well PI to Develop Giant CarbonateReservoir with Artificial Lift 60Majid H. Al-Otaibi, Cesar H. Pardo, Ronny Gunarto and Mohammed S. Kanfar

Moving Toward Intelligent Field Applications: MPFM for Production Rate Testing and Beyond 66Karam S. Al-Yateem and Nami A. Al-Amri

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ABSTRACT treatment and disposal costs. In general, excessive water pro-duction in mature fields is a serious issue in effective reservoirmanagment4.

One option to reduce water production from high water cutwells is to convert the well into a cyclic producer. Cyclic wellsare alternated between shut-in and producing phases that nor-mally last for six months each. The results of closing thesewells are the reduction of high water with a minimal impact onoil field production. The main benefit of the cyclic strategy isto reduce water production, which allows optimizing of thewater injection process, minimizing of recirculation and a bet-ter displacement of the waterflood front to the up-dip offsetproducers3. In terms of economics, since less injected water isrecirculated, the operational handling costs decrease and theeconomic efficiency of the water injection project improves.

This study was implemented in a mature field as a part ofthe water management effort to reduce water production. Inthis study, a reservoir simulation model was developed basedupon very fine geological characterization and history matchingof the field performance. The model has constantly updated itshistory matching by using the latest reservoir surveillance data,pressure, water saturation for flood front detection and newinfill well data. The predictability of the reservoir simulationmodel is very good. Simulation runs with several cyclic pro-duction scenarios (CPS) were conducted to analyze and optimize the impact of CPS on the production performance ofthe field.

CPS CONCEPTS

Figure 1 illustrates the CPS with a certain period of shut-intime. In a cyclic production mode, the mechanism of fluidmovement is different than it is in a normal production mode.During the shut-in period, heavier water of greater density issegregated and separated from the oil and settles down to-wards the lower portion of the oil column. Water coning andfingering will smear back to the lower part of the reservoir, enabling the well to produce oil at a reasonable rate during theproduction period.

One main advantage of cyclic production is less water con-ing (and lower water cut) during the production phase becausegravity segregation restores the oil column in the wellbore re-gion during the shut-in phase. Another advantage is that cyclic

Oil wells in mature fields with strong aquifer influx and thefirst row of producers near peripheral water injectors experi-ence very high water cuts (above 80%), which lower oil pro-duction and increase disposal costs.

To mitigate this situation, various production strategieshave been implemented in this simulation study to reduce wa-ter production, optimize oil production and revive dead wells.One strategy is to implement a cyclic production scheme(CPS)1. CPS involves alternate shutting in and flowing of wellswith high water cuts over predetermined time cycles. The mainobjectives of the cyclic strategy are to reduce water productionby optimizing oil production, minimizing the coning effect andhaving a better control of the uniform waterflood front to theup-dip producers. This strategy enhances the sweep efficiency,improving pressure maintenance and minimizing water production2.

This simulation study assessed the effectiveness and the performance of CPS implemented in a reservoir simulationmodel of a mature oil field. Simulation runs using several scenarios were conducted to understand and optimize the impact of CPS.

The simulation results provided the best cyclicproduction/shut-in period and showed the significant advan-tages of applying CPS over the regular noncyclic production inall scenarios. In this study, more than 93 wells have been eval-uated, and most of these wells showed good overall oil recov-ery after applying the CPS strategy.

INTRODUCTION

Water management has become a key strategy in fields thathave entered into a high water cut development period. Asfields mature, there is a natural trend for water volumes to increase as aquifer and injected water advances towards theproducers. Increasing levels of water production can impair oilproduction rates, in some cases to the point where the wellceases to be economical to produce3.

Although injected water is an enabler for improved hydro-carbon recovery, it is essential to control water production volumes and the flood front. High water production may limitoil production in a rate-limited well and may increase water

Appraising the Performance of CyclicProduction Scheme through ReservoirSimulation, a Case Study

Authors: Tareq M. Al-Zahrani

2 FALL 2012 SAUDI ARAMCO JOURNAL OF TECHNOLOGY


production is particularly applicable to dead wells that havebeen revived but have marginal pressure potential, as the shut-in period also allows the buildup of potential pressure2.

The main objectives of CPS are to save reservoir energy bykeeping water in the reservoir: reservoir pressure is main-tained, which enhances sweep efficiency by disrupting thestreamlines around the injection wells that direct the injectedwater to the un-contacted areas, enabling recovery of the by-passed oil. Also, CPS provides other benefits related to gas-oilseparation plant operations as it can be used to minimize surg-ing conditions after reducing water production, to control thewater handling capacity for disposal wells and to optimizedemulsifer consumption.

SELECTION CRITERIA AND IMPLEMENTATION

The key well production parameters used in the selection ofCPS candidates are water cut above 60% and up to 99%, andminimum oil production, normally below 1,000 barrels of oilper day (MBOD) and sometimes as marginal as 0.2 MBOD.The designation of a producer well as a cyclic producer is doneafter other water control methods, such as water shut-off andworkovers, have been considered. Cyclic producers are selectedin areas of thin oil columns near to peripheral water injectors.

This strategy was first implemented in 2005 with 22 wells,mostly located in a thin oil column of less than 20 ft andspread throughout the entire area of the field. No evaluationthrough reservoir simulation had been done to assess the per-formance of these wells before this study. The results showthat CPS wells under these conditions achieve a significant wa-ter reduction with minimum impact on oil field production.

RESERVOIR SIMULATION MODEL DESCRIPTION

The model used in this study is based on the latest geologicalmodels developed with detailed reservoir characterization. Itoffers fine layering (49 layers) with a grid size is of 250 meters,totaling 3 million cells. It includes detailed fracture modelingand petrophysical rock typing. The permeability distributionfor this model is validated by transmissibility (KH) values obtained from pressure transient analyses. The main history

matching parameters include new enhanced permeability dis-tribution, vertical transmissibility reduction, lower aquifer per-meability and localized fracture lineaments.

HISTORY MATCHING

History matching is a critical step in simulation model calibra-tion because it allows the static geological model to be ration-alized with production data. It plays a critical role inmonitoring displacement processes and enhances the under-standing of reservoir flow dynamics and the predictability offuture production performance.

In this model, the historical production and pressures werecalibrated and matched for the CPS wells used in this evalua-tion. The accuracy of the history matching was very high, reflecting the good quality of the reservoir simulation model.Figures 2 and 3 show the good history matching quality fortwo wells; the cyclic mode is captured clearly in these graphs.Given this good quality, the model can be used to simulate thefuture reservoir performance with a higher degree of confidence.

EVALUATION PARAMETERS

The following two main parameters have been evaluated veryclosely: (1) duration of shut-in intervals, and (2) production

Fig. 1. CPS.

Fig. 2. History matching quality for Well AAAA.

Fig. 3. History matching quality for Well BBBB.

SAUDI ARAMCO JOURNAL OF TECHNOLOGY FALL 2012 3


performance. The main constraints used in this study are shownin Table 1. A total of 93 wells were evaluated in this study.

Duration of Shut-In Intervals

The goal of this part of the study was to come up with an acceptable timing for shut-in and flowing periods. The key parameter was the water reduction assessed via reservoir simu-lation. Four different cycles were tested and evaluated, Table 2.

After many simulation runs and evaluations, all well resultsshowed that the best cyclic period is eight months flowing fol-lowed by four shut-in months (8/4), based on the reduction ofwater and improvement in oil rate. The prediction cases of water cut, oil rate and cumulative oil production for all fourdifferent production cycles for one of the cyclic wells areshown in Fig. 4. The green line representing the best cyclic case(8/4) shows the water cut reduction and oil rate improvement.Figure 5 further shows the advantageous performance in the8/4 case, where the green line is the base case (wells withoutcyclic mode) and the red one is the cyclic cases for all the wells.Based on these results, the 8/4 cycle has been used in the actualfield production optimization of cyclic wells.

PRODUCTION PERFORMANCE

The second parameter evaluated in this study was the produc-tion performance. The study assessed the following four majoroutcomes that contributed to a reasonable judgment on CPSperformance: (1) oil production, (2) water production, (3)sweep efficiency, and (4) offset wells’ performance. The follow-ing sections evaluate the impact of CPS on these areas.

Oil Production

This is the first key parameter to evaluate in this study. Figure6 shows the production performance of the cyclic group comparedto the normal case, clearly indicating an increase in oil rate whenthe cyclic wells were put on production. This increase in oil rateoccurred due to the buildup of pressure and the oil accumula-tion in the top of the wellbore during the shut-in period. Figure7 shows a single well’s performance. Cyclic wells improve theoil production when compared to continuous production wells.

Water Production

The major key objective in this study was to reduce water pro-duction. A reasonable correlation can be developed betweenthe number of cyclic wells placed on production and the de-crease in the amount of water production; water productiondecreased by about 20%, Fig. 8.

Table 1. Study constraints

# Months Off Months On

1 12 12

2 8 4

3 6 6

4 4 8

Table 2. Cyclic periods used in the study

Fig. 4. All prediction cases in one well.

Fig. 5. The best cycle time.

Fig. 6. Increase in oil rate for the cyclic wells group.



The closing CPS wells provide a high water reduction withminimal impact on oil field production. Figure 9 shows oil andwater reduction for some cyclic wells. It has been found that agreater reduction in produced water can be achieved by usingCPS.

Sweep Efficiency

In the cyclic process, an incremental production effect isreached due to the interplay of different production mecha-nisms: capillary and viscous forces, gravity segregation andcompressibility effects. This interplay leads to improved fluidcross flow and better reservoir sweep efficiency.

In this study, sweep efficiency improvement from flow pat-tern redistribution has been observed, and this redistributioncould make an additional contribution to oil recovery. Thishappened due to the realignment of streamlines established inthe field. The improvement in the sweep efficiency in someparts of the field is shown in Fig. 10.

Offset Wells’ Performance

In this study, the effect of the CPS process was evaluated alsofor the offset wells around the cyclic wells. Cyclic wells have asignificant impact on the offset wells’ performance. Figure 11shows the performance of one of the offset wells with andwithout a cyclic process in the wells around it, and it clearlyshows that the oil rate has increased in the CPS case. Improvedperformance of offset wells has been observed in many areas,with improvement continuing beyond the cyclic period andinto the future.

CONCLUSIONS

The implementation of this CPS water management strategyhad a big impact on the optimization of oil production fromthe reservoir. Significant water reduction from CPS wells wasconsidered one of the most important factors in achievingmore effective reservoir management. The oil production was

Fig. 7. Increase in oil rate in one cyclic well.

Fig. 8. Water production reduction in the cyclic group.

Fig. 9. Pie chart for some cyclic wells showing water reduction.

Fig. 10. Sweep efficiency improvement after cyclic mode.

Fig. 11. Well performance for one of the offset wells around a CPS well.



reduced slightly, though, due to the eight months flowing andfour months shut-in cyclic time, compared to continuous pro-duction of these wells. After CPS, an instantaneous increase inoil rate and a reduction in water were observed in all reservoirsimulation cases: due to gravity effects, cyclic production en-hanced the oil rate and reduced the total water production dur-ing the flow period cycle. The study results show that CPS is aviable option for water production management in oil fields.Cyclic production continues to be an effective practice to reduce water production and conserve reservoir energy in mature fields.

ACKNOWLEDGMENTS

The author would like to thank Saudi Aramco managementfor their permission to present and publish this article.

This article was presented at the SPE International Produc-tion and Operations Conference and Exhibition, Doha, Qatar,May 14-16, 2012.

REFERENCES

1. Al-Mutairi, S.M. and Al-Harbi, M.H.: “Water ProductionManagement Strategy in North ‘Uthmaniyah Area,” SPEpaper 98847, presented at the SPE Europec/EAGE AnnualConference and Exhibition, Vienna, Austria, June 12-15,2006.

2. Al-Mutairi, S.M., Al-Yousef, H., Al-Ajmi, F. and Al-Hashim, H.: “Cyclic Production Scheme: InnovativeApplication in Reducing Water Production and IncreasingUltimate Recovery from Mature Areas,” SPE paper120818, presented at the SPE Saudi Arabia SectionTechnical Symposium, al-Khobar, Saudi Arabia, May 10-12, 2008.

3. Babadagli, T.: “Mature Field Development – A Review,”SPE paper 93884, presented at the SPE Europec/EAGEAnnual Conference, Madrid, Spain, June 13-16, 2005.

4. Yaozahong, Y., Tao, D. and Chengfeng, W.: “The ReservoirSimulation Research and Extending Application aboutCyclic Water Injection,” SPE paper 104440, presented atthe International Oil and Gas Conference and Exhibition,Beijing, China, December 5-7, 2006.

BIOGRAPHIES

Tareq M. Al-Zahrani joined SaudiAramco in October 2002. He is aPetroleum Engineer working in theReservoir Description & SimulationDepartment. Tariq has 10 years ofexperience and a proven track recordof success within various organizations

in Saudi Aramco, mainly in reservoir engineering andreservoir management.

He is an active Society of Petroleum Engineers (SPE)member and has published many papers. Recently, Tariqwas awarded the SPE Century Club membership for hisoutstanding membership and recruitment efforts.

In 2002, he received his B.S. degree in PetroleumEngineering from King Fahd University of Petroleum andMinerals (KFUPM), Dhahran, Saudi Arabia.

in Saudi Aramco, mainly



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ABSTRACT fewer than 10%. The key reason is that in nearly all cases,milling seats is seen to add risk that outweighs the potentialpositive effect on hydrocarbon production. For this article, wewill discuss cases where milling of the ball-activated port seatswas necessary, and we will provide recommendations on theoptimum bottom-hole assembly (BHA) tool string setup.

Since every application will vary with the well’s size, depth,inclination and hole condition, this analysis is only a guideline,as it cannot cover all the potential issues involved in CT opera-tions. As such, the intent of this article is to take the lessonslearned from surface testing and field operations, and transferthis knowledge to operators for use in developing a successfulmilling program, given local well conditions, equipment avail-ability and operator preferences. The use of local proceduresfor well and personnel safety, hole cleaning and CT convey-ance should be followed as required for each application. Thisanalysis is not intended to specify the selection of CT BHAtools, but to recommend the preferred and field proven op-tions. The availability and selection of these tools will vary ineach operation and remain the responsibility of the comple-tion/CT service company.

This article will discuss seat milling operations conductedduring the past two years on ball-activated ports in four wellsthat involved multistage fracturing. Two different suppliersprovided the ball-activated ports and these will be referred toas port suppliers A and B. Each of the ball-activated port sup-pliers provided the specialized mills to mill out the balls andseats of their ports.

Two different milling service suppliers were used and thesewill be referred to as milling suppliers A and B. The millingsuppliers provided the complete BHAs, including the motors,used in the ball and seat milling operations.

Ball-activated Ports

All ball-activated ports used for multistage fracturing opera-tions have a similar basic design: a seat is attached to a sleevethat moves downwards to open when a ball is on the seat andpressure is applied. Here is where the similarity ends, as thereare many variations in seat materials and seat design, and portsmay be designed for single or multiple operations. There arealso several different types of ball materials, depending on con-ditions in the well during stimulation operations. All of thesefactors can affect the ease of milling out the balls and seats.

Open hole multistage fracturing completions are becomingstandard practice in the southern gas fields development inSaudi Arabia, with more than 40 wells completed to date usingopen hole packers and selective port technology.

Overall, the production results from the use of multistagefracturing completions have been very positive, and the fore-cast is that multistage fracturing technology usage will growconsiderably over the next several years. In general, multistagefracturing completions provide an excellent advantage in thatthey are intervention-less in their standard mode of operation.An evolving aspect of such completions is the secondary use ofcoiled tubing (CT) to handle the planned and unplanned (con-tingency) operations occasionally required to reach well pro-duction objectives. Without optimum operational planningand the selection of correct CT downhole tools, completionproblems can be encountered, and this ultimately can result innot reaching the job objective at all or only at increased costs.In addition, the use of CT to function ball-activated ports toshut-off zones or to restimulate wells is starting to be appreci-ated.

This article presents multistage fracturing case studies whereCT has been deployed, and then investigates the operationalimpact and productivity enhancement of CT deployment. Correlations taken from the key hardware variables, such asfracturing port size and type, motor type, mill type and CTsize, are also considered and analyzed.

Following the lessons learned and best practices derivedfrom these experiences, the findings from this article, with cor-rect implementation, should increase the potential for success-ful multistage completion operations and ultimate improve-ments in productivity. These guidelines can therefore be trans-ferable to other operators using similar multistage fracturingcompletion technologies.

INTRODUCTION

This article is intended to act as a guideline covering all rele-vant options in milling ball-activated port seats with coiledtubing (CT) in multistage fracturing completions. It should benoted that of the more than 10,5001 multistage fracturingcompletion operations that have been performed worldwide,the milling of ball-activated port seats has been performed in

Coiled Tubing Operational Guidelines inConjunction with Multistage FracturingCompletions in the Tight Gas Fields of Saudi ArabiaAuthors: Mohammed A. Al-Ghazal, Saad M. Driweesh, Abdulaziz M. Al-Sagr, J. Tate Abel, Stuart Wilsonand Bryan Johnston



Seat Material

The seat should be made from a material that is able to resistcorrosion and abrasion from wellbore and stimulation fluids,yet can be easily milled, if required. Seats manufactured fromhardened steel address part of the equation — the material isresistant to corrosion and abrasion — but mill-out is difficultand time consuming. Port supplier A has developed a propri-etary seat material that is both strongly resistant to corrosionand abrasion, yet easily millable.

Seat Type

If water breakthrough can occur, it is preferable to use reclosable,ball-activated ports so that zones producing water can be identi-fied and shut off. If the well can benefit from future stimulationtreatments, it is also preferable to use reclosable, ball-activatedports so that the additional stimulations can be performed. Seatsfor reclosable, ball-activated ports tend to be longer than singleoperation ports, increasing the need for easily millable material.

Ball Material

Depending on the application, balls are manufactured from differ-ent materials. Ball materials used for low temperature and low-pressure wells are different from those used for high temperatureand high-pressure wells. The choice of material is based on theneed to have a ball with sufficient fracture toughness and hard-ness to be pumped downhole at a high rate, land on the ball seatat a high velocity without any damage, open the ball-activatedport and seal off the zones below. When the stimulation job on azone is complete, the ball is no longer required, so the balls haveto be either flowed back with the produced fluids or milled out.

As soon as the surface pressure has been released after stimula-tion on a zone is complete, the ball will move off the seat. Withthe added pressure and flow from the well production below, theball will be further pushed off the seat and will not be a hindranceto hydrocarbon production. Following fracturing operations, ide-ally the ball will be pushed back to the surface during well flowback and initial production, where it will be caught by a ballcatcher in the flow back line. Recovery of complete balls doeshappen in some situations; however, what has been seen in manyfield operations is that the balls appear to flow back part of theway and then reach a particular deviation in the well where theychurn — pulled up by the produced hydrocarbons and down bygravity. As the balls are rapidly moved around in this way, theysmash against the tubing and each other, and disintegrate over ashort time. In most instances, only fragments of the balls are recovered in the ball catcher.

DISCUSSION POINTS REGARDING CT MILLINGREQUIREMENTS

In some multistage fracturing cases, ball-activated port seatmilling and/or ball milling is essential and must be planned inadvance. These cases include:• Water injector wells, where the balls cannot be flowed back

and injection into all zones is required.• Operations and/or interventions that require tools (e.g., log-

ging, perforating or shifting tools) to be run to the lower part of the multistage fracturing completion immediately after stimulation treatments and before flow back. In these instances, milling of only the balls should be consid-

ered first, leaving the seats intact so the ball-activated portscan be used for future operations. In all other cases, optionalmilling of both balls and ball seats can be considered and con-ducted on an as-needed basis. Multistage fracturing systemsshould be designed so that the seat’s inside diameters (IDs) al-low CT and logging tools to be deployed to total depth with-out milling out the seats.

The two positions of the ball seat within the ball-activatedport are shown in Figs. 1 and 2. Following the initial fracturingtreatment and when the pressure from above has been released,the ball will roll off the seat to allow production back to thesurface during well flow back.

The proprietary material of the drillable, ball-activated portseat is strong and highly pressure and abrasion resistant, butit has low ductility and so is fairly brittle and easy to millout.

FIELD EXPERIENCE

Typically, as noted earlier, the balls for the ball-activated portsare flowed back to the surface when production is started. Ifthe balls are not retrieved or if there is an obstruction, such aswellbore debris, in the ball-activated ports, the ball seats andballs need to be milled out.

Experience shows that the seats of both port suppliers Aand B can be milled; however, the choice of mills and motors,as well as the time required, varies significantly. Port supplierA allows for multiple ball seat milling operations in one run,with or without the balls present in the system; however, withport supplier B, if the ball is on the seat, two CT runs persleeve are required.

Four recent cases in the southern gas fields of Saudi Arabiawere investigated and compared:

Well 1: Mill-out of two ball-activated ports (port supplier A,milling supplier A); Well 2: Mill-out of two ball-activated ports

Fig. 1. Ball-activated port showing ball seat of a multistage fracturing completion:Closed/Initial position.

Fig. 2. Ball-activated port showing ball seat of a multistage fracturing completion:Open/Final position.



(port supplier A, milling supplier A); Well 3: Mill-out attemptof one ball-activated port (port supplier B, milling supplier B);and Well 4: Mill-out of one ball-activated port (port supplierB, milling supplier A).

Case Study Well 1

The objective was to mill-out two ball seats (port supplier A)in a single CT run (milling supplier A):

• Ball-activated port #1 at 16,472 ft, mill-out from 3” to 3.375” ID.

• Ball-activated port #2 at 16,853 ft, mill-out from 2.75” to 3.375” ID.

Following the milling recommendation given by port sup-plier A, a 3.375” 4-bladed starcutter mill was run below a2.875” outside diameter (OD) high-torque motor. Each ballseat mill-out took approximately 45 minutes at moderateweight on bit (WOB); no stalls and no high-drag situationswere encountered, Fig. 3.

The post-job plot shows the mill-out of the ball seats with-out a single motor stall. The mill approached the ball-activatedport at approximately 5,800 psi off-bottom pressure. Once themill engaged the seat, pressure increased to 7,250 psi on-bottompressure and was kept steady while proceeding slowly. After30 minutes, the ball seat was milled and a check trip performed.Motor performance at 1,450 psi differential pressure was ap-proximately 1,050 ft-lb torque output at 45 horsepower (HP).

Case Study Well 2

The objective was to mill-out two ball seats (port supplier A)in a single CT run (milling supplier A):

• Ball-activated port #1 at 13,670 ft, mill-out from 3” to 3.375” ID.

• Ball-activated port #2 at 15,184 ft, mill-out from 2.75” to 3.375” ID.

The two ball seats were milled out with the recommendedmilling BHA: a 3.375” OD starcutter mill below a high-torquemotor. The average WOB was higher than in Well 1 through-out the milling operation, resulting in faster rates of penetra-tion (ROP). The upper seat was milled out in 25 minutes and

the lower seat was milled out in 30 minutes, Fig. 4. The post-job data shows a fast target approach and inten-

tional motor stall to confirm the depth of the ball seat. Themilling BHA was then slowly lowered at approximately 1,050psi off-bottom pressure, which increased to 2,450 psi when themill engaged the seat. With a motor load of approximately1,000 ft-lb, the seat was steadily milled in approximately 25minutes, without a motor stall.

Case Study Well 3

The objective of the intervention was to mill out a single ball seat(port supplier B) at 14,448 ft from 3.025” ID to 3½” ID. Millingservices were provided by milling supplier B, with a 2.875” ODCT motor and a 3½” OD step mill. Repeated motor stalls wereexperienced immediately after the mill engaged the seat, and nomilling progress was possible. High drag was observed whenpulling up, indicating either that the mill was wedged in the seat,as opposed to milling the seat, or that the ball left in the seat haddeflected the taper-shaped mill from the desired milling path. Themill-out operation was abandoned due to the risk of the mill’sgetting stuck and also the potential to damage the completion bycreating an accidental sidetrack.

While approaching the ball-activated port, the pump

Fig. 3. Well 1: Milling out lower seat with starcutter mill – post-job plot.

Fig. 4. Well 2: Milling out upper seat with starcutter mill – post-job plot.

Fig. 5. Well 3: Unsuccessful attempt to mill out ball and seat.



pressure (off-bottom pressure) was constant and low, afterwhich a sudden pressure spike was observed on all three at-tempts when the mill contacted the seat, Fig. 5. The pressurespikes resulted from the mill’s locking into the seat and stop-ping the motor, thereby blocking the flow through the motor.The off-bottom circulating pressure remained constant andthe motor stalled at the same depth, indicating that noprogress was made. After the last milling attempt, an over-pull of 20,000 ft-lb was experienced, showing the mill hadbecome temporarily stuck.

During surface inspection, the mill showed no wear patternsat the bottom steps, but significant wear on the top section, Fig.6. This indicates that the mill became jammed inside the portand explains the overpull experienced on the last milling run.

Case Study Well 4

Based on lessons learned from the previous mill-outs, themilling supplier on this well was changed to milling supplier A.The objective was to mill-out a 3.025” ID seat (port supplierB) to a 3½” ID.

Following a mill-out procedure provided by port supplier B,two unsuccessful runs were made: first using a 5-bladed flat-bottomed mill, then using a 4-bladed flat-bottomed mill, belowa 2.875” OD high-torque downhole motor. On both runs, motor stalls were encountered and no milling pattern could beestablished. The mill-out procedure was revised to include a 4-

bladed step mill, which is typically used to mill out nipple pro-files or other very hard-to-mill materials. Running this specialstep mill on the third run proved fairly successful; however, themill-out took approximately three hours at maximum motortorque output, Figs. 7, 8 and 9.

Seven stalls, indicated by sudden pressure peaks, were expe-rienced when the mill made contact with the ball seat, Fig. 7.Even at a very slow target approach speed, it was not possibleto make progress, indicated by the steady low pumping pressure

Fig. 6. Picture of step mill after retrieval back to surface.

Fig. 7. Well 4: First run with 5-bladed flat-bottomed mill – post-job plot.

Fig. 8. Well 4: Second run with 4-bladed flat-bottomed mill – post-job plot.

Fig. 9. Well 4: Third run with 4-bladed step mill – post-job plot.



(off-bottom pressure) and the motor’s stalling at the samedepth repeatedly.

Similar results were observed on four additional milling attempts, Fig. 8. The motor worked at low pressure during the tar-get approach, then stopped as soon as the mill contacted the seat.

The post-job data plot, Fig. 9, shows the successful mill-outof the ball seat with a 4-bladed step mill. The first approachwas performed with an intentional stall to confirm the targetdepth, and the seat was then milled out in three milling stages.The off-bottom pressure during the target approach was ap-proximately 1,700 psi; it then increased to 3,200 psi on-bottompressure when the mill was engaged. At 1,500 psi differentialpressure, the motor put out approximately 1,100 ft-lb torque.The total time required to mill the sleeve was approximately150 minutes.

The results of the case studies listed above are summarizedin Table 1.

DISCUSSION

Analysis of four recent ball seat mill-out examples showed significant performance variations.

Ball-activated Port “Millability” and Mill Selection

The seats of the ball-activated ports from supplier B are millable;however, operationally it was noted that they required a signif-icant amount of preparation, runs and time to mill. This is be-cause the ball seats are made from hardened steel. As such, anonaggressive mill, such as a multiple stepped mill with preci-sion carbide inserts, is required. Any aggressive mill will over-load a high-torque motor, even at minimum WOB force.Mill-out time experienced was approximately three hours.

With the ball still on the ball seat, two runs were requiredper port to achieve mill-out. The ball had to be milled with anaggressive flat-bottomed junk mill first, followed by a secondrun with a nonaggressive step mill. Combining the two runs isimpossible because the taper-shaped step mill can be deflectedoff the desired milling path when the ball is on the seat, whilethe aggressive junk mill overloads (stalls) the motor immedi-ately when milling the ball seat itself.

The ball-activated ports from supplier A proved to be readilymillable in a short time regardless of whether the ball was stillon the seat or not. Multiple balls and seats could be removedin one run. This is because the ball seats are made of a propri-etary material that is hard, yet millable. The material can bemilled in a short time with a semi-aggressive mill. A customized,4-bladed junk mill with starcutter inserts provided by port

Well 1 Well 2 Well 3 Well 4

Port Supplier A A B B

Depth, Port #2 16,472 ft 13,670 ft 14,448 ft 13,400 ft

Depth, Port #1 16,853 ft 15,184 ft - -

Mill Supplier A A B B

Mill Type3.375” Starcut-ter Mill

3.375” Starcutter

Mill

3.500” OD Step

Mill

3.500” OD Step

Mill

Mill Details

4-Bladed Flat-bot-

tom, w/

Starcutter Inserts

4-Bladed Flat-bot-

tom, w/

Starcutter Inserts

4-Bladed,w/

Carbide Inserts

4-Bladed, w/

Carbide Inserts

Mill Character-ization

Semi-ag-gressive

Semi-ag-gressive

Non-ag-gressive

Semi-ag-gressive

Motor TypeHigh-

Torque Motor

High-Torque Motor

CT MotorHigh-

Torque Motor

Maximum Torque

1,100 ft-lbf 1,100 ft-lbf - 1,100

ft-lbf

Maximum hp 52 hp 52 hp - 52 hp

Milling Time, per Port

45 min per Seat

25 min and 30 min per

Seat

Could not Mill Seat

3 hours for 1 Seat

Job ResultSuccess on 1st Run

Success on 1st Run Failure

Failure on 1st and 2nd Run, Success on 3rd Run

Table 1. Summary of the four wells analyzed from field operations

Fig. 10. BHA diagram showing the component options for CT milling of ball-activated seats.



CT Connector

A standard grub screw or slips type connector is recommended.A “roll-on” type connector is not recommended as it risks losingits grip on the CT string when used in conjunction with motors.

Motorhead Assembly

A heavy-duty, rigid motorhead assembly is recommended thatincorporates dual-flapper check valves, a hydraulic drop-balldisconnect and a drop-ball circulation sub. A hydraulic discon-nect should always be employed when milling in the event theBHA becomes stuck in the well. It also must be rugged enoughto withstand the forces imposed during the milling operation.The separation section is actuated by dropping a ball andpumping it through the CT string to a ball seat in the hydraulicdisconnect tool. When the ball seats, the BHA is placed in ten-sion and pressure is applied to shear the pins connecting thetwo portions of the hydraulic disconnect. The lower portion ofthe hydraulic disconnect remains in the well; it incorporates aninternal fishing neck, which facilitates fishing operations. Theupper portion is retrieved to the surface. Once milling is com-plete, it may be desirable to increase the pump rate to clean upthe well or pump nitrogen to unload the well. This increase inpump rate is accomplished by bypassing the motor to eliminaterotation and the friction pressure drop. The circulating sub ispositioned below the hydraulic disconnect so that the separa-tion section can still be actuated after the circulation sub isopened, if required. The circulating sub may be actuated bydropping a ball and pumping it through the CT string to theball seat in the circulating sub, or by applying high circulationpressure alone. In the ball-drop design, when the ball seats, theBHA is placed in tension and pressure is applied to shear thepins, allowing an internal sleeve to shift and expose large circulation ports.

Stabilizers/Centralizers

The use of a stabilizer is recommended as part of the millingassembly. The stabilizer should have an OD between 0.125”and 0.25” smaller than that of the mill to allow driftingthrough an obstacle that is milled. The stabilizer allows for abetter centralized milling operation and more efficient cuttingsremoval during milling (e.g., in horizontal wells, where thetool could be lying on the low side of the well and so restrictcuttings flow back). In restricted wellbore applications, themotor OD may approach the mill size. In these cases, the useof a stabilizer is of limited benefit and therefore optional.

Hydraulic Motor

In the majority of cases, as large a motor as possible should berun for the milling job. Certainly the motor OD needs to be atleast one size (~0.25” to 0.125”) smaller than the mill OD. TheOD is initially dependent on the minimum restrictions in the well,as with the mill, but also the annular clearance between the motorOD and the tubing/casing ID needs to be considered to ensuregood flow passage of the debris being returned to the surface.

supplier A is recommended. Mill-out time ranged between 25and 40 minutes per seat when run in conjunction with a high-torque motor.

Motor and Mill Operational Performance Analysis

Motor selection proved to be a critical parameter when millingball seats provided by port supplier B. Even with a nonaggressivemill, the seat material hardness caused the mill to stop rotatingat minimal WOB (see Well 3, milling supplier B), and this inturn caused frequent motor stalls with little or no progress.Changing to a high-torque motor helped to rectify this condition,keeping the mill turning when high torque was required. Evenwith the high-torque motor working at maximum HP output,however, milling the hardened steel seat took significant timeand patience.

Ball seats from port supplier A were found to be easily mill-able. In both cases that were evaluated (Well 1 and 2, millingsupplier A), high-torque motors were run, and no stalls wereencountered at high ROP. This leads to the assumption thatthese seats could potentially be milled with a standard motor,if it was required. High-torque motors are preferred because:

• The high-torque output keeps the mill rotating at high load

(reduced number of stalls).

• No milling interruptions after motor stalls.

• Longer mean time between failures because reduced or

no stall damage occurs (stator rubber decomposition,

chunking).

• Higher ROP due to increased HP output.

• Chemical-resistant design allows for combining seat mill-out

with other job objectives (acid spotting, N2 lifts).

RECOMMENDED BHA FOR MULTISTAGE FRACTURINGMILLING OPERATION

The recommended BHA for the mill-out of a ball-activatedport ball seat in a multistage fracturing completion, Fig. 10,would be as follows:

• CT connector.• Motorhead assembly (dual-flapper check valves, hydraulic

disconnect and circulation sub).• Hydraulic up-acting jar (optional).• Circulation sub (optional).• Nonrotating centralizer (recommended).• Hydraulic high-torque motor.• Starcutter mill.Based on the extensive testing, field cases and general

practices for milling with CT, the following recommendationscan be made with respect to mills, motors, stabilizers and addi-tional milling equipment. Note that the circumstances for eachwell will be different. As such, these procedures are not intended to cover every application, nor should they takeprecedence over local practices and procedures, especially with regard to health, safety and environmental issues; rather, they should be used as a guide based on previous successfuloperations.



For a given size motor, it is recommended to choose a high-torque motor over one with high rotational speed when a hardobject, such as a ball seat, will be milled. Generally, the torqueincreases with the number of stages and the number of lobes inthe rotor/stator assembly. The speed decreases as the numberof lobes increase. High speed is not efficient if the feed rate andWOB cannot be controlled effectively, as the motor will con-stantly stall.

Often, the initial issue for the milling program is to addressthe available CT size and length. This will greatly affect the selection of the milling BHA. While all motors will generallyoperate over a wide range of flow rates, it is essential to checkthat the motor will function with the optimum torque rangefor the flow rates available. A large, high-torque motor is noteffective if the available flow rate is too low. CT force simula-tions should be run to check that sufficient WOB is available.If tubing forces simulation results indicate potential weighttransfer problems, a metal-to-metal friction reducer may alsobe considered.

Mills

The recommended mill type is a 4-bladed end mill with downfacing holes for circulation. The OD of the mill is dependentupon the ID minimum restriction in the well (e.g., upper R-Nipples, etc.); otherwise the mill OD will be determined by theliner/tubing drift ID or the mill-out ID of the ball-activatedport. It is important that the mill have a long body or shaft, toallow for better stabilization of the mill and to reduce the riskof having the mill end fall into recesses and mill on non-drill-able components of the ball-activated port.

RECOMMENDATIONS AND CONCLUSIONS

Selection of Ball-activated Ports

If removal of the seats from ball-activated ports is anticipated,or even a potential requirement, it is important to deploy portsthat are designed for easy mill-out. Hardened steel seats arenot easy to mill, and if the ball is still on the seat, a separaterun is required to first remove the ball. Then a second run witha different mill is required to remove the seat. In addition tothe time and cost of a second CT run, much time is required tomill the hardened steel seat. If hardened steel seats have to beremoved from multiple ports, two runs will be required foreach port.

When ball-activated ports with seats engineered for mill-outare deployed, a single mill can be used to remove the balls andseats from multiple ports in a single run.

Selection of Mill

Each supplier of ball-activated ports will have recommenda-tions for the mills to use for milling the seats from their ports.The most efficient seat and mill combination found to date isthe starcutter mill used on the proprietary engineered seat

(port supplier A). The starcutter mill can mill through multipleballs and seats in a single run.

Selection of Motor

High-torque motors are preferred over standard motors. Formill-out of ball seats from supplier B, a high-torque motor ismandatory to achieve success. Mill-out of ball seats from supplierA could be performed with standard motors; however, usinghigh-torque motors reduces milling time.

High-torque motors from milling service supplier A haveproven successful at milling out all types of ball seats. Thehigh-torque output is achieved by higher differential pressure,which is made possible due to the even layer of rubber liningthe stator. These motors can be used in high temperature applications, if nitrogen-assisted cuttings lift is required oreven if aggressive chemicals have to be spotted.

Selection of BHA

The CT BHA for milling ball seats from ball-activated portsshould include a dimple connector, a circulation sub, an emer-gency disconnect and a stabilizer. Milling services supplier Aincludes a circulation valve in their BHA to provide a contin-gency for removing cuttings during ball seat mill-out. The cir-culation valve can be switched from milling mode to cleanoutmode by adjusting the pump rate.

Contingencies/Efficiency

As with any milling operation, removal of cuttings and holecleaning is crucial to reduce the risk of loading up the annulusand becoming stuck. Best practices developed include circula-tion of high viscosity pills or sweeping the wellbore aftermilling out several ball seats. Nitrified gel can be pumped totransport cuttings in low bottom-hole pressure wells or to increase cutting transport velocity.

ACKNOWLEDGMENTS

The authors would like to thank the management of SaudiAramco, Schlumberger and Packers Plus Energy Services fortheir permission to present and publish this article. The authorswould also like to thank Maria Meijer and Marco Dutra atPackers Plus Energy Services for their assistance in the prepa-ration of this manuscript.

This article was presented at the SPE Middle East Uncon-ventional Gas Conference and Exhibition, Abu Dhabi, U.A.E.,January 23-25, 2012.

REFERENCES

1. Rahim, Z., Al-Kanaan, A., Johnston, B., Wilson, S., Al-Anazi, H. and Kalinin, D.: “Success Criteria for MultistageFracturing of Tight Gas in Saudi Arabia,” SPE paper149064, presented at the SPE Saudi Arabia SectionTechnical Symposium and Exhibition, al-Khobar, SaudiArabia, May 15-18, 2011.



J. Tate Abel is a Senior PetroleumEngineer working for Saudi Aramco inthe Gas Production EngineeringDivision. Before joining Saudi Aramco,he spent 3 years as a consultant fornumerous independent oil and gasoperators in North America and for

several state-run E&P companies in India. Tate has over 17years of workover/completion and project managementexperience in the Middle East, North America and Asia.

He received his B.S. degree in Chemical Engineeringfrom the New Mexico Institute of Mining and Technology,Socorro, NM, and a MBA from Centenary College,Shreveport, LA.

Stuart Wilson is a Stage FRACManager for Schlumberger WellServices in al-Khobar, Saudi Arabia,responsible for the marketing andtechnical development of thecompany’s multistage fracturingcompletion business throughout Saudi

Arabia and the Middle East region. After earning his B.Eng. degree in Mechanical

Engineering from the University of Hertfordshire,Hertfordshire, England, and his M.Eng. degree in Businessand Operations Management from the Norwegian Instituteof Technology, Trondheim, Norway, in 1997, Stuart joinedSchlumberger as a Field Engineer in Stavanger, Norway. Heworked 5 years in various technical and operationalpositions in Norway and Denmark. From 2002 until 2005,Stuart served as the worldwide product champion for theSchlumberger coiled tubing (CT) inflatable packer business.

In late 2005, he became the GeoMarket TechnicalEngineer in Moscow, covering CT operations in the Russiaarea. In 2006 until late 2007, Stuart worked as the CTOperations Manager for the Far East-Russia GeoMarketregion in the Sakhalin area, working on several projects,including Lunskoye.

From 2008 until taking his current post in 2009, heserved as the multistage fracturing completion productchampion based in Dubai, U.A.E., covering the MiddleEast and Far East regions.

Stuart is the author of several papers on multistagefracturing, inflatable packers and CT offshore technology.In 2003, he was named a World Oil New Horizons awardfinalist.

Stuart is a member of the Society of PetroleumEngineers (SPE).

BIOGRAPHIES

Mohammed A. Al-Ghazal is aProduction Engineer at Saudi Aramco.He is part of a team that is responsiblefor gas production optimization in theSouthern Area gas reserves of SaudiArabia. During Mohammed’s careerwith Saudi Aramco, he has

participated in several upstream projects, including pressurecontrol valve optimization, cathodic protection systemperformance, new stimulation technologies, safetymanagement processes and petroleum applicationsenhancement.

In 2011, Mohammed assumed the position of GasProduction HSE Advisor in addition to his productionengineering duties.

In early 2012, he went on assignment with the SouthernArea Well Completion Operations Department, where heworked as a foreman leading a well completion site.

In 2010, Mohammed received his B.S. degree inPetroleum Engineering from King Fahd University ofPetroleum and Minerals (KFUPM), Dhahran, Saudi Arabia.He has also authored and coauthored several SPE papersand articles in technical publications.

Saad M. Driweesh is a Gas ProductionEngineering General Supervisor in theSouthern Area Production EngineeringDepartment (SAPED), where he isinvolved in gas productionengineering, well completion andfracturing and stimulation activities.

His main interest is in the field of production engineering,including production optimization, fracturing andstimulation, and new well completion applications. Saadhas 24 years of experience in areas related to gas and oilproduction engineering.


Abdulaziz M. Al-Sagr is a Supervisorin the Southern Area ProductionEngineering Department (SAPED). Hehas been very involved in the gasdevelopment program in the SouthernArea to meet the growing global gasdemand. Abdulaziz’s experience covers

several aspects of production optimization, including acidstimulation, coiled tubing applications and fishingoperations.

In 1995, he received his B.S. degree in ChemicalEngineering from King Fahd University of Petroleum andMinerals (KFUPM), Dhahran, Saudi Arabia.

several aspects of production optimization, including acid

J. Tate Abel

several state-run E&P companies in India. Tate has over 17

Arabia and the Middle East region.

His main interest is in the field of production engineering,

participated in several upstream projects, including pressure



Bryan Johnston is the BusinessDevelopment Coordinator for PackersPlus, serving the Middle East Gulfcountries. He has worked in the oilservices industry for 20 years inoperational, technical and marketingpositions, and is experienced in

cementing, stimulation and downhole tools. Bryan workedfor Dowell Schlumberger as a Field Engineer, then as anOperations Supervisor and District Manager. He workedwith McAllister Petroleum Services, the manufacturer ofinflatable packer products, as Marketing Manager. Whenthat company was acquired by Weatherford, Bryan workedin sales and business development positions withinWeatherford before joining Packers Plus in 2006.

He received his technical diploma from the BritishColumbia Institute of Technology, Burnaby, BritishColumbia, Canada, and an MBA degree from theUniversity of British Columbia, Vancouver, BritishColumbia, Canada.

Bryan is a coauthor on several papers on multistagestimulation in the Gulf region and he is a member of theSociety of Petroleum Engineers (SPE).

cementing, stimulation and downhole tools. Bryan worked



ABSTRACT

two processes: internal corrosion as a result of the interactionof hydrogen sulfide (H2S) in the carried media (sour crude orgas) with the pipe material, and/or external corrosion as a re-sult of other corrosion processes depending on the location ofthe pipe (this includes interaction of the outer environment,salt water due to rain and cathodic protection, with the steelpipe, which may release hydrogen). When H2S reacts with steel(the pipe material), it forms iron sulfide and releases hydrogenatoms. Therefore, an increase in the amount of hydrogen entryflux to the pipe leads to a buildup in the local concentration ofhydrogen until it reaches some threshold level necessary to initiate cracking2. The hydrogen atom represents the smallestatom and is the only atom that can permeate steel. In the caseof the sleeved pipe, the small gap between the sleeve and thepipe is a preferential site for hydrogen to accumulate. Collapsewill not occur as long as the amount of the pressure generatedby the trapped hydrogen is lower than the operating pressureof the pipe. It is strongly believed that collapse occurs onlywhen there is a sudden drop in the operating pressure of thepipe. The affected pipe can be sleeved with direct welding orbutt strap welding, Fig. 1.

This study was carried out to assess and monitor both typesof sleeves. The objective of the monitoring was to detect andpossibly predict the sleeved pipe’s collapse.

SYSTEM DESCRIPTION

Fiber Bragg grating (FBG) strain sensors have a potential ap-plication for structural monitoring because of their stabilityand exceptional capacity for long-term monitoring. This sens-ing technology takes advantage of a spectrally encoded signal,

This article discusses the application of fiber Bragg gratings(FBGs) for use as strain sensors to monitor and predict thebuckling phenomena in sleeved pipes. Some sections of apipeline are sleeved when their wall thickness is significantlyreduced due to localized corrosion/erosion. The sleeve is basi-cally adding additional thickness to the pipe to keep it in serv-ice; however, the sleeve does not stop corrosion/erosion fromprogressing, and the hydrogen evolution byproduct of the cor-rosion process will permeate the steel and be trapped in anygaps or voids that it may encounter. Obviously, the addedsleeve provides in its annulus just such a small gap for hydro-gen entrapment, and consequently, inward pipe buckling mayoccur due to the hydrogen pressure buildup. It has been ob-served that such buckling usually occurs directly under the“butt strap” reinforcement on the sleeve. The pipe bucklingleads to serious consequences, including increased operationalcost due to scrapers becoming lodged at the location of thebuckling during the frequent scraping of the pipe. Over thepast decade, use of a fiber optic sensor for strain measurementhas become an attractive technology for integrity monitoring.The most frequently used technology involves inscribing nano-structured Bragg gratings, in the form of periodic variations ofthe optical refractive index, into the core of optical fibers madeof glass. The Bragg grating period represents the scale lengththat can be influenced by external strains. The scale length canbe determined using the wavelength of the light reflected in theoptical fiber. Due to all these advantages, it was decided to useFBGs to monitor pipelines for potential buckling phenomenaand to help in predicting its occurrence through measurementsof several operational parameters.

INTRODUCTION

The phenomenon of sleeved pipe collapse is a major concernfor pipeline operations. The collapse usually occurs due to acombination of two factors: the formation of hydrogen atomsas a result of corrosion, and the pressure fluctuation of thepipeline caused by abnormal operation. The effect of hydrogenatoms in metal is known as hydrogen embrittlement; this phe-nomenon has been studied over the past seven decades, but afull explanation for it has not been identified1. In general, cor-rosion can be the result of one process or a combination of

Prediction of Collapse Phenomena inPipelines Using Fiber Bragg Grating (FBG)Sensor Technology

Authors: Bander F. Al-Daajani, Waleed A. Al-Obaid, Bassam A. Al-Matar, Dr. Ihsan M. Al-Taie, Wasim A. Jweihanand Thierry Cherpillod

Fig. 1. Sleeved pipes with a butt strap.



which provides inherent immunity from the signal intensityfluctuations that plague many other fiber optic and electronicsensing techniques. This technology has undergone rapid de-velopment in recent years, following the observation of verynarrow band reflection in the photosensitive core region of Ge-doped silica optical fibers and its first successful fabricationon fiber core by exposure of a coherent two-beam UV interfer-ence pattern in 19893, 4.

This FBG system consists of three main components: an optical strain gauge, a temperature compensation sensor andan optical sensing interrogator.

Optical Strain Gauge

The optical strain gauge is designed to make fiber handlingeasy, and sensor installation fast and repeatable. It is based onFBG technology. The optical strain gauge’s stainless steel car-rier holds the FBG in tension and protects the fiber during in-stallation. Since there are no epoxies holding the fiber to thecarrier, long-term stability is ensured by the gauge’s design.There are two ways of holding the optical strain gauges: eitherby welding or by epoxy attachment to a structure’s surface.Welded gauges can be used immediately after attachment. Theoptical strain gauge is qualified for use in harsh environmentsand delivers many advantages inherent to all FBG based sensors.

Temperature Compensation Sensor

The temperature compensation sensor is specifically designedto provide temperature compensation data for strain measure-ments from FBG based strain gauges installed on the samestructure. Like the optical strain gauge, it is designed to makefiber handling easy, and sensor installation fast and repeatable.It is based on FBG technology. The temperature compensationsensor’s stainless steel carrier holds the FBG in tension andprotects the fiber during installation. Since there are no epoxiesholding the fiber to the carrier, long-term stability is ensuredby the sensor’s design. Using FBGs for temperature and pres-sure sensing generally follows the same procedures used forlong-term static and dynamic strain testing. The idea here is toisolate the FBG that is being used for temperature testing fromany effects of strain on the structure being tested.

Optical Sensing Interrogator

The optical sensing interrogator is a compact, field proven, in-dustrial grade static sensor interrogation module designed forrobust, reliable, long-term field operation.

It is built upon the Micron Optics x25 optical interrogatorcore, featuring a high power, low noise swept wavelength laserthat is realized with Micron Optics’ patented Fiber Fabry-Perot Tunable Filter technology. The x25 optical interrogatorcore employs full spectral scanning and data acquisition, pro-viding measurements with high absolute accuracy, and featuresflexible software post-processing and high dynamic range per-formance. The x25 based interrogators support continuous,onboard, NIST traceable wavelength reference components

and are ideally suited to measure many different optical sensortypes, including FBGs, long period gratings, extrinsic Fabry-Perot sensors and many others. Well over half of the fiber opticsensors deployed today are measured with instrumentationthat uses Micron Optics technology.

PRINCIPAL OPERATION AND EXPERIMENTS

The sensing system selected for this test is based upon FBG op-tical strain gauges. The complete sensing system requires anoptical interrogator, strain gauges and thermal compensationsensors. Based upon the prior analysis, locations for the straingauge and temperature sensor placement were determined. Locations were chosen to provide strain measurements at keylocations on the pipe, on the sleeve and directly on the buttstrap. Figure 2 shows the locations of the sensors.

The sensors were connected serially in four strings. The up-per strain gauges were designated as SU# and the lower straingauges were designated as SD#, where numbers run from 1 to5. Similarly, the 10 temperature sensors, five upper and fivelower, were designated as TU# and TD#, respectively. A FBG isa wavelength-dependent filter/reflector formed by introducing aperiodic refractive index structure within the core of an opticalfiber. Whenever a broad-spectrum light beam impinges on theFBG, it will have a portion of its energy transmitted throughand another portion reflected off, as depicted in Fig. 3.

The reflected light signal, which is very narrow, will be centered at the Bragg wavelength, which corresponds to twice theperiodic unit spacing, . Any change in the modal index orgrating pitch of the fiber caused by strain or temperature changes

Fig. 2. Locations for strain gauges (SU, SD) and temperature sensors (TU, TD).

Fig. 3. Transmission and reflection spectra of a FBG.



will result in a Bragg wavelength shift. Strain can be measuredusing FBG sensors by properly mounting them on, or embeddingthem into, the substrate of interest. One of the advantages ofthis technique is that the detected signal is spectrally encoded,so that transmission losses in the fiber are of no concern.

Two field studies were conducted to assess the FBG system,as follows.

Detection Configuration of Pipe Collapse

The first part of the study focused on using the sensor configu-ration to detect the collapse as soon as it occurs. This studywas conducted on two sleeved pipe sections (supplied by thePipeline Department). The pipe sections were placed in a desig-nated area at the Pipeline Department yard for high-pressuretests. The first pipe was left with two open ends, and the sec-ond one was sealed at both ends. The sealed pipe was 90%filled with water.

Both pipes were subjected to pressure buildup in the annu-lus between the pipe and the sleeve. The test continued by in-creasing the pressure difference between the annulus and themain pipe until the sealed pipe collapsed. The open-endedsleeved pipe section did not collapse, even at a higher pressure(1,000 psi); for this test the open-ended pipe had a diameter of28”. The fiber optic system was examined for the detectionsignal. The signals of the FBG sensors were collected for fur-ther interpretation. The types of the signals collected were pro-grammed in the system and were standardized to be utilizedfor the field trial.

Prediction Configuration of Pipe Collapse

This part of the study focused on the methodology of predict-ing the pipe’s collapse by determining the following three mainvariables:

• Delta Pressure: During this test, the two pressures, the trapped hydrogen pressure and the pipe pressure, were continuously monitored until the collapse occurred due to the controlled pressure reduction of the pipe.

• Threshold Pressure: The threshold pressure was experi-mentally determined under various pressure differences between the sleeve and the pipe. This experiment was intended to allow for different operating pressures used by different pipeline operators.

• Collapse Predictor: A prediction algorithm capable of generating an alarm before the collapse occurs can be developed based on a mathematical model of the pipe, the delta pressure changes recorded during previous phases and the threshold pressure determined experimentally.

RESULTS AND DISCUSSION

Prior analysis and field evidence suggested that the occurrenceof buckling coincided with the reduction in internal operatingpressure when the annular region under the sleeve containedhydrogen. It was decided that this could be tested by pressurizingonly the annular region to create a pressure differential across

the pipe wall. It was assumed that the mechanism was suffi-ciently linear and that the operating pressure was not significant: only the pressure differential across the wall wasimportant.

The monitoring instrument and sensors were set up with thetest pipe initially unpressurized. The sensor interrogator wasset to scan each sensor every 10 seconds, and the pressure inthe annulus was increased manually in 100 psi increments. Noautomated reading of the pressure was possible during thistest. Approximately 2-10 minutes was allowed between stepsto allow for settling and for the temperature to become as uni-form as possible. During the pressure increase from 400 psi to500 psi, an audible indication of buckling was heard when thepressure reached 430 psi. Figure 4 shows the location of thebuckling underneath the butt strap section.

The pressure was held at 430 psi for 10-12 minutes until thesensor scanning was terminated. The data recorded during thetest was imported into FOX-TEK’s DMAT Database softwarefor analysis. The temperature sensor data was used to compen-sate for any thermal effects on the strain gauges due to the outdoor location of the test pipe and the pressurization. Exam-ination of plots in Figs. 5 and 6 reveals clear and consistenttrends in reference to the distances of the sensors from the buttstrap and the location of the buckling area. Although insuffi-cient time was allowed during the initial phases of pressurizationfor the readings to stabilize, it is clear from Figs. 5 and 6 thatthe upper strain gauge array, including SU1, SU2, SU3 andSU4, showed the largest changes in strain values and greatestresponse to pressure changes in the annulus region between thesleeve and the main pipe.

This difference in response between the upper strain gaugearray (SU) and lower strain gauge array (SD) is attributed to theproximity of SU to the butt strap, whereas the SD was less than10 cm from the butt strap. Closer examination of the trends, asseen in Figs. 5 and 6, indicates that pre-buckling strain changesoccurred approximately 5-10 seconds before the buckling tookplace. The slight deviations from the linear trends in the straingraphs are thereby precursors to buckling. These occur over avery narrow pressure change range and can be of practical useas an indicator that buckling is about to happen if the system isconfigured as a remote monitoring station designed to track

Fig. 4. Collapsed area that occurred during the experiment.



these changes continuously. It is very important to notice thatthe trends shown in Fig. 5 and Fig. 7 can be used to indicateboth the occurrence of buckling and its approximate location.This is demonstrated by the readings of SU4, SU5, SD4 and SD5about 5 seconds before the buckling. The sharp jump in strainreadings is shown clearly in Figs. 5 and 6; see SU1/SD1, SU3/SD3 and SU4/SD4. This indicates that the locations of these sen-sors are the optimum, in particular SU3 and SD3. This dramaticshift results from a pressure increase of approximately 7.5%,which simply reinforces that buckling is a nonlinear event. Thebuckling behavior can be made to stand out from normal elasticresponse by correcting for the pressure changes. If the data inFig. 6 are examined, SU5 appears to vary only with pressure andis not affected by the buckling. If all data points at each pressureincrement are divided by the corresponding strain value given bySU5, the strains are normalized and the influence of pressure iseliminated, Fig. 8.

The data clearly shows that the ratio of surface strains on thesleeve and butt strap to a reference value that tracks pressuregives a very clear indication when buckling occurs. For a field sys-tem, a monitoring package would be required with the capabilityto process the raw FBG data into strains, then to compute thestrain ratios, then to determine when and where buckling occurs,and finally to relay that information remotely to a data station.

CONCLUSIONS

The direct welded sleeve pipe did not exhibit the collapse phe-nomena even at a 1,000 psi pressure difference in the annulusregion. This is due to the sleeve configuration, which allowedthe pipe to be exposed to uniform pressure in all directions(360°). The butt strapped sleeved pipe with the specificationpreviously mentioned collapsed at a pressure difference of 430psi between the sleeve butt strap and the main pipe. The pres-ence of the butt strap section on the sleeved pipe created a lo-calized pressure vessel, which resulted in a collapse at less than430 psi pressure difference between the main pipe and the buttstrap sleeve with the pipe specification previously mentioned.The FBG sensor system can be configured to detect the criticalpressure difference in the sleeve annulus. Therefore, it can beutilized to predict the collapse before it occurs. Although FBGhas shown the capability to predict collapse in a sleeved pipe,the obtained results cannot be generalized for all cases ofsleeved pipes with different dimensions and thickness.

ACKNOWLEDGMENTS

The authors would like to thank Saudi Aramco managementfor their permission to present and publish this article.

REFERENCES

1. Chatzidouros, E.V., Papazoglou, V.J., Tsiourva, T.E. andPantelis, D.I.: “Hydrogen Effect on Fracture Toughness ofPipeline Steel Welds, with In-Situ Hydrogen Charging,”International Journal of Hydrogen Energy, Vol. 36,

Fig. 5. Temperature compensated strain (SU1-SU5) vs. time.

Fig. 6. Temperature compensated strain (SD1-SD5) vs. time (40 minutes time scale).

Fig. 7. Magnified time scale (1 minute total scale) of Fig. 8 showing details ofsensors’ response before, during and after buckling.

Fig. 8. Temperature compensated strain ratio (SU#/SU5 and SD#/SU5).



No. 49, September 2011, pp. 12,626-12,643.

2. Han, Y.D., Jing, H.Y. and Xua, L.Y.: “Welding Heat InputEffect on the Hydrogen Permeation in the X80 SteelWelded Joints,” Materials Chemistry and Physics, Vol. 132,No. 1, January 16, 2012, pp. 216-222.

3. Maaskant, R., Alavie, Q.T., Measures, R.M., Tadroqb, G.,Rizkalla, S.H. and Guha-Thakurtad, A.: “Fiber OpticBragg Grating Sensors for Bridge Monitoring,” Cementand Concrete Composites, Vol. 19, No. 1, 1997, pp. 21-33.

4. Majumder, M., Gangopadhyay, T.K., Chakraborty, A.K.,Dasgupta, K. and Bhattacharya, D.K.: “Fiber BraggGratings in Structural Health Monitoring — Present Statusand Applications,” Sensors and Actuators A: Physical, Vol.147, No. 1, 2008, pp. 150-164.

BIOGRAPHIES

Bander F. Al-Daajani joined SaudiAramco in October 2001 and beganworking in the Corrosion Services Unitof the Research and DevelopmentCenter (R&DC) as a Lab Scientist. InApril 2003, he started his fielddeployment with the Tanajib gas plant

as an Operation Engineer. Then Bander moved to theRiyadh refinery as a Process Engineer for 1 year, and thenworked as a Corrosion Engineer for the remaining periodof his 3-year assignment. He led some projects during thisassignment, such as the installation and implementation offiber optic sensors in the refinery.

In June 2006, Bander rejoined R&DC as a Lab Scientistand worked with the Materials Performance Group. Hecontributed to different upstream research projects and hadthe opportunity to lead some activities. Bander has also ledand contributed to some activities in the technical supportprogram, such as the assessment of the Pinpoint SystemProject and the efforts to identify a suitable internal coatingsystem for the Arabiyah and Hasbah trunk lines.

He is currently assigned to the Nanotechnology sub-teamunder the Design Nano Application Team at the R&DC.Bander contributes to nano-material, metallic coating andnano-structured coating activities.

Bander has published three technical papers as the mainauthor and five other papers as coauthor in addition toseveral submitted innovative ideas.

In 2000, he received his B.S. degree in ChemicalEngineering from King Saud University, Riyadh, SaudiArabia.

Waleed A. Al-Obaid is a Specialist LabTechnician in the Research andDevelopment Center (R&DC) at SaudiAramco. He joined Saudi Aramco in1991 after successful completion ofthe Saudi Technical DevelopmentProgram (STDP) in the company.

Waleed has been contributing to several research projects,including Materials Performance Testing, CorrosionMonitoring and Prediction, and Development of Nano-structured Materials.

He is the author of several articles in the area ofCorrosion Science and Nanotechnology.

as an Operation Engineer. Then Bander moved to the

Waleed has been contributing to several research projects,



Bassam A. Al-Matar joined SaudiAramco’s College Preparatory Programin 1996. After receiving his B.S. degreein Mechanical Engineering in 2002from King Fahd University ofPetroleum and Minerals (KFUPM),Dhahran, Saudi Arabia, Bassam went

to work with the Northern Area Pipelines Department(NAPD) from 2002 until 2004. He then moved to thePipeline Technical Support Division’s Instrument ScrapingUnit for a period of 1 year. Bassam was then assigned tothe Inspection Unit of NAPD until 2008.

After that time, he became the Inspection UnitSupervisor, until 2011, when he was moved to NAPD’sProject Coordination Unit.

Bassam’s experience includes the testing and piloting ofseveral technologies related to new inspection methods andcoating systems, which were completed successfully.

Dr. Ihsan M. Al-Taie joined SaudiAramco’s Research and DevelopmentCenter (R&DC) in 2001. Currently, heis the team leader of the Design NanoApplications R&D Division. Prior tothis, Ihsan worked as a ResearchScientist at the Canadian Ministry of

Natural Resources. He received his Ph.D. degree in High Temperature

Materials and Corrosion from Manchester University,Manchester, U.K., in 1992.

Wasim A. Jweihan has extensiveindustrial experience in engineering andmanufacturing and many years ofexperience in commercial management.Working at SOGEC Engineering for 1year, he has designed the cathodicprotection system for pipelines and

steel structure. Wasim then moved at Zamil Group HoldingCompany, selling technology and products. For 3 years hehelped develop nonintrusive corrosion monitoringtechnology from FOX-TEK ranging from fiber optics toPinPoint technology. Wasim then changed job roles, tohandle more international accounts, continuing to developmore products and technologies, such cooling towers, plateheat exchangers, multiphase flow meters, and crude andfuel chemical additives. He is now a unit manager withZamil.

In 2006, Wasim received his B.S. degree in MechatronicsEngineering from Philadelphia University, Trevose, PA. Heis a registered professional engineer in the JordanianEngineering Association.

Thierry Cherpillod is the VicePresident of Operations at FOX-TEKCanada. He is responsible for themanagement of operations,engineering, research and development,and project management. Thierry isalso one of the founding members.

Prior to assuming this position, Thierry worked for 11years as a Research Engineer with the Space Dynamics,Controls and Robotics Group at the Institute for AerospaceStudies, at the University of Toronto. There, he wasresponsible for the custom design of a wide variety ofadvanced sensor systems, and embedded control systemsfor a number of robotics projects and satellite simulationsystems. In the past, Thierry has also been involved inindustrial engineering projects for Aventech Research(aircraft mounted meteorological systems), Electro-Photonics Corp. (fiber optic measurement systems), YorkUniversity’s Human Performance lad (zero-g neuralfeedback measuring systems) and Dynacon Enterprises(robotics position sensing technologies).

He received his B.S. degree in Electronics Technologyfrom Ryerson Polytechnic Institute, Toronto, Ontario,Canada.

to work with the Northern Area Pipelines Department

Natural Resources.

steel structure. Wasim then moved at Zamil Group Holding

Prior to assuming this position, Thierry worked for 11



ABSTRACT rates in vertically completed wells1. Following the field’s initialdevelopment with single lateral wells, the reservoir contact wasgradually increased by drilling 2 km and using 3+ km lateralwells. From 1998 to 2001, significant improvements in wellperformance, demonstrated in increased productivity index(PI), lower drawdown and further delays in gas coning, led tothe evolution of maximum reservoir contact (MRC) wells. Inearly 2002, the first MRC well was drilled with a total reser-voir contact of 8.5 km using an open hole completion. Drillingexperience and production performance of this well were presented in previous papers2, 3.

With the ability to contact more reservoir volumes with asingle horizontal well, either in a single lateral or with multiplelaterals, came the need for much more sophisticated flow control. The main driver for developing advanced well comple-tions (AWCs) has been the desire to increase the well performancefrom horizontal and MRC wells. The main advantage of AWCsis their ability to improve oil recovery through better flowmanagement from the different sections of reservoir contact.With this increased complexity in well configuration, theAWC’s drilling, completion and operating costs rose. Thisgreater investment must be justified by significant improve-ments in recovery from all contacted areas, and a reduction inthe number of development wells and in the need for well interventions.

The evolution of a more complex well and AWC architecturepushed the limit of the existing numerical reservoir simulation’scapability to design and optimize these types of MRC wells.Modeling and optimization are the two key challenges in theperformance evaluation of a complex well equipped with anAWC. Saudi Aramco grasped the situation clearly: as the com-plexity of well configurations increases, new challenges tomodeling their performances arises, such as the need for a detailed description of pressure gradients along the lateralwellbore, taking into account slip, friction and gravity acceler-ation, as well as a detailed representation of the well path and a corresponding numerical calculation of the grid-cell connec-tion factors4. Other important issues are cross flow among laterals and the ability to model advanced control devices, suchas inflow control devices (ICDs), inflow control valves (ICVs),chokes, downhole separators, etc. The increased complexity ofthe numerical modeling is compounded by the lack of appro-priate visualization tools to enable a production performance

It is challenging to arrive at an optimal well placement andcompletion design for maximum reservoir contact (MRC)wells in heterogeneous oil and gas reservoirs. Saudi Aramcoinitiated a new workflow, in collaboration with a service com-pany, to determine an optimal design based on the integratedsoftware packages of PetrelTM and Saudi Aramco’s POWERSTM

simulator. Applying sensitivity and optimization algorithms,this workflow can conduct simulation runs optimizing well ar-chitecture, smart completions with inflow control devices/in-flow control valves (ICDs/ICVs), and lateral and vertical shiftsof the well to obtain maximum oil and gas recovery. The newworkflow proved to have robust functionality and providedboth significant cost savings and optimal oil and gas recovery.

Three case studies are discussed in this article. The first caseinvolved a trilateral well’s optimization in an oil field that isunder development. Based on the sensitivity analysis, a shiftingof the well’s location was required. The most significant im-pact of the workflow was to provide higher oil recovery anddelayed water breakthrough for several years.

In the second case, the new workflow assessed a proposedsidetrack and concluded that it was not a good option, due tofast water influx from the west flank. This workflow movedthe sidetrack lateral 207 m to the east, and the completion wasdesigned to equip the well with an ICD and blank pipes. Simu-lations showed that the optimized sidetrack provided 50%more oil recovery than the well that was not moved.

The third case was to propose the best location and well de-sign for a complex dual-lateral maintain potential (MP) well.The most sensitive parameters were movement of the well tothe north and the vertical locations, its motherbore length andthe flow rate of the oil. In simulations, shifting the dual-later-als 750 m north and designing a completion with optimizedICDs for flow control and a 1,750 m motherbore length pro-vided double the cumulative oil production of the single wellthat was manually designed and completed.

INTRODUCTION

In the mid-1990s, Saudi Aramco developed an oil field with anoriginal gas cap using a 1 km single lateral to delay, and mini-mize the potential for, early gas breakthrough and/or waterconing, and to produce at well rates in excess of critical coning

Application of a Newly DevelopedWorkflow to Design and Optimize MRC and Smart Well Completions

Authors: Dr. Shamsuddin H. Shenawi, Wahyu Hidayat, M. Methgal Al-Shammari, Khalid A. Nasser, Abdulhamed A. Al-Faleh,Dr. Umar A. Al-Nahdi, Yahya A. Ghuwaidi and Nabil Mekki



analysis of the complex MRC well with AWC. Saudi Aramcodeveloped a new well equation to incorporate a pressure dropacross equalizers with the pressure drop caused by reservoirdrawdown in its proprietary simulator POWERSTM. The newwell equation for ICD/ICV performance can be solved simulta-neously with reservoir mass balance equations to yield a stablesolution in a numerically efficient manner5.

MODELING OF COMPLEX MRC WELLS WITH AWC

Although several attempts have been made to establishmethodologies for the evaluation of a complex well with anAWC, there is no standard process available in the petroleumindustry that offers a comprehensive numerical modeling capa-bility and a visualization tool. Saudi Aramco initiated a studyto develop a new workflow4 that was easy to use, efficient andable to model ICDs using advanced reservoir simulationmethodology. The developed workflow is illustrated in Fig. 1.In this workflow, a small sector model was extracted from afull-field reservoir simulation model. The near wellbore modelingwas applied to design and model possible complex well architectures. A neural network and a genetic optimization algorithm were used to determine the optimum well architec-ture, one that provided the maximum oil production consideringthe geological uncertainty. The most likely geological realizationand the optimum well architecture were used to specify theplacement and number of ICDs in an AWC design that providedthe optimum oil production.

NEW WORKFLOW FOR SIMULATION OF COMPLEX

MRC WELLS WITH AWC

After successful development of the workflow to simulate com-plex MRC wells with AWC, Saudi Aramco initiated a projectin 2008 to automate the design and placement of complex architecture wells in the best possible areas and in productivezones, and to optimize the design of ICDs in multilateral wells.Figure 2 illustrates the new workflow. The MRC optimizationworkflow processes consist of three main stages: (1) buildingthe initial simulation case, (2) performing the optimization,and (3) analyzing the results. The following steps were devel-oped to complete the new workflow.

Define the Area in Which to Place the Complex MRC Well

In this new workflow, the proposed region of interest (ROI)where the new complex MRC well is to be placed is selected ina full-field reservoir simulation model. The placement of thecomplex architecture MRC well in the selected area is deter-mined using the PetrelTM workflow. The possible scenarios forthe architecture of the MRC wells is illustrated in Fig. 3, alongwith the selected area. The selected area is refined with finergrid blocks, whereas grid blocks outside of the selected areaare kept as original. This type of grid block system is called atartan grid system, and it provides a more accurate simulatedsolution around the new complex MRC well.

Build the Simulation Model

A reservoir simulation case is developed with the initial MRCwell architecture, which uses a uniform placement of ICDs/ICVs along each lateral. Following the selection of the ROI, anew well, either a sidetrack well or a maintain potential (MP)well, is completed in the identified ROI. In addition, the trajec-tories of the well’s laterals are defined, if needed, to cover addi-tional space. Once the initial well trajectory is determined, aninitial completion strategy is implemented. A tartan grid sys-tem or a refined sector model in the original simulation modelis then used to enhance the accuracy and the speed of the simu-lation. An initial development strategy for the field and the

Fig. 1. Developed workflow to design and optimize complex MRC wells4.

Fig. 2. New workflow to design and optimize complex MRC wells.

Fig. 3. Possible scenarios of MRC well architecture and selected infill well area.



wells is established, including production and injection con-straints, conditional actions of the wells and the group, andfield level constraints. The preceding steps provide the neededdata for creating the initial simulation case. This simulationcase represents the base case with the initial well architectureand AWC design. The initial case is run for 25 years and theproduction performance is analyzed.

Uncertainty and Optimization

Many possible parameters can affect well performance, due tothe various well architecture design and placement strategies inthe proposed area. The first step is to conduct a sensitivityanalysis to identify those parameters that will have the mostsignificant impact on well production performance. This im-portant step serves to narrow down the search space for thelater optimization. A tornado chart is provided by the work-flow to identify the most sensitive parameters impacting thewell production performance after running tens of reservoirsimulation cases. Generally, the most sensitive parameters are ashift of well placement (from north to south, from east to west,and vertically), the number of laterals, the lengths of the moth-erbore and laterals, the azimuths of the laterals, the angle ordip of the laterals, targeted production rates and the number ofICDs/ICVs in each lateral segment. The workflow can assessthe geological uncertainty in the distributed geological andpetrophysical parameters.

In this workflow, the objective function is defined; thiscould be achieving the highest cumulative oil production, thelongest plateau or the net present value. The objective can bedesigned also for a full field, a group of wells or a single well.In this workflow, Saudi Aramco’s simulator POWERSTM isused to assess various combinations of parameters and differ-ent ranges of uncertainties. Using the optimization algorithmsavailable (simplex optimizer or neural network), the workflowbuilds and tests different designs in well architecture and com-pletion until it finds the optimum solutions. This process’sturnaround time is mainly dictated by the time needed for tensof simulation runs with various combinations of parameters.Another faster but less reliable solution is to build proxy modelsthat can optimize the sensitivity parameters without runningthe actual simulation models. These results must be reevaluatedusing the simulator to ensure the accuracy of the results.

RESULTS

Case 1: A New Multilateral Well Assessment

This section presents the case of a single well design and place-ment optimization for a field that is under development. Thewell is located at the northern region of the field, surroundedby peripheral injectors and its offset producers. Even though itis a single well optimization at a particular region, a full-fieldsimulation model with multimillion cells was used.

Many possible parameters can affect well performance, due to

the various well design and placement strategies. The first stepis to conduct a sensitivity analysis to identify those parametersthat will have the most significant impact on well performance.The next step is to select the most important parameters forfurther optimization by incorporating combinations of optimizedparameters, which are selected based on the central compositedesign. This approach allows the selection of enough combina-tion values to represent all possible combinations.

In this particular case, seven sensitivity parameters wereconsidered. Table 1 shows the sensitized parameters and theirranges of minimum and maximum values. As a base case, allparameters are set up at their mid-values. Sensitivity simula-tion runs for the combinations of the optimized parameterswere done by varying minimum and maximum values, and applying the Experimental Design Artificial Intelligence algo-rithm. The cumulative oil production and water cut of the wellwere used as sensitivity parameter indicators. Tornado chartswere used to compare the sensitivity of all parameters. The tornado charts in Fig. 4 show that the most sensitive parame-ters are shifting the well location in the east to west (X) andnorth to south (Y) directions. The other parameters are lesssensitive, such as shifting the well toward the vertical (Z), thenumber of laterals, the motherbore length and the lateral’s azimuth.

The next step is to proceed with well optimization. The wellconfiguration that was selected for optimization is a dual-lat-eral well configuration. Based on the sensitivity result, threeparameters were selected for further well placement optimiza-tion; these were shifting the wells in the X and Y directions,

Table 1. Sensitized parameters of well design and placement

No. Variables Minimum Maximum

1 Well Length (ft) 3,000 5,000

2 Well Shift, X (m) -750 750

3 Well Shift, Y (m) -750 750

4 Well Shift, Z (ft) -25 25

5 Number of Lateral 1 3

6 Lateral Length (ft) 2,000 4,000

7Lateral Azimuth (degree)

30 60

Fig. 4. Tornado charts: Sensitivity of optimization parameters.



and the motherbore length, Table 2. Each optimization caseconsisted of combinations of these three parameter valueswithin the minimum and maximum range. More than 30 simu-lation runs were conducted to find the optimum parameters.Figures 5 to 7 show the cumulative oil production, oil produc-tion rate and water cut, respectively, for all optimization simu-lation runs. Each graph shows the performances of anoptimized well alone and an optimized well plus its offset wellsfor 22 years of prediction. The optimized case resulted in betteroil production and significant delay of water breakthrough.There was performance consistency between the optimized wellalone and the optimized well plus its offset wells. This showsthat the performance improvement at the well of interest doesnot significantly affect its offset wells’ performance. Figure 8

shows the optimum well location, one achieved by shifting thewell in an eastern direction.

Further steps were taken to attempt to create a response surface proxy of the three optimized parameters, and then aMontecarlo simulation was used to obtain the highest value fromthe objective function, which is cumulative oil production in thiscase. The best optimized cases from the response surface proxyare generally in agreement with those from multiple realization simulation cases if the number of runs is more than 30.

The advantage of using an uncertainty and optimizationworkflow is that the simulation model input preparation forvarious well designs and placements can be done automaticallyand quickly. Traditionally, preparing simulation input manu-ally may take days. For this type of case, one cycle of optimiza-tion takes three to four days to complete. Most of the time isconsumed running the simulation cases.

Case 2: Sidetrack of a Vertical Producer Assessment

The vertical oil well producer in this case experienced water invasion from the nearby aquifer. The well needed to be side-tracked to continue producing oil. The proposed sidetrack areaand the initial assessment well, running in the north to south

Fig. 7. Water cut of all optimization cases (Case 1).

Fig. 6. Oil production rate of all optimization cases (Case 1).

Fig. 8. Well location: base vs. optimized (Case 1).

Fig. 5. Cumulative oil production of all optimization cases (Case 1).

Table 2. Optimized parameters of well design and placement

No. Variables Minimum Maximum

1 Well Length (ft) 3,000 5,000

2 Well Shift, X (m) -750 750

3 Well Shift, Y (m) -750 750



direction, were defined in the reservoir simulation model, Fig. 9.Two sidetrack scenarios were assessed by the simulator, withICDs placed at uniform intervals. Both sidetracks experiencedhigh water cut very quickly due to the nearby aquifer. The pro-posed sidetrack area needed to be moved to the east, away fromthe aquifer. Figure 10 illustrates the new sidetrack area with ahybrid tartan grid system imposed on the sidetrack of the sim-ulation model. The north-to-south sidetrack well was placed inthe middle of the new sidetrack area. The new workflow opti-mized the design and placement of ICDs (equalizers) along thesidetracked horizontal well. The optimized ICD locations are

shown in Fig. 11. Blank pipes were installed to prevent waterfingering from the aquifer in some sections of the lateral. Fur-ther optimization to improve productivity was carried out bythe new workflow, which determined that moving the well 207m eastward provided the highest oil production, Fig. 12.

Case 3: New MP Horizontal Well Assessment

The same reservoir simulation model used in Case 2 was usedto design and assess the production performance of a proposednew dual-lateral horizontal well. The proposed new drillingarea and the initial dual-horizontal well are defined in a tartangrid system, Fig. 13. The initial motherbore length was 9,000ft, covering the drilling area defined in the workflow. Theother lateral length was 1,250 ft. The following parameterswere sensitized, using the experimental design, to determinethe optimized combination of parameters that would providethe highest cumulative oil recovery in a 25-year simulation period:

• Motherbore length.• Lateral length.• Offset length for the lateral from the heel of the motherbore.• Lateral azimuth where the lateral is kicked off from the

motherbore.

Fig. 12. Movement of the well 207 m to the east provided the highest oil recovery(Case 2).

Fig. 13. Proposed new drilling area and initial dual-horizontal well, defined in thetartan grid system (Case 3).

Fig. 9. Sidetrack of a vertical producer near an aquifer (Case 2).

Fig. 11. Optimized design and placement of ICDs (Case 2).

Fig. 10. Simulation of the new sidetrack well using the tartan grid system (Case 2).



• Shift of both laterals in a north to south direction. • Compartment lengths along both laterals.• Number of ICDs per compartment.• Initial maximum oil production rate.Figure 14 shows the tornado chart depicting the positive

and negative impacts of the sensitized parameters on the cumu-lative oil produced. Figure 15 illustrates the cumulative oil pro-duced by a different combination of these same parametersand shows values for those parameters that provided the high-est oil recovery. The motherbore was reduced from 9,000 ft to1,750 ft, and the well was moved northward 750 ft. The bestcase provided the highest oil recovery without ICDs since the wellis far away from the aquifer and no significant water invasionwas observed during the simulation period.

CONCLUSIONS

The new workflow, the first in the petroleum industry, wassuccessfully developed and tested in three oil fields and one gasfield of Saudi Arabia. This workflow seamlessly conjoins thegeological model in PetrelTM with the reservoir simulationmodel in POWERSTM to run tens to hundreds of simulationruns using various combinations of sensitive parameters relatedto complex multilateral well architecture and AWC devices.The following conclusions can be drawn:

• The industry’s first new workflow has been developed to design and optimize the complex architecture of multilat-eral wells that are equipped with AWC devices such as ICDs or ICVs.

• The new workflow seamlessly developed and conducted tens to hundreds of reservoir simulation runs with various combinations of geological, petrophysical and complex architecture parameters impacting multilateral wells equipped with AWC devices.

• In all cases, this workflow provided the optimum combination of parameters that achieves the highest oil recovery.

• This new workflow could prevent the failed or inefficient design of well architecture, well placement and AWCs, thereby preventing the loss of such wells’ high capital investment.

• The advantage of using uncertainty and optimization in the new workflow is that the simulation model input preparation for various well design and placement can be done automatically and quickly. Traditionally, preparing simulation runs manually may take days to weeks. In this study, one cycle of optimization takes three to four days tocomplete. Most of the time is consumed in running the tens to hundreds of simulation cases.

ACKNOWLEDGMENTS


This article was presented at the SPE Saudi Arabia SectionTechnical Symposium and Exhibition, al-Khobar, Saudi Arabia, April 8-11, 2012.

REFERENCES

1. Salamy, S.P., Al-Mubarak, H.K., Hembling, D.E. and Al-Ghamdi, M.S.: “Deployed Smart Technologies Enablers forImproving Well Performance in Tight Reservoirs — Case:Shaybah Field, Saudi Arabia,” SPE paper 99281, presentedat the Intelligent Energy Conference and Exhibition,Amsterdam, The Netherlands, April 11-13, 2006.

2. Dossary, A.S. and Mahgroub, A.A.: “Challenges andAchievements of Drilling Maximum Reservoir Contact(MRC) Wells in Shaybah Field,” SPE paper 85307,presented at the SPE/IADC Middle East DrillingTechnology Conference and Exhibition, Abu Dhabi,U.A.E., October 20-22, 2003.

Fig. 14. Tornado chart showing the impacts of sensitized parameters on cumulativeoil produced in simulation cases (Case 3).

Fig. 15. Parameters providing the highest oil recovery (Case 3).



creo

3. Saleri, N.G., Salamy, S.P., Al-Mubarak, H.K., Sadler, R.K.,Dossary, A.S. and Muraikhi, A.J.: “Shaybah-220: AMaximum Reservoir Contact (MRC) Well and ItsImplications for Developing Tight Facies Reservoirs,” SPEReservoir Evaluation & Engineering Journal, Vol. 7, No.4, August 2004, pp. 316-320.

4. Moreno, J.C., Bradley, D., Gurpinar, O., et al.: “OptimizedWorkflow for Designing Complex Wells,” SPE paper99999, presented at the SPE Europec/EAGE AnnualConference and Exhibition, Vienna, Austria, June 12-15,2006.

5. Su, H. and Dogru, A.H.: “Modeling of EqualizerProduction System and Smart Well Applications in Full-Field Studies,” SPE paper 111288, presented at theSPE/EAGE Reservoir Characterization and SimulationConference, Abu Dhabi, U.A.E., October 28-31, 2007.

BIOGRAPHIES

Dr. Shamsuddin H. Shenawi is aReservoir Simulation Specialist in theReservoir Simulation Division of SaudiAramco. Prior to joining SaudiAramco in July 2005, he was aReservoir Simulation Advisor in theWorldwide Technical Services of theOccidental Oil Company in Houston.

Shamsuddin mentors and trains young professionals in theSimulation Division and in the Upstream ProfessionalDevelopment Center (UPDC) in Saudi Aramco.

He received his B.Eng. degree from the RangoonInstitute of Technology in Burma (Myanmar) and his M.S.degree from King Fahd University of Petroleum andMinerals (KFUPM), Dhahran, Saudi Arabia, both inPetroleum Engineering. In 1994, Shamsuddin obtained hisPh.D. in Petroleum Engineering from Texas A&MUniversity, College Station, TX.

He has published several Society of Petroleum Engineers(SPE) papers on fractured reservoir simulation, tight gasreservoirs, hydraulic unit rock typing and smart wellssimulation.

Wahyu Hidayat is a ReservoirSimulation Engineer in the ReservoirSimulation and DescriptionDepartment of Saudi Aramco. He iscurrently working on the Manifa fieldincrement project. Prior to joiningSaudi Aramco in 2007, Wahyu worked

for Chevron Indonesia for 14 years. In 1989, he received his B.S. degree in Petroleum

Engineering from the Institute of Technology, Bandung,Indonesia, and in 1992, he received his M.E. degree inPetroleum Engineering from Texas A&M University,College Station, TX.

M. Methgal Al-Shammari joined SaudiAramco in 1984 and has worked indiverse technical and supervisorypositions in the company’s E&Pbusiness areas. Beginning in 1994, hejoined the Reservoir SimulationDivision (RSD), where he worked on

various projects involving carbonate field modeling studiesfor oil and gas. Methgal led the Simulation SupportDepartment from 1998 to 1999. Then he was put in chargeof the Abqaiq Reservoir Simulation Unit in RSD for 7years. In 2007, Methgal became the General Supervisor forthe Southern Area fields of RSD for 2 years. He is currentlyworking as a Petroleum Engineering Consultant for variousinnovative technical projects, including the maximumreservoir contact (MRC) optimization project, where he isthe coordinator.

Methgal served as Chairman of the 1999 Society ofPetroleum Engineers (SPE) Technical Symposium inDhahran.

In 1984, he received his B.S. degree in PetroleumEngineering from King Fahd University of Petroleum andMinerals (KFUPM), Dhahran, Saudi Arabia. In 1990,Methgal received his M.S. degree in Petroleum Engineeringfrom the University of Southern California (USC), LosAngeles, CA.

Khalid A. Nasser is a PetroleumEngineer Systems Analyst in theReservoir Simulation Support Divisionof Saudi Aramco. He has more thansix years of experience in supportingreservoir simulation engineers withapplications to help them build, quality

check and visualize their simulation models in 2D and 3D.For the last three years, Khalid has been developing a state-of-the-art, one-of-a-kind software platform for maximumreservoir contact (MRC) wells that streamlines, automatesand optimizes the workflow of designing well trajectoryand smart well completion configurations in collaborationwith Schlumberger SIS Abingdon Technology Center.

He received his B.S. degree in Software Engineeringfrom King Fahd University of Petroleum and Minerals(KFUPM), Dhahran, Saudi Arabia.

Abdulhamed A. Al-Faleh is aPetroleum Engineering SystemsAnalyst. He has 3 years of experiencein reservoir simulation, ranging fromdevelopment and support of reservoirsimulation applications to conductingreservoir simulation studies.

Abdulhamed was a key member in the development of themaximum reservoir contact (MRC) wells optimizationworkflow that streamlines, automates and optimizes theprocess of designing well trajectory and smart completionconfigurations.

He received his B.S. degree (with first class honors) inSoftware Engineering from King Fahd University ofPetroleum and Minerals (KFUPM), Dhahran, Saudi Arabia.

various projects involving carbonate field modeling studies

check and visualize their simulation models in 2D and 3D.

Abdulhamed was a key member in the development of the

for Chevron Indonesia for 14 years.



Dr. Umar A. Al-Nahdi is the team leadfor the Advanced Reservoir Technologyteam. For the past 12 years, he hasworked in several differentdepartments, including the Drilling andWorkover Systems Division, SimulationSystems Division and EXPEC Advanced

Research Center. Umar has also participated in thedevelopment of Saudi Aramco’s in-house reservoirsimulator (POWERS™), the MRC/Complex Wellsoptimization workflow, a well approval package andseveral other major projects. His areas of specialty includehigh performance computing, mathematical computation,reservoir simulation and modeling.

Umar received his B.S. degree in Computer Science fromKing Fahd University of Petroleum and Minerals (KFUPM),Dhahran, Saudi Arabia. He also has a M.S. degree inPetroleum Engineering from Heriot-Watt University,Edinburgh, U.K., and a Ph.D. degree in PetroleumEngineering from the Colorado School of Mines, Golden,CO.

Yahya A. Ghuwaidi is a SeniorReservoir Engineer who is currentlythe Lead Engineer for day-to-dayintegration of reservoir models for allfields in the Northern Area. He startedhis oil field career in 2002 withSchlumberger in Saudi Arabia as a

Reservoir Simulation Engineer dealing with all mature oiland gas fields in the region. Yahya then worked as aReservoir Simulation Engineer and field study leader forSchlumberger SIS Kuwait. His last position before joiningSaudi Aramco was as a Senior Reservoir Engineer inSchlumberger SIS Saudi Arabia.

Yahya received his B.Eng. degree in PetroleumEngineering from King Saud University, Riyadh, SaudiArabia, in 2002.

He has been a member of the Society of PetroleumEngineers (SPE) since 1998.

Nabil Mekki is a Senior ReservoirEngineer with Schlumberger workingin al-Khobar, Saudi Arabia. He joinedSchlumberger Information Solution(SIS) in 2004 as a ReservoirSimulation Engineer and was involvedin various projects in North Africa.

Nabil also worked for a period of 2 years in Angola as anindependent consultant responsible for advising on fieldperformance optimization and for producing fieldperformance profiles for the asset team located in Luanda.In 2010, he began working in Saudi Arabia with theMRC/Complex Wells collaboration project between SaudiAramco and SIS to develop and deploy complex welloptimization workflows in PetrelTM software and thePOWERSTM simulator.

Nabil also delivered several reservoir engineeringtraining courses in Algeria, Tunisia and Mauritania.

In 2001, he received his B.S. degree in PetroleumEngineering from the Faculty of Hydrocarbon andChemistry at the University of Boumerdes, Boumerdes,Algeria.

Research Center. Umar has also participated in the

Reservoir Simulation Engineer dealing with all mature oil

Nabil also worked for a period of 2 years in Angola as an



ABSTRACT

powder removed from their pipelines. For example, whereassome studies report black powder as being predominately ironsulfides1-3, others report the complete absence of iron sulfidesbut the presence of iron oxides and hydroxides, such as Fe3O4

and FeOOH4, 6, while still others report a combination of allof these products (iron sulfides, iron carbonates and iron ox-ides)5. In the Middle East, with its large unburied onshore net-works, the main composition of black powder is Fe3O4 mixedwith smaller amounts of FeOOH and iron carbonates7-10.

These products have one common source: they are formedinside natural gas pipelines because of the corrosion of their in-ternal walls1-10. More specifically, they are formed by reactionsof the iron (Fe) present in the ferrous pipeline steel with con-densed moisture containing carbon dioxide (CO2), hydrogensulfide (H2S) or oxygen (O2).

Corrosion due to CO2, H2S or O2 in sales gas pipelines haswell-established mechanisms. The following are simplified elec-trochemical reactions that describe these corrosion processesand their respective corrosion products. It is important to notethat in all of these electrochemical reactions, condensed wateris a necessary condition for these reactions to proceed.

Siderite-FeCO3 (CO2 Corrosion)

Siderite-FeCO3 corrosion products are formed when CO2, anaturally occurring constituent in some natural gas, is dis-

Sales gas pipeline systems with large diameters and longpipeline lengths can experience the formation of large quanti-ties of corrosion products commonly known as “black pow-der.” A variety of iron oxides, iron carbonates, iron sulfidesand other contaminants comprise black powder. Black powderformation can be caused by the presence of corrosive gases, in-cluding oxygen, carbon dioxide or hydrogen sulfide, dissolvedin condensed water in the lines.

Generally, pipeline companies practice various methods tomanage and control black powder in their gas networks. Thesemethods can be divided into three broad categories: (1) re-moval, (2) mitigation, and (3) prevention. Although mitigationwith corrosion inhibitors is typically practiced in lines trans-porting wet sour gas, it is not normally practiced in sales gaslines.

This article describes a research study conducted to assessthe performance of 14 commercial and specially formulated inhibitors proposed to mitigate the formation of iron oxidebased black powder under simulated sales gas conditions. Special test methods developed in-house were used to evaluatethese inhibitors. Two inhibitors passed the tests, showing acorrosion inhibition effectiveness of approximately 90% andno pitting attack under the simulated sales gas environment.

INTRODUCTION

Black powder is a worldwide phenomenon experienced bymost, if not all, sales gas pipeline operators with internal un-coated lines1-6. Black powder can have a serious impact oncustomer satisfaction and pipeline operations, namely delays ininstrument scraping, reduced in-line inspection accuracy, andcontrol valve and pipe erosion. It is found in several forms,such as wet, with a tar-like appearance, or dry, in the form of avery fine powder. Figure 1 shows typical dry black powder.Black powder has been reported in recently commissioned aswell as older sales gas transmission pipelines1-6. Black powdercomprises various forms of corrosion products, namely ironsulfide, iron oxide or iron carbonate. It is mixed or chemicallycombined with any number of contaminants, such as salts,sand, liquid hydrocarbons and metal debris. Different gaspipeline operators report different compositions for the black


Black Powder Inhibitors —Performance Study

Authors: Dr. Abdelmounam M. Al-Sherik, Dr. Arnold L. Lewis, Abduljalil H. Rasheed and Ali A. Al-Jabran

Fig. 1. Fine black powder collected at a scraper door receiver in a sales gaspipeline.


solved in condensed water, thereby producing carbonic acid,which in turn reacts directly with steel to produce FeCO3, inaccordance with these reactions11:

H2O (condensed water) + CO2 (in gas) H2CO3

(carbonic acid) (1)H2CO3 + Fe (pipeline steel) FeCO3 + H2 (2)

Iron Sulfides (H2S Corrosion)

Iron sulfide (FeS) corrosion products are formed when H2S, anaturally occurring constituent in some natural gas, though itis sometimes produced by sulfate-reducing bacteria, is dis-solved in condensed water, thereby producing hydrosulfuricacid, which in turn reacts with the steel wall of the pipeline asper the following reactions1, 2:

H2O (condensed water) + H2S (in gas) H3O+ + HS- (3)HS- + H3O+ + Fe (pipeline steel) FeS + H2 + H2O (4)

Iron Oxides (O2 Corrosion)

Oxygen ingress in gas lines can cause significant corrosion insmall concentrations and even lead to combustion in largeramounts12, 13. A 1988 survey of 44 natural gas transmissionpipeline companies in North America indicated that their gasquality specifications allowed maximum O2 concentrationsranging from 0.01 mol% to 0.1 mol% with a typical value of0.02 mol%12, 13. It has been shown that the oxygen content ofapproximately 0.01 mol% has little effect on steel corrosion inthe presence of stagnant water inside sales gas transmissionpipelines, while the oxygen content of 0.1 mol% producesfairly high corrosion rates. As a general rule of thumb, it hasbeen recommended that transmission pipelines should considerlimiting oxygen concentration to a maximum of 10 ppmv(0.01 mol%)12, 13.

In cyclical wet-dry environments with low dissolved oxygen,iron oxides are usually formed by the direct oxidation of pipe-line steel walls, in accordance with the following reaction11:

4Fe + 2H2O (condensed water) + 3O2 4 α -, - or γ-FeO(OH) (5)In water containing low concentrations of dissolved oxygen,

as is the case in a sales gas environment, γ-FeO(OH) is unsta-ble and will quickly transform to magnetite-Fe3O4 and waterby the following reaction11:

8γ-FeO(OH) + Fe 3Fe3O4 + 4H2O (condensed water)(6)

Subsequently, if the water is saturated with dissolved oxygen, then hematite (Fe2O3) is often present11.

BLACK POWDER MANAGEMENT METHODS

Generally, pipeline companies practice several methods tomanage and control black powder in their gas pipeline grid.These methods can be divided into three broad categories: (1)removal methods, (2) mitigation methods and (3) preventionmethods. For the purpose of this article, only mitigation –

specifically, chemical inhibition through the batch treatmentapplication of corrosion inhibitors – will be presented and discussed.

Chemical inhibition is an effective corrosion control methodthat is commonly used in untreated wet sour gas lines. In thoselines, a batch treatment chemical is applied periodically to theinternal walls of the pipeline between scrapings. The concen-tration of the chemical is typically one part inhibitor diluted infour parts diesel, producing a mixture that is 20% inhibitor byvolume. The inhibitor is reapplied periodically on an as-neededbasis. In contrast, corrosion inhibition of pipelines transport-ing “dry” sales gas is not typically practiced. One reason couldbe that the expected corrosion rate in these dry lines is verylow; thereby not affecting the integrity of the pipelines, so mitigation of corrosion through chemical inhibition is unwar-ranted. Even though this reasoning appears logical, the largesurface area of internally uncoated pipelines in the Middle Eastmeans the amount of black powder generated in dry lines canbe tremendous, causing major operational and environmentalproblems as well as erosion failures of pressure control valves.

As mentioned earlier, in the Middle East, the prevalent blackpowder composition is iron oxide with smaller amounts ofiron carbonate; FeS is seldom found as a constituent in MiddleEast black powder. For this reason, in the work presented here,14 commercially available and specially formulated corrosioninhibitors for only the inhibition of an oxygen based corrosionmechanism were studied in a simulated sales gas environment.

EXPERIMENTAL PROCEDURE

Corrosion testing of carbon steel coupons under a simulatedsales gas environment was conducted to evaluate 14 commer-cially available and specially formulated corrosion inhibitorsfor their potential use in batch treating sales gas pipelines. Agas bulk mixture was prepared such that, when used under thelaboratory test conditions, the gas would contain 16.5 psiaCO2 + 0.23 psia O2 + 0.002 psia H2S.

This gas composition was designed to simulate the partialpressures of the active components that do occur in typicalsales gas lines with a maximum of 2 ppm H2S gas.

Several of the chemicals tested in this study could also beapplied continuously in the vapor phase; however, applicationof vapor phase inhibitors in sales gas pipelines was deemed tonot be a cost-effective field solution. Therefore, all testing inthis study was conducted assuming that the chemicals wouldbe used in batch treatment mode.

The original test matrix consisted of 14 corrosion in-hibitors. Two inhibitor diesel ratios were tested: 1:99 and 1:4.The 1:4 ratio is the normal starting concentration used in thefield when treating wet sour gas pipelines, and it typically provides acceptable inhibition effectiveness for a period of sixmonths. In contrast, the 1:99 ratio represents an assumed fieldsituation where only 1% of the originally applied inhibitor remains.




Five of the 14 chemicals formed two separate phases whenmixed with the diesel in both test ratios. After discussions withfield personnel, these five inhibitors were removed from addi-tional testing. Because a chemical that forms two separatephases with diesel cannot be applied effectively by batch treat-ment, additional performance testing was not warranted,therefore, these five were not tested. Table 1 notes the 14 studiedinhibitors, including those five that were removed from furthertesting.

Corrosion Test Coupon Preparation

Rectangular UNS G10100 carbon steel shim stock coupons of120 µm thickness with a total exposed surface area of 10 cm2

were used throughout this study. These cut-to-size steelcoupons were immersed in 50% (v/v) hydrochloric (HCl) acidand sonicated for 20 minutes to remove the as-received millpattern. Following this treatment, the coupons were ground insuccession using 400, 600 and 800 grit silicon carbide paper.The coupons were immediately rinsed thoroughly with distilledwater, followed by an acetone rinse. All cleaned and driedcoupons were then weighed to the nearest 0.1 mg and thisweight was recorded.

The coupons used in this testing were treated with the cor-rosion inhibitors shown in Table 1 by the standard dip-and-drip procedure in the two inhibitor-diesel ratios of 1:99 and1:4. For replication purposes, three coupons were placed ineach bottle using a magnetic rod. The bottle was turned on itsside and continuously rotated to ensure that the three couponswere fully immersed in the inhibitor solution, Fig. 2. After 60seconds of immersion in the inhibitor-diesel mixtures, thecoupons underwent two separate procedures: one for the 1:99ratio and the other for the 1:4 ratio.

For the 1:99 inhibitor-diesel ratio, the coupons were removedfrom their respective bottles and held vertically, so that the excessinhibitor-diesel solution was allowed to drain away, and thenthey were immediately immersed in the corrosion test bottle.

To evaluate the inhibitor film persistency provided by the1:4 inhibitor-diesel ratio mixtures, after the coupons were re-moved from the 60-second immersion, they were placed verti-cally under a high flow rate stream of distilled water for 30seconds. Following this, they were immediately placed intotheir corrosion test bottles. Coupon treatment by the high flowrate stream of distilled water was done to simulate a worstcase scenario, such as water condensation and gas flow in thelines, causing the film’s partial removal.

Immediately after completion of the test, the samples wereremoved and air dried by holding them in a vertical positionwith the bottom edge resting on a paper towel to allow liquidsto drain away. Each set of three coupons was then placed intoinhibited HCl acid and sonicated for 3 minutes to remove anycorrosion products that had formed on the coupon’s surfaces.Finally, the samples were photographed to show the degree ofcorrosion attack on their surfaces.

Corrosion Test Procedure

Immersion tests were performed in 1 liter sealed glass bottleswith gas inlet and exit connectors. Figure 3 shows the testarrangement used for these experiments.

Three coupons were placed at the bottom of each test bottle.For replication purposes, three separate test bottles for eachcondition were used. Each test bottle contained 15 ml ofdeionized water. This volume of liquid resulted in a low liquid

Fig. 2. Photograph showing the dip-and-drip procedure used to form an inhibitorfilm on the coupons prior to corrosion testing.

Corrosion Inhibitor Comments

A Full testing conducted

B Full testing conducted

C Full testing conducted

D Full testing conducted

E Full testing conducted

F Full testing conducted

G Full testing conducted

H Full testing conducted

I Full testing conducted

J Removed from further testing due to incompatibility with diesel

K Removed from further testing due to incompatibility with diesel

L Removed from further testing due to incompatibility with diesel

M Removed from further testing due to incompatibility with diesel

N Removed from further testing due to incompatibility with diesel

Table 1. Corrosion inhibitors tested in this study



volume to sample surface area ratio, which was thought im-portant for simulation of the expected corrosion conditions inan actual sales gas pipeline (corrosion in a thin liquid film).The bottles were then sealed and purged with nitrogen gas for30 minutes to remove oxygen. Following the nitrogen purge, apurge with the test gas was conducted for 15 minutes to ensuresaturation of the headspace with the test gas. As mentioned,the test gas used throughout this work resulted in 16.5 psiaCO2 + 0.23 psia O2 + 0.002 psia H2S in each test bottle. Fol-lowing this initial purge of test gas, the gas inlet valve for eachbottle was left open for the entire 33 day test. The exit valvefor each bottle, however, was kept closed most of the time. Thepressure of the test gas in each bottle was fixed at 2 psig,which allowed a constant gas pressure of 2 psig to be estab-lished and maintained in the headspace of each bottle. Eachday, to replenish the gas mixture in the headspace of the bot-tles, the exit valve for each bottle was opened for a few min-utes, allowing gas to flow through the bottles. The closure ofthe exit valves and parallel connection of the bottles to the gassource were important steps to ensure that the desired diesel-inhibitor ratio remained constant throughout the test and thatthe gas pressure and composition remained consistent through-out the test. All tests were carried out at ambient room temper-ature — approximately 22 °C. The corrosion rates weredetermined by measurement of coupon mass loss and subse-quent calculation.

RESULTS AND DISCUSSION

Figure 4 shows the average corrosion rate and inhibition effec-tiveness for the nine tested inhibitors, A to I, conducted at the1:99 inhibitor-diesel ratio. A control bottle with no inhibitiontreatment, marked in the figure as “Blank,” was also includedto provide a comparison value against which inhibition effec-tiveness was assessed. Inhibition effectiveness measured as per-cent protection was defined from 0.0 to 100, where 100%protection implies 100% inhibition and 0.0% protection im-plies no inhibition. It is clear from Fig. 4 that inhibitor B is not

an effective inhibitor in this environment. While examiningFig. 4 alone would lead to the conclusion that the other eighttested inhibitors provide excellent (72% to 96%) overall pro-tection, looking closely at the “Observations” column in Table2 shows that this conclusion is misleading. Corrosion rate calculations done by means of weight loss methodology, by default, provide only general corrosion rate values. Pitting cor-rosion is not determined by weight loss means. A detailed visualpost-test examination of the coupons confirmed that many ofthe coupons exhibited pits, as described in Table 2. Althoughthe general corrosion protection from these chemicals appearsexcellent, the presence of pits suggests corrosion that would be detrimental in field applications. Figure 5 shows a typicalexample of post-test coupons that do not exhibit pitting, andFig. 6 shows an example of post-test coupons that do exhibitpitting. Examining Fig. 4 and Table 2 led to the conclusion that

Fig. 3. Photograph showing the arrangement used throughout the experiment. Fig. 4. Corrosion rate and inhibition effectiveness for nine inhibitors tested indeionized water, after dip-and-drip procedure in 1:99 inhibitor-diesel solutions,exposed to a simulated sales gas environment for 33 days. Corrosion rate andinhibition effectiveness for deionized water are also included as a blank.

Fig. 5. Photograph showing typical post-test coupons with general corrosion onlyand no pitting.


only two chemicals (F and H), out of the nine inhibitors tested,provide excellent general corrosion protection and do not pro-mote pitting.

As previously mentioned, a second test series was performedto obtain a measure of the film persistency of the chemical inhibitors. This testing was done using the chemicals at theconcentration at which they would be applied to a pipeline inthe field, which is the 1:4 inhibitor-diesel ratio. After dipping

and dripping in the inhibitor mixtures, the coupons were sub-jected to flushing in a stream of deionized water for 30 secondsto simulate film removal. Figure 7 shows the corrosion rateand inhibition effectiveness for the nine tested inhibitors at the1:4 inhibitor-diesel ratio in deionized water exposed to thesimulated sales gas environment for 33 days. Corrosion rateand inhibition effectiveness for untreated steel samples indeionized water are also included as a blank.


Fig. 6. Photograph showing post-test coupon with typical through-thicknesspitting.

Fig. 7. Corrosion rate and inhibtion effectiveness for nine inhibitors tested indeionized water, after dip-and-drip and flush procedure in 1:4 inhibitor-dieselsolutions, exposed to a simulated sales gas environment for 33 days. Corrosionrate and inhibition effectiveness for deionized water are also included as a blank.

Corrosion Inhibitor

Average Corrosion Rate, mpy

Inhibition Effectiveness,% Protection

Observations

Blank 2.25 0.0 General corrosion

A 0.47 78 Pitting attack

B 1.87 17 General corrosion

C 0.58 74 Small deep pits, non-perforating

D 0.1 96 Through-thickness perforations

E 0.12 95 Through-thickness perforations

F 0.37 84 General corrosion

G 0.18 92 Through-thickness perforations

H 0.29 87 General corrosion

I 0.63 72 Small deep pits, non-perforating

Table 2. Inhibitor performance of samples in 1:99 inhibitor-diesel solutions exposed to a simulated sales gas environment for 33 days. Corrosion rate and inhibitioneffectiveness for deionized water are also included as a blank.

Corrosion Inhibitor

Average Corrosion Rate, mpy

Inhibition Effectiveness,% Protection

Observations

Blank 1.42 0.0 General corrosion

A 0.19 87Through-thickness

perforations

B 0.43 70 General corrosion

C 0.43 70 General corrosion

D 0.2 86 General corrosion

E 0.5 65 General corrosion

F 0.22 85 General corrosion

G 0.21 85 General corrosion

H 0.24 83 General corrosion

I 1.15 19 General corrosion

Table 3. Inhibitor performance of samples in 1:4 inhibitor-diesel solutionsexposed to a simulated sales gas environment for 33 days. Corrosion rate andinhibition effectiveness for deionized water are also included as a blank.


It is clear from Fig. 7 that inhibitor I is not effective in thisenvironment because of its poor film persistency. This is inagreement with the results shown in Table 2, where inhibitor Iwas also at the lower end of inhibition effectiveness at the 1:99ratio. Similar to the earlier discussion, examining Fig. 7 alonesuggests that the other seven tested inhibitors show good filmpersistency, as manifested by their inhibition effectiveness inthe range 70% to 87%, but the “Observations” column inTable 3 indicates that this good inhibition effectiveness is mis-leading. A detailed visual post-test examination of the couponsconfirmed that inhibitor A, with the highest inhibition effec-tiveness and therefore best film persistency, exhibited perforat-ing pits. This is consistent with the observation made wheninhibitor A was tested at the 1:99 ratio.

By examining the results obtained from both the 1:99 andthe 1:4 ratio mixtures, it was concluded that inhibitors F andH are expected to provide the best film persistency and inhibi-tion effectiveness for a period of six months.

CONCLUSIONS

1. Batch treatment corrosion inhibitors were found inlaboratory testing to provide a technically feasible means tomitigate the carbon steel corrosion that creates blackpowder.

2. Two batch treatment corrosion inhibitors were found inthe laboratory to be very effective in mitigating the carbonsteel corrosion that creates black powder.

3. Corrosion inhibitors that yield the highest inhibitioneffectiveness, as calculated from weight loss measurements,are not necessarily always the best. Visual inspection of thecorrosion morphology could be important in ruling out apitting attack, which cannot be detected through weightloss measurement alone.

ACKNOWLEDGMENTS


REFERENCES

1. Baldwin, R.M.: “Black Powder in the Gas IndustrySources, Characteristics and Treatment,” Gas MachineryResearch Council Report No. TA97-4, May 1998.

2. Baldwin, R.M.: “Here Are Procedures for HandlingPersistent Black Powder Contamination,” Oil & GasJournal, Vol. 96, No. 43, October 26, 1998, pp. 51-58.

3. Baldwin, R.M.: “Black Powder Control Starts Locally,Works Back to Source,” Pipeline & Gas Industry, April1998, pp. 81-87.

4. Tsochatzidis, N.A. and Maroullis, K.E.: “Methods HelpRemove Black Powder from Gas Pipelines,” Oil & GasJournal, March 12, 2007, pp. 52-58.

5. Arrington, S.: “Pipeline Debris Removal Requires ExtensivePlanning,” Pipeline & Gas Journal, Vol. 233, No. 11,November 1, 2006, pp. 77-87.

6. Godoy, J.M., Carvalho, F., Cordilha, A., Matta, L.E. andGodoy, M.L.: “(210)Pb Content in Natural Gas PipelineResidues (‘Black Powder’) and Its Correlation with theChemical Composition,” Journal of EnvironmentalRadioactivity, Vol. 83, No. 1, 2005, pp. 101-111.

7. Sherik, A.M.: “Black Powder: Study Examines Sources,Makeup in Dry Gas System,” Oil & Gas Journal, Vol.106, No. 30, August 1, 2008, pp. 54-59.

8. Sherik, A.M.: “Black Powder: Management RequiresMultiple Approaches,” Oil & Gas Journal, Vol. 106, No.31, August 18, 2008, pp. 66-70.

9. Sherik, A.M., Zaidi, S.R., Tuzan, E.V. and Perez, J.P.:“Black Powder in Gas Transmission Systems,” paper08415, presented at CORROSION 2008, NACEInternational, New Orleans, Louisiana, March 16-20,2008.

10. Sherik, A.M., Perez, J.P., Abdulhadi, A. and Jutaily, S.: “Composition, Source and Formations Mechanisms of Black Powder in Sales Gas Pipelines,” paper presented at EUROCORR 2007, Freiburg, Germany, September 9-13, 2007.

11. Craig, B.: “Corrosion Product Analysis — A Road Map to Corrosion in Oil and Gas Production,” Materials Performance, August 2002, pp. 56-58.

12. Sridhar, N., Dunn, D.S., Anderko, A.M., Lencka, M.M. and Schutt, H.U.: “Effects of Water and Gas Compositions on the Internal Corrosion of Gas Pipelines Modeling and Experimental Studies,” Corrosion, Vol. 57, No. 3, 2001, pp. 221-235.

13. Lyle, F.F.: “Carbon Dioxide/Hydrogen Sulfide Corrosion Under Wet Low-Flow Gas Pipeline Conditions in the Presence of Bicarbonate, Chloride and Oxygen,” PRCI Final Report PR-15-9313.



Abduljalil H. Al-Rasheed joined SaudiAramco in 1981 and is currently aSenior Lab Technician Specialist withthe Modeling & Prediction Group ofthe Research and Development Center(R&DC) Network Integrity Team. Hehas strong hands-on experience and

knowledge in many electrochemical techniques, and hiscurrent activities focus mainly on designing experimentalsystems and data analysis. Abduljalil conducts experimentalwork on the corrosion simulation process, materialsevaluation and electrochemical impedance spectroscopy.One of his key accomplishments includes building a newLinear Polarization Resistance (LPR) monitoring systemfrom instruments deemed obsolete.

Ali A. Al-Jabran joined Saudi Aramcoin July 1983 and is currently workingin the Materials Performance Unit ofthe Research and Development Center(R&DC) as a Senior Technician.During the past 28 years, he hasspecialized in high-pressure/high

temperature (HP/HT) operations and specifically in flowaccelerated corrosion, electrochemistry and process controlof HP/HT equipment. Ali has accumulated a great amountof knowledge in all aspects of corrosion and materialtesting. He has demonstrated several initiatives throughparticipation in the design of new equipment as well asrenovation of existing ones. In addition, Ali was involvedin developing new competencies in HP/HT testing bycompleting six months of specialized training with CCTechnology, Lafayette, LA.

BIOGRAPHIES

Dr. Abdelmounam M. Sherik joinedSaudi Aramco in 2004 and is currentlyworking for Saudi Aramco’s Researchand Development Center (R&DC) asa Science Specialist with the MaterialsPerformance Group of the TechnicalServices Division. Prior to joining

Saudi Aramco, he worked in Canada for over 15 years inseveral research positions in university, government andindustrial research centers. Abdelmounam has over 23years of professional experience in the areas of materialsand corrosion.

He received his B.S. degree in Materials Science andEngineering from Tripoli University, Tripoli, Libya, and hisM.S. and Ph.D. degrees in Materials and MetallurgicalEngineering from Queen’s University, Kingston, Ontario,Canada.

Abdelmounam has authored or coauthored more than60 journal and international conference publications incorrosion of sales gas pipelines and nano-structuredcoatings. He is an active member of the NationalAssociation of Corrosion Engineers (NACE), where he haschaired and vice chaired several technical symposia.Abdelmounam is a member of the Society of PetroleumEngineers (SPE).

Dr. Arnold L. Lewis joined SaudiAramco in 1988 and is a ResearchScience Consultant with SaudiAramco’s Research and DevelopmentCenter (R&DC). He has 30 years ofprofessional experience in scientificresearch and development.

Arnold’s current research focus is atomic hydrogenpermeation studies in hydrogen sulfide environments. Hisother research interests are corrosion and corrosioninhibition technology, and cathodic protection processes. In 1975 Arnold received a B.A. in Chemistry from PacificLutheran University, Tacoma, WA, and in 1981, he receiveda Ph.D. in Analytical Chemistry from Oregon StateUniversity, Corvallis, OR.

Arnold has authored or coauthored numerouspublications in his areas of expertise and has four U.S.patents with Saudi Aramco.

knowledge in many electrochemical techniques, and his

temperature (HP/HT) operations and specifically in flow

Arnold’s current research focus is atomic hydrogen

Saudi Aramco, he worked in Canada for over 15 years in




ABSTRACT target rock thickness and the total thickness of the formationpenetrated by a vertical well. Some information about the pro-portions of rocks at undrilled locations also may be availablefrom seismic facies1, 2. The main limitation is the vertical reso-lution; as a consequence, thinner beds and heterogeneity due tosmall rock bodies are not visible from seismic. Reconstructionsof the depositional facies environments with sequence stratig-raphy3, 4 may allow for soft information about the probabilitiesof finding certain facies with new wells. Sequence stratigraphyidentifies key bounding surfaces as maximum flooding surfacesand sequence boundaries, typically delineating rock bodies ofpredictable grain size trends in three dimensions. Sedimentsupply, accommodation space and the boundary conditions ofbasin paleo-topography and sea level, however, are highly uncertain, resulting in nonunique and subjective mapping,which is unreliable at higher resolution due to the sparse dataconstraints. Dynamic modeling, based on flow mechanics, considers the sources of sediment supply, depositional constraints,subsidence and tectonics5, e.g., the Sedsim approach, and alsoyields highly nonunique solutions due to uncertainties in theboundary conditions6. In addition, facies bodies cannot be sim-ulated to match the high resolution data of the current wells.These limitations necessarily result in insufficient local precisionfor detailed field development decisions. Direct interpolationof proportions from the wells is unrealistic because the geome-try of rock bodies is usually complex and produces nonlinearrelations between proportions. Consequently, the quantitativeintegration of seismic, sequence stratigraphy and current welldata is necessary to gain information about facies distributionsand rocks expected in the subsurface. The prediction of rockproportions from seismic and sequence stratigraphy depends onrealistic probability distributions of such proportions and thespatial variations inferred from contemporary trend analogs.

Facies trends are nonstationary constraints used to controlthe local, prior probability distribution of facies proportions ingeostatistical indicator simulations7, 8. A rarely recognizedaspect of facies modeling is that a trend constraint often hasthe largest impact on the outcome of indicator facies simulationsand the resultant flow simulations9. In addition, decisions thatdepend on localized risk cannot be made on the basis of a real-ization of the facies’ assemblage; the variable of interest is thelocal proportion or probability of the target facies.

Successful drilling of new wells in carbonate and clastic reser-voirs must maximize the probability of intercepting the targetrocks. Wells are planned on 3D cellular computer modelswhere each cell represents a rock’s 3D element and its petro-physical properties. Geocellular modeling of rock categories isbased on the prior 3D depiction of facies proportions. Theproportions are a measure of probability, and they are uncer-tain at nonsampled locations. Therefore, proportions must bemodeled as random variables p(x) at each location x. Experi-ence shows that proportions do not appear to follow theGaussian, power or lognormal distribution; instead, numericalexperiments on real geological phenomena led to the discoverythat conditional proportions behave as Beta distributed vari-ables. The theoretical implications of Beta distributions are notdiscussed in this article, but one finding is that classical geosta-tistics cannot be directly used on the proportions. Therefore, anovel transform was devised to project the proportion randomvariables to a Gaussian domain. This enables the use of classi-cal spatial statistical methods. The correct conditional meansand variances of the Beta variables are recovered after thetransformation back to proportions through Riemann integra-tion. Obtaining a theoretically correct estimate of the uncer-tainty in the local facies proportions allows risk analysis withhigh confidence for such activities as drilling infill developmentwells. Some complementary examples are presented with dis-cussions. In addition, Beta distributed rock proportions allowgeological modelers to explore the uncertainty in facies trendsfrom mapping or seismic attribute interpretation in a quantita-tively correct way that is straightforward, yet avoids the re-striction of a multivariate Gaussian model.

INTRODUCTION

Successful placement of wells for hydrocarbon reservoir devel-opment must maximize the proportion of target rocks inter-cepted by the wells. The critical problem of well placement isthat carbonate or clastic rock categories are uncertain at undrilledlocations; therefore, the unknown proportions of rocks (i.e.,geological heterogeneity) must be treated as a probability ofrock occurrences. Proportions can be measured at a single well;for example, the vertical proportion is the ratio of permeable

Representative Prediction of GeologicalFacies and Rock-Type ProportionDistributions with Novel Beta FieldCharacterization Authors: Dr. Jose A. Vargas-Guzman and Dr. K. Daniel Khan



Predicting the probability of the occurrence of specific geo-logic facies at undrilled locations is equivalent to predictingconditional proportions from indicators, which are the typicalrandom variables used for representing the occurrence of aspecific category at a given location

for K categories. The mean indicator for each category, takenover some volume of interest (e.g., a wellbore), is a propotion,Eqn. 1:

(1)

This proportion can be interpreted as a probability in the sensethat it describes the frequency of occurrence of elements of agiven size (e.g., well log or core samples) over the volume orthickness of interest. The variance of the facies proportions iswritten as:

(2)

Equations 1 and 2 are summary statistics of the distributionof the facies indicator. The random variable of interest here isthe facies indicator proportion pk at each spatial location xconditional to the surrounding data. At drilled locations, theprobability pk is known, within measurement error, while atundrilled locations, operators must estimate the probabilitydensity function (pdf) of pk to predict the most likely rock dis-tribution in any new planned well. If such a probability distri-bution is fairly represented by the first two moments, thenestimating the mean E(pk) and variance var(pk) is critical forany risk assessment of drilling due to the uncertainty in the geological heterogeneity.

The Beta distribution has been presented in the geostatisticalliterature as a means for modeling the global uncertainty incategorical facies proportions10, 11 and for modeling change-of-support effects in categorical facies proportions12. The objec-tive of this article is to show practical evidence demonstratingthat the distribution of the proportions of facies over a fieldcorresponds to a field of correlated Beta distributed randomvariables. The importance of this finding is that an understand-ing of the probability distribution law governing the spatiallycorrelated proportions of rocks allows construction of morerealistic models for facies proportions. The article also pro-poses a practical methodology to model facies proportionswhile accounting for closure constraints, and it provides asound tool to study proportions in facies analogs and outcrops.

EVIDENCE FOR BETA DISTRIBUTED FACIESPROPORTIONS

Gaussian Projection Experiment

The original insight that conditional proportions are Beta distributed variables was obtained from straightforward

experiments, explained next. It is well-known that indicatorstatistics are defined for any continuous attribute by countingthe frequency of samples below a cutoff value,

For example, the proportion of rock samples having poros-ity less than or equal to a specified cutoff defines the cumula-tive proportion for that indicator class. The collection of allsuch indicator proportions defines the global or unconditionalcumulative probability distribution for the attribute, Fg(z). Aconditional cumulative distribution function (ccdf) of the attribute, say, at a specific location in the field is denoted Fc(z| .).The conditional mean and variance are a function of the sur-rounding information (.). In the simplest case, all of the condi-tional distributions are the same shape as the global distribution. Consider a standard, normally distributed vari-able z. We project the z values corresponding to a ccdf, Fc(z| .),onto the uniform [0,1] cumulative probability axis of the z cdf,Fg(z), Fig. 1. For the unconditional variate z, the result is, ofcourse, the uniform [0,1] distribution; however, for any condi-tional distribution Fc(z| .), it yields the conditional randomvariable of the conditional cumulative proportions,pβ (x)=Fg(z|(x) .). The result is a set of conditional histogramsof the [0,1] valued probability, or the cumulative proportionrandom variable pβ (x), one for each conditional random vari-able projected, Fig. 1. These density functions have nonuni-form shapes ranging systematically from a symmetric functionabout the median skewed distributions towards the extremes.The conditional distributions in Fig. 1 are all a perfect fit withBeta pdfs, which have the following form:

(3)

where r(.) is the gamma function, p is the proportion, (�) and(β ) are shape parameters.

Fig. 1a. Distributions of conditional probability are generated by projection ontothe unconditional uniform [0,1] axis of the standard normal Gaussian CDF.Fig. 1b. Distribution of proportions from eight conditional Gaussian distributionswith mean values (-2.5, - 1.64, -1.27, -0.67, 0, 0.67, 1.27, 1.64) and variance (0.9,0.9, 0.9, 0.9, 0.9, 0.5, 0.5, 0.5), read from top left.



The shape parameters � and β of the Beta distribution arerelated to the mean and variance of proportions by the follow-ing well-known relations:

(4)

The exercise shows evidence that conditional distributionsof proportions, or probability random variables, are not uni-form. This result is not confined to the Gaussian distributionmodel; the same result is observed when the global and condi-tional z-cdfs are lognormal distributed or when they follow the F-distribution. The possibility of conditional proportionsbeing Beta distributed variables needs to be tested with realphysical phenomena. Such an experiment is described next.

Analog Image Analysis Experiment

To test whether the facies proportions in a real complex geo-logical field are Beta distributed, the experiment utilized an im-age of a carbonate tidal flat environment. The satellite image isavailable from NASA’s Earth Observatory website as photo-graph ISS026-E-5121. A small area of the image was selectedfor the experiment, Fig. 2. Sampling local proportion distribu-tions in a realistic geological field can be accomplished in amodel-based setting with images generated through an object-based geostatistical model or a forward process rules-based,pseudo-physical model. Alternatively, to avoid model-basedconstraints on the analysis, simulated annealing can be used togenerate multiple subtly different versions of the reference im-age while retaining the overall character of the original image,as was done here.

The satellite image, Fig. 2, was first classified into three cat-egories based on its red, green and blue spectrum; truncationson the first two principal components of the spectrum weresufficient for this classification. The image classifications plau-sibly correspond to (1) grainy facies, (2) reef facies, and (3)tidal flat facies, Fig. 2. Although the image classification is notperfect, likely having some misclassification errors and lackingin facies discrimination, it suffices for the purposes of the ex-periment. The simulated annealing program SASIM13 was usedto perturb the pixel maps of the principal components, subjectto constraints on the variograms, histograms and smoothedversions of the reference pixel maps. Each pair of realizationsof the principal components’ pixel maps was truncated accord-

ing to the same criteria and assembled into a single realizationof the categorical facies assemblage. A total of 500 indicatormaps were processed. Taking the average indicator for each fa-cies class yielded three facies proportion maps, which served asthe reference proportion maps, Fig. 3. These proportion mapswere then perturbed using SASIM to generate multipleequiprobable realizations of the facies proportions. It is thesefinal facies proportion realizations that we were interested insampling at specific locations to observe the distributions of lo-cal conditional proportions.

The frequency histograms of the local proportions at four

Fig. 2. NASA Earth Observatory photograph ISS026-E-5121, Bahamas, with asmall cutout classified into three facies categories for image analysis.

Fig. 3. Reference facies indicator proportion maps for the (a) grainy and (b) reeffacies, as generated by simulated annealing perturbations of the classified image inFig. 2.

Fig. 4. Annealing results on reference facies proportion map of Fig. 3a providesempirical evidence that local distributions of uncertainty in facies proportions areBeta distributed.



different locations, ranging from low to high valued proportionsfor Facies 1, is shown in Fig. 4. As before, these histograms arefit well by Beta distributions: no other distribution family pro-vides a better fit. These results, taken together with the resultsfrom the analytical experiments, provide convincing empiricalevidence that spatial conditional proportion fields are com-prised of correlated Beta distributed random variables. Figure4 is consistent with the geologists’ intuition, as deposition offacies is affected by distance to the sea, topography and physi-cal and chemical gradients, meaning that facies conform tononstationary geological heterogeneity, which cannot have uniform frequency.

MODELING BETA DISTRIBUTED FACIES PROPORTIONS

Transforming Correlated Beta Proportions

The finding that a Beta random variable comprises the condi-tional facies proportion in the likelihood distribution determinedin analog satellite images is a powerful one for hydrocarbonexploration and for the probability of finding selected rocks inthe subsurface. One can now obtain a robust, possibly non-symmetric, conditional pdf at each unsampled location in thefield. Note that the shape of each pdf depends on the propor-tion mean p̂ and variance var(p̂ ). Therefore, all that is neededis an estimate of the local mean and variance, which can be obtained by kriging. A significant complication, however, isthat the variable shapes of the local Beta distributions entailnonlinear correlations between the proportion random variablesat any two locations14. This means that a stationary covariancemodel, or variogram, cannot account for the spatial correlationunderlying the proportion field. Dealing with such nonlinearand nonstationary correlations is highly impractical at bestand would require sophisticated estimation programs. A prac-tical solution is to find a transformation function that convertsthe Beta random variables to random variables that follow asymmetric distribution function, regardless of the conditionalmoments.

A simple and novel transformation was devised. The logicleading to the proposed transform is based on basic principlesof indicators. In summary, it was found that the logarithm ofthe variance of indicators, , is a squared Gaussian.Note that the variance of indicators is a second order meas-ure. The linearization transformation, �(p), is

(5)

From Eqn. 5, a back transformation is constructed after solv-ing the quadratic relation between the proportion and theGaussian random variable. This is

(6)Note that p is the target Beta distributed proportion randomvariable, and q=(1-p) is the proportion random variable forthe complementary event. Both results are directly obtained

from solving Eqn. 6, and the closure condition q+p=1 is auto-matically granted.

Because this nonlinear transformation cannot be applied toexpected values without introducing a strong bias, the ex-pected values for the moments must be evaluated using Rie-mann’s integral for power random variables15. This yields

(7)

The corrected mean, , and variance, ,are used to compute the Beta parameters, as indicated in Eqn. 4.

The transformation of Eqn. 5 is exactly Gaussian for anysymmetric Beta distribution, (� = β ) , for integer Beta parame-ters. For asymmetric Beta distributions, (� π β ) , the transfor-mation is approximate, but yields results that are very close toGaussian14. The estimated Beta parameters based on the ap-proximate Gaussian transformation are therefore not exact,because Eqn. 7 considers a true Gaussian variable while therandom variable given by the transformation of Eqn. 5 is notexactly Gaussian. In practice, the errors in the estimated Betaparameters are sufficiently small that they can be neglected,since they do not result in a large change in the shape of theBeta distribution.

Estimation and Simulation Workflow

The first step in a practical workflow is to average the faciesindicator well logs by zone for the proportion data, pk(x), ateach well location. In 3D averaging, one can use moving win-dows and transform these pk(x) data to y(x) data via Eqn. 5.One then computes the experimental variogram of the y(x)data and fits a combination of valid nested models13. Option-ally, one can transform any secondary constraints on the localseismic facies and facies maps, or other secondary data, to y-scores to make use of collocated cokriging or kriging with alocally varying mean7, 13.

Simulation of conditional Beta probability fields (P-fields)proceeds via the conventional sequential simulation approach,with the Riemann back transformation of parameters, Eqn. 7,and Gaussian forward transformation of simulated propor-tions, Eqn. 5, as embedded steps.

1. Initialize a path through the nodes. 2. Compute a kriging mean �̂y(x) and variance σ̂ 2

y(x) at an unsampled location.

3. Back transform the estimates, �̂y(x) and σ̂ 2y(x), with the

Riemann integration, Eqn. 7, to obtain the Beta ccdf param-eters � and β , Eqn. 4.

4. Draw a random number, up [0,1], from the uniform pdf andobtain the inverse of the local Beta distribution as a simu-lated realization, p(x), of the random variable pβ (x).

5. Transform the simulated value p(x) to y(x) using Eqn. 5, and return to step 2 to iterate on the estimation of parameters for

the next location. Repeat steps 2-5 until all nodes have been visited.The public domain software SGSIM13 is easily modified to

the variance of indicators, , is a squared Gaussian.



accommodate the proposed algorithm. The inverse of the localBeta ccdf is obtained by implementing the algorithm16. Afterthe proportion data are transformed into the pseudo-Gaussianvariables, nonlinear relations will have vanished, but nonsta-tionary relations may still be present and need proper handlingwith known workflows. The goal of the typical workflow is todecompose the deterministic trend and stochastic residuals asseparate components17.

DISCUSSION OF PRACTICAL EXAMPLES

Risk Quantification in Development Well Drilling

Consider the grainstone facies proportion map of Fig. 4 and acorresponding dataset sampling from the reference map, Fig.5. The proportion data have been transformed via Eqn. 5, andthe sample variogram of the y-scores is fit by an anisotropicmodel. We identified two proposed well locations, Fig. 5, forevaluation. Suppose a minimum thickness criterion for an eco-nomic well requires that no less than 50% of the reservoirthickness be the grainstone facies. A direct kriging and simula-tion approach to the facies proportions should be avoided be-cause of the nonstationary and nonlinear correlations betweenBeta distributed random variables, as pointed out in previoussections. The recommended approach is to simulate with trans-formations a reasonably large number of facies proportion

realizations, since we are estimating the local Beta distributionparameters sequentially; one such realization is shown in Fig.5. The ensemble mean (E-type) and the conditional variancemap for proportions of the target facies provide an estimate ofthe local Beta distributions at each unsampled location, includ-ing our proposed well locations, Fig. 6. Location 1 has a con-ditional mean and facies proportion variance of 0.55 and 0.06,respectively, while location 2 has a conditional mean and faciesproportion variance of 0.60 and 0.08, respectively. While theestimated expected proportion and the uncertainty are not verydifferent between the two locations, it is clear that the distribu-tion shape will affect the risk, as estimated from a given cutoffon the ccdf. The proposed Beta simulation methodology can beexpected to accurately characterize the local uncertainty distri-butions. A traditional Gaussian simulation technique wouldeasily yield incorrect results. This is because the underlyingconditional proportion field comprises a nonlinear Beta P-fieldthat does not respond to a stationary variogram model. In ad-dition, a conventional normal scores transformation and simu-lation under a multivariate Gaussian model would not beequivalent to the proposed approach. The multivariate Gaussianmodel forces the necessary limitations of asymptotic independ-ence of the extremes, or maximum entropy. In comparison, acorrelated field of Beta distributed random variables does notcorrespond to such behavior and appears to be much closer toreality, as inferred from empirical results.

Uncertainty of the Facies Trend Model

Most reservoirs are nonstationary in the local facies proportions.All geostatistical algorithms for facies modeling require thespecification of the nonstationary facies trend models (i.e.,hand drawn facies maps from sequence stratigraphy and/or

Fig. 5. Simulated facies proportions (top), expected value map (center) andconditional variance map (bottom), summarizing the local distributions ofuncertainty in facies proportions based on a sparse sample dataset of the referencefacies map of Fig. 3a. Proposed infill drill locations are shown as boxes 1 and 2.

Fig. 6. Distributions of local facies proportions for proposed infill drill locations 1and 2 of Fig. 5. The probability of encountering less than the minimum faciesthickness criterion of 0.5 of total reservoir thickness is 42% at location 1 and31% at location 2.


seismic). The facies trend model is typically considered a prior,low frequency constraint, yet the trend model tends to dominatethe character of the simulated facies, and it may over-constrainthe variability between realizations, which may unrealisticallyreduce the uncertainty in the geology. Therefore, there is ar-guably strong motivation to introduce a realistic level of uncer-tainty in the facies proportion map or model. In this example,Beta fields enable a more realistic uncertainty evaluation.

Probabilistic inverse calibration techniques for iterative conditioning to nonlinear response variables in this examplemake use of correlated Beta proportion fields. Consider a

reservoir quality indicator variable that has a significant impacton production response, Fig. 7. The proportion map of this facies is simulated as previously described, and the ensembleaverage and conditional variance maps yield the local Betaprobability distributions, Fig. 8. We selected a vector of seed ormaster locations from which to propagate perturbations to thelocal proportions (e.g., as per the method of Capilla, Rodrigoand Gómez-Hernández18). The impact of the propagations is afunction of the shape of the correlated local Beta distributions.Convergence to a set of optimal perturbations to the referencefacies proportion map that minimize the mismatch betweenobservation data and reservoir simulation response yields atrend realization that may be considered the best prior constraintfor a 3D indicator realization of the facies model, Fig. 9. Theproposed novel idea here is to consider a field of correlatedBeta variables as a robust, nonlinear probabilistic model forexploring the geological uncertainty in inversion problems.The same approach is applicable to blind tests or can be usedto cross-validate the goodness of trend facies maps, with newwells compared to multiple facies models with the same priorfacies maps. Errors detected with new wells can be utilized tomodify the stratigraphic interpretation. More generally, thisexample offers evidence that a statistically correct way to handlecorrelated local uncertainties in categorical facies proportions,or continuous P-fields with no simplifications, should be to useBeta distributions of proportions.

Comparison to Gaussian Assumption: Consequence inTerms of Risk and Cutoffs

The standard approach to solving geostatistical estimationproblems of continuous attributes is to consider a rank pre-serving transformation (i.e., anamorphosis) of the data to nor-mal scores, kriging and simulation in Gaussian space, followedby back transformation of the simulated values through theglobal cumulative distribution function (CDF) of the attrib-ute13. Riemann integration in Eqn. 7 shows that a back trans-

Fig. 7. Facies proportion trend map of a key reservoir quality indicator facies (top)and the example indicator simulation constrained by this map (bottom).

Fig. 9. Three realizations of the facies proportion map generated by correlatedfield of probability perturbations from control node locations. These proportionmaps have a dominant impact on the simulated facies model.

Fig. 8a. Estimated facies proportion mean and variance maps with eight locationsselected to propagate perturbations to the facies probability field.Fig. 8b. Distributions of uncertainty at the selected control nodes.Fig. 8c. Impact of probability perturbation of +0.2 units to the mean on the localfacies proportion at control nodes 2 and 3.




formation of the Gaussian moments to obtain the Beta mo-ments is not the same as the transformation of the Gaussian toBeta random variables. As an analogy, lognormal geostatisticsshows that the exponential of the Gaussian mean is not themean of the lognormal. Therefore, the Beta estimation andsimulation approach of conditional proportions is not equiva-lent to a transformation mapped or tabulated through theglobal CDF. In fact, the global CDF has no practical utility innonstationary fields, such as facies proportions. Consider thatthe distributions of Fig. 8b are various local proportion distri-butions from specific locations in a field with a global histogram,Fig. 10. The field is assumed to be quasi-stationary in theGaussian domain, but it is nonstationary in the Beta domain.Assume that the estimated Beta distributions, according to theproposed methodology, are very close to the true Beta distribu-tions, as previously discussed. Now consider Gaussian modeledlocal proportion distributions followed by a back transforma-tion on the global CDF, as per the classical rank transform approach. Note that the conditional means and variances ofthe intermediate y-scores, Eqn. 5, of the Beta simulationmethodology are directly comparable to the Gaussian parametersobtained by classical Gaussian simulation before back trans-formation. After classical back transformation of the normal

scores is performed, the local conditional distributions of theproportions do not correspond to the expected Beta distribu-tions, Fig. 11. The only case where the classical Gaussian approach would yield closely comparable results is where theglobal distribution of proportions is approximately uniform.This will most often not be the case in practice. The consequenceis a potentially severe bias of the predicted risk towards thelow end, or an underestimation of the net reservoir occurrencebased on cutoffs, Fig. 12. This example shows that modelingBeta distributed proportions will enable a more realistic riskanalysis and prediction of local proportions of net reservoir paydefined from facies, rock-type classifications, or fluid saturationand petrophysical property cutoffs. The recommendation is toavoid the standard practice of using transformations from theglobal distribution because facies proportions are nonstationary.In addition, the nonlinear effect on expectations, implicit inRiemann’s integral, is not included in such transformations.

DISCUSSION AND CONCLUSIONS

This article is a unique contribution on the use of the Betaprobability distribution as a law for natural facies proportions.Evidence is presented to show that the conditional probabilitydistributions of facies proportions in a geological field are ac-tually comprised of correlated Beta random variables. This ap-pears as a new discovery in geostatistics and opens up a moregeneral framework for the study of correlated conditionalprobability. A particularly important insight leading to a newdevelopment in correlated Beta processes is that a field of cor-related conditional probability is highly nonlinear and thereforecannot be directly modeled by stationary, second order Gaussianmodels. This addresses a long-standing gap in geostatistics per-taining to the covariance structure of a P-field19-21. Althoughthis work is focused on categorical facies proportions, the con-cept applies to the P-field of continuous attributes as well11.

Facies proportions are defined over a volume within whichthe facies indicators are distributed. To simplify the illustration,the examples here deal with 2D maps, representing the averag-ing of facies indicators over a reservoir horizon. The conceptsand methods presented here, however, apply equally in charac-terizing the variability of facies proportions in 3D. For example,facies proportions inferred from 3D seismic at a coarser reso-lution average the underlying geological vertical heterogeneity,which needs to be restored using the proper variance and shapeof pdfs for proportions.

Most often we are interested in multiple facies, for K=1, ..., Kfacies categories. The expected proportions must sum to unity,which is known as the closure condition. One can estimate thelocal distributions of uncertainty in the facies proportions pair-wise by lumping categories in a hierarchical estimation work-flow. The multivariate modeling with closure conditions isreported separately.

This contribution clarifies the nature of the distribution ofconditional proportions underlying categorical geological faciesattributes. Empirical evidence from annealing perturbations on

Fig. 11. Local conditional probability distributions of proportions modeled with aclassical Gaussian approach and anamorphic back transformed through the globaldistribution. Compare with the actual Beta distributions of Fig. 8b.

Fig. 12. Comparison of Beta-modeled (blue) and (anamorphic-back-transformed)Gaussian-modeled (red) conditional distributions of local facies proportions at thefirst four locations in Fig. 8b and Fig. 11. The Gaussian-modeled and back-transformed probability distributions are systematically biased low andunderestimate the risk of exceeding a cutoff in facies proportion. At location 2,the example shows a difference in risk of 30%.

Fig. 10. Global distribution of facies proportions used to map the transformationto normal scores and back in a classical Gaussian simulation approach.



real images of geology demonstrates that the random variablescharacterizing the uncertainty in local facies proportions appearto be Beta distributed. Analytical evidence on conditional pro-portions or cumulative probability gives exact results. CorrelatedBeta proportion fields are nonlinear, such that the correlationfunctions between different locations cannot be modeled byclassical linear geostatistical methods. In addition, the articleoffers a completely novel workflow for modeling the proposedBeta fields of facies proportions. A novel transformation of theproportions was developed to transform the variance of indica-tors in terms of proportion random variables to approximateGaussian distributions, which respond to a stationary covarianceor variogram model. This allows kriging based estimation ofthe local mean and variance by standard methods, followed byan integral back transformation of the estimated mean and sec-ond order Gaussian variance to yield unbiased estimates of themoments of Beta random variables.

Obtaining a theoretically correct estimate of the uncertaintyin the local facies proportion allows high confidence in riskanalyses for the activities, such as infill drilling of developmentwells, discussed in the article. In addition, it allows geologicalmodelers to explore the uncertainty of facies trends from sequence stratigraphic mapping or seismic attribute interpretationin a quantitatively correct way that is straightforward — allowingthe use of Gaussian kriging, yet without the need for the oftenincorrect simplification of a multivariate Gaussian spatial field.The claim that the local facies distributions are truly Beta distributed is based on empirical evidence. The proposedmethodology for simulating geostatistical fields of Beta randomvariables is practical and highly valuable in light of the improve-ments it makes possible over Gaussian approaches when faciesor rock proportions are the attributes of interest.

ACKNOWLEDGMENTS


The supporting theory of this study was delievered by the authors at the 9th International Geostatics Congress in Oslo,Norway, June 11-15, 2012.

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18. Capilla, J.E., Rodrigo, J. and Gómez-Hernández, J.J.: “Simulation of non-Gaussian Transmissivity Fields Honoring Piezometric Data and Integrating Soft and Secondary Information,” Mathematical Geology, Vol. 31, No. 7, 1999, pp. 907-927.

19. Srivastava, R.M.: “Reservoir Characterization with Probability Field Simulation,” SPE paper 24753, presented at the SPE Annual Technical Conference and Exhibition, Washington, D.C., October 4-7, 1992.

20. Froidevaux, R.: “Probability Field Simulation,” pp. 73-84,in Geostatistics Troia, ed. A. Soares, New York: Kluwer Academic, 1993.

21. Srivastava, R.M. and Froidevaux, R.: “Probability Field Simulation: A Retrospective,” pp. 55-64, in Geostatistics Banff 2004, Vol. 1, ed. O.L. Leuangthong and C.V. Deutsch, Banff, Canada: Springer, 2004.

in advanced geostatistics at the University of Queensland,Australia. In the 1980s, he served as a Chief Geologist forSociété Générale de Surveillance (SGS).

Jose Antonio’s current interest is in higher-orderpetroleum systems. He proposes the inverse reconstructionof complex geological processes and the evaluation ofnatural resources with estimation and stochastic simulationwith higher-order cumulants. Jose Antonio’s mostoutstanding inventions are 3D geological modelingalgorithms, such as sequential kriging, stochastic simulationby successive residuals, conditional decompositions,transitive modeling of facies, spatial upscaling of thelognormal distribution, downscaling methods for seismicdata with derivatives of the variogram, scale effect ofprincipal component analysis, power random fields, andcumulants for higher-order spatial statistics of complexrock systems and heavy tailed distributions of permeabilityfields.

Dr. K. Daniel Khan is a Geologist andNumerical Modeler working with theReservoir Characterization Departmentin Saudi Aramco. He applies hisexpertise in heterogeneity modeling forpetroleum reservoir characterizationusing geostatistical and inverse data

calibration techniques on various assets within theKingdom. Daniel has been with Saudi Aramco since June2010. Prior to this, he worked for the Energy TechnologyCompany of Chevron Corporation in Houston, TX.

In 2001, he received his B.S. degree in Geology from theUniversity of Alberta, Edmonton, Alberta, Canada. In2006, Daniel received his Ph.D. degree in Hydrogeology,also from the University of Alberta.

He is active in publishing original research and hascoauthored an instructional book on geostatistics.

BIOGRAPHIES

Dr. Jose Antonio Vargas-Guzmánjoined Saudi Aramco in 2002 andworks as a Senior Consultant with the Reservoir CharacterizationDepartment, Geological ModelingDivision. During his career, he hasbeen involved in mathematical

applications to 3D geological modeling and evaluation, andhe is the senior author of many journal papers, bookreviews and book chapters; he has received numerousliterature citations. The International Association forMathematical Geology (IAMG) conferred on him the BestPaper Award from the Mathematical Geology journal forhis peer-reviewed paper on successive estimation of spatialconditional distributions in 2003. The IAMG alsobestowed on him the Best Reviewer Award from theJournal of Mathematical Geosciences in 2007.

Jose Antonio is a former Fulbright and DAAD Scholar.In 1998, he received his Ph.D. degree from the Universityof Arizona, Tucson, AZ, where he has also served as aresearch associate, instructor and full-time faculty member.He was granted a graduate scholarship and a post-doctoralfellowship with funding provided by the U.S. NuclearRegulatory Commission (NRC) and the Department ofEnergy (DOE), respectively. Also, he was a research fellow

calibration techniques on various assets within the

applications to 3D geological modeling and evaluation, and


ABSTRACT

ment). For gas turbine blades used in an engine, the centrifugalstress during the operation can also add to the original residualstress and change the status of the residual stress. The effectsof residual stress may be beneficial or detrimental, dependingon the magnitude, sign and distribution of the stress with re-spect to the load-induced stresses. Tensile residual stress mayreduce the performance or cause the failure of manufacturedproducts. It may also increase the rate of damage by fatigue,creep or environmental degradation. Tensile residual stress canalso reduce the load capacity by contributing to the product’sfailure by brittle fracture or cause other forms of damage, suchas shape change4.

XRD residual stress measurement was performed on thesample from a prematurely failed gas turbine blade, Fig. 1, ofan aero-derivative engine used as a driver for a super pump.The examined blade was removed with the rest of the set aftera few hundred hours of operation. The reason for removal wasdamage to the leading edges of the blade, which resulted whenimpurities in the fuel were converted into solids and depositedin the fuel nozzle or carried away later with the airflow. Thepurpose of the XRD stress analysis was to examine the stressstatus in the failed blade and help engineers to improve operationprocedures and make a proper replacement. To calculate theresidual stress of the blade sample, phase identification infor-mation and elemental composition data were needed. Therefore,XRD phase identification and X-ray fluorescence (XRF) elemental composition determination were included in our analytical procedure.

XRF ELEMENTAL COMPOSITION DETERMINATION

Nickel (Ni)-based superalloys are widely used in gas turbineblades since they maintain a high resistance to corrosion, fatigue, shock, creep and erosion at elevated temperatures. In

X-ray diffraction (XRD) phase identification and residualstress analysis were performed on a sample from a prematurelyfailed gas turbine blade. XRD results show that the undesir-able brittle phase of cobalt molybdenum (Co3Mo) was presentin the failed blade sample. Co3Mo is a topologically close-packed (TCP) phase usually formed during heat treatment atthe manufacturer. TCP phases can damage tie-up γ and γ’strengthening elements and reduce creep strength. They can actas crack initiators because of their brittle nature. The residualstress analysis indicates that the longitudinal direction has atensile stress (206.4 ± 45.4 MPa), whereas the transversal direction has a compressive stress (-203.1 ± 28.4 MPa). Basedon the operating conditions, it is possible that the tensile stresswas formed and the creep extension occurred due to the centrifugal force as a result of operation in a high temperature environment. A crack potential was found perpendicular to thelongitudinal direction of the blades due to the tensile stress.Based on the stress analysis, it is suggested that the turbine’srotational speed and the combustor’s exit temperature should be reviewed at the design stage, and that the blade’s heat treat-ment process to protect the blades from failure should be reviewed as well; an alternative is to replace the current direct-ionally solidified blades with single crystal blades for better performance.

INTRODUCTION

X-ray diffraction (XRD) residual stress measurement is con-sidered a useful tool for material failure analysis. Residualstresses have been identified as an important factor contribut-ing to some failures, particularly in cases of high performancecoating or materials that are exposed to an extreme environ-ment1, 2. The original residual stress in a component is locked-in thermal stress, which primarily comes from solution heattreatment cycles. Although it is important to cool componentsrapidly from a solution heat treatment cycle, the variation incooling rate from the surface to the center results in large ther-mal stress, often large enough to cause plastic strains and sub-sequent residual stress3. The original residual stress of acomponent can be modified by surface treatments, such as ma-chining, grinding, shot peening or stress relaxation (heat treat-


X-ray Diffraction Technique Application in Evaluating the Damage of a Gas Turbine Blade Authors: Dr. Shouwen Shen, Dr. Alaaeldin H. Mustafa, Dr. Gasan Alabedi, Dr. Syed R. Zaidi, Dr. Husin Sitepu and Dr. Ihsan M. Taie

Fig. 1. Illustration of a gas turbine and XRD sampling of a damaged blade.


general, Ni-based alloys contain about 10 wt% to 20 wt% ofchromium (Cr), up to 8 wt% of aluminum (Al) and titanium(Ti), and 5 wt% to 15 wt% of cobalt (Co) and iron (Fe)5.They may also contain minute controlled quantities of otherrefractory elements, such as tungsten (W), tantalum (Ta),molybdenum (Mo), hafnium (Hf) and niobium (Nb), addedto enhance their strength and oxidation properties6. To exam-ine the chemical composition of the failed blade, a wave-length dispersive X-ray fluorescence (WDXRF) spectrometryanalysis was performed. As the blade sample couldn’t beground into powder, it was measured directly in the instru-ment (PANalytical’s Axios Advanced WDXRF) using theloose powder method in a helium environment. Semi-quanti-tative WDXRF results, Table 1, of two samples, Fig. 1, fromthe failed blade indicate that the blade was made of a Ni-based superalloy with significant content of W, Cr, Co andplatinum (Pt) (Sample #1), whereas the surface was coatedwith a PtAl type diffusion coating (Sample #2).

XRD PHASE IDENTIFICATION

For phase identification, a PANalytical XPERT PRO X-ray dif-fractometer with Cu Kα radiation (λ = 1.5418Å) was used. A0.27° parallel plate collimator and a proportional detectorwere employed at the diffraction beam side in conjunctionwith a 8 mm polycapillary lens at the incident beam side set-ting with a 2 mm wide mask and a 2 mm high divergence slit.The XRD instrument was set at 45 kV and 40 mA and runfrom 10° to 160° 2 θ using a step size of 0.02° and a counttime of 1 second per step. The blade sample was directlymounted at an open Eulerian cradle with a manual Z transla-tion stage. XRD results, Fig. 2 and Table 2, show that the ma-jor phases are β phase (NiAl) and β’ phase (Ni3Al) with minorphases of carbides, Co3Mo and CrPt, in which CrPt is proba-

bly from the PtAl type diffusion coating, whose actual formulawill be Pt (Al, Cr). It is necessary to point out that Co3Mo is atopologically close-packed (TCP) phase. The TCP phase is theusual undesirable brittle phase formed during heat treatment.Usually, all TCP types have a plate structure, which has negativeeffects on mechanical properties, such as ductility and creep-rupture. TCP phases can damage tie-up β and β’ strengtheningelements and reduce creep strength. They can act as crack initiators because of their brittle nature.

XRD RESIDUAL STRESS ANALYSIS

When a monochromatic X-ray beam interacts with a crystallinematerial, incident photons are subject to diffraction at theplanes of the atoms and produce a strongly diffracted beamthat leaves the crystal in defined and predicted directions,given by the well-known Bragg’s Law, 2d Sin θ = λ where λ isthe wavelength of the incident beam, d is the interspacing be-tween the planes in the atomic lattice, and θ is the angle betweenthe incident ray and the scattering planes. Changing in inter-spacing, d, can be used with the Bragg’s equation to detectelastic strain7 through knowledge of the incident wavelength(λ ) and the change in Bragg’s scattering angle θ . The most pop-ular technique for measurement of residual stress is the sin2ψmethod8. According to the sin2ψ method, the residual stress inthe sample is related to the slope of the plot of strain ε = Δ d/d0

vs. sin2ψ using the equatio ε = where E is Young’smodulus, ν is the Poisson’s ratio, and σ is the stress coefficient.In our study, the XRD instrument conditions were set at thesame conditions as the phase identification except that thecount time was changed to 20 seconds per step. The d spacingmeasurements were conducted on the high 2 θ peak (115.4°)of the NiAl (310) plane of the blade sample at different tilting(ψ changes at 0°, 21.41°, 31.08°, 39.22°, 46.90°, 54.72°,63.42° and 75°, respectively). The d spacing against sin2ψ wasplotted for the measurements of two directions, respectively.The calculation of the residual stress was automatically per-formed by the PANalytical X’Pert Stress software using theslopes “m” and the equation σ = .

The values of Young’s modulus (E = 199.5 GPa) and Pois-son’s ratio (ν = 0.312) for nickel were used for the calculation.The results indicate that the transversal direction has a compres-sive residual stress (-203.1 ± 28.4 MPa), whereas the longitudi-nal direction has a tensile residual stress (206.4 ± 45.4 MPa),Figs. 3 and 4. As both tensile stress and compressive stress are of


ELEMENTS Ni W Cr Pt Co Al Ti Ta Hf Th

Sample #1Polished Blade 43.0 13.6 9.4 7.7 7.2 4.0 2.8 2.2 2.0 0.9

Sample #2Blade with Coating 22.8 3.7 2.9 54.0 2.9 10.5 0.6 0.6 - -

Table 1. Semi-quantitative results of the elemental composition analysis of the blade from WDXRF**Note: Carbon content cannot be detected by our WDXRF.

Fig. 2. XRD diffractogram of the blade with identified phase patterns.

= where is the Poisson’s ratio, and is the stress coefficient.

= .



the same magnitude, it is believed that the creep extension occurred along the longitudinal direction and shrinkage presentin the transversal direction of the failed blade. A micro-fracturein the failed directionally solidified blade was found in the opticalmicroscopic photo, Fig. 5, which confirmed our assumption.Based on the operating conditions, it is possible that the tensile

stress was formed by the centrifugal force as a result of operationin a high temperature environment.

CONCLUSIONS

Based on stress analysis and phase identification, it can be con-cluded that the creep extension occurred along the longitudinaldirection and shrinkage present in the transversal direction of

Phase Identifi ed Interpretation

Nickel Aluminum(NiAl)

NiAl is a gamma (Y) phase (face-centered-cubic structure) in the alloy, in which the lattice sites are totally equivalent and the atoms constituting the solid solution are distributed randomly. Co, Fe, Cr, Mo and W can replace Ni and Al as a solid solution. The actual formula of Y phase in the failed blade will be Ni (W, Cr, Co, Al).

Aluminum Hafnium Nickel(Al3HfNi12 or Ni3Al0.75Hf0.25)

Ni3Al is a gamma prime (Y’) phase (face-centered-cubic structure) in the alloy, in which Ni atoms are at the face-centers and the Al or other atoms (Ti, Cr, Hf, Nb or Ta) are at the cube corners. The actual formula of Y’ phase in the failed blade will be Ni3 (Al, Ti, Cr, Hf, Ta).

Tantalum Titanium Tungsten Carbide(C5TaTi3W or Ti0.6Ta0.2W0.2C) Both are carbide phases in the form of MC with face-centered-cubic

crystal structure. The carbides usually precipitate at grain boundaries and reduce the tendency for grain boundary sliding.Hafnium Carbide

(CHf or HfC)

Cobalt Molybdenum(Co3Mo)

Co3Mo is a TCP phase, the usual undesirable brittle phase formed during heat treatment. The structure of this phase consists of close-packed atoms in layers with relatively large interatomic distances one below the other. The characteristic topology is generated when the layers sandwich larger atoms. Usually, all TCP types have a plate structure, which has negative effects on mechanical properties, such as ductility and creep-rupture. TCP phases can damage tie-up Y and Y’ strengthening elements and reduce creep strength. They can act as crack initiators because of their brittle nature.

Chromium Platinum(CrPt)

CrPt is probably from the PtAl type diffusion coating. The actual formula will be Pt (Al, Cr).

Table 2. XRD results of phase identification of the blade

Fig. 3. Results of the residual stress analysis in the transversal direction of thefailed blade showing compressive stress (negative).

Fig. 4. Results of the residual stress analysis in the longitudinal direction of thefailed blade showing tensile stress (positive).



the failed blade. There is a crack potential perpendicular to thelongitudinal direction of the blades due to the tensile residualstress. The undesirable brittle TCP phase was found in theblade, which can act as a crack initiator because of its brittlenature. It is suggested that the rotational speed and the com-bustor’s exit temperature should be reviewed at the designstage, and that the blade’s heat treatment process to protect theblades from failure be reviewed as well; an alternative is to replace the current directionally solidified blades with singlecrystal blades for better performance.

ACKNOWLEDGMENTS

The authors would like to thank Saudi Aramco managementfor their permission to present and publish this article. Specialthanks go to Abdulelah Al-Naser and Yazeed Al-Dukhayyil fortheir encouragement and support in many ways. The authorswould also like to thank X-ray Group members for their helpin the experiments.

REFERENCES

1. Mustafa, A.H., Badairy, H.H. and Mehta, S.: “Gas TurbineAero-Engine First Stage Turbine Blade FailureInvestigation,” Journal of Engineering for Gas Turbine andPower, Vol. 131, 2009, pp. 1-4.

2. Ezugwu, E.O., Wang, Z.M. and Machado, A.R.: “TheMachinability of Nickel-Based Alloys: A Review,” Journalof Materials Processing Technology, Vol. 86, Nos. 1-3,February 15, 1999, pp. 1-16.

3. Wallis, R.A. and Craighead, I.W.: “Research Summary:Predicting Residual Stresses in Gas Turbine Components,”JOM, Vol. 47, No. 10, October 1995, pp. 69-71.

4. Sridhar, B.R., Ramachandra, S. and Chandrasekar, U.:“Residual Stress in Nickel Base Superalloy UDMET 720for Different Surface Conditions,” International Journal ofEngineering Science and Technology, Vol. 3, No. 1,January 2011, pp. 36-43.

5. Choudhury, I.A. and El-Baradie, M.A.: “Machinability ofNickel Base Superalloys: A General Review,” Journal ofMaterials Processing Technology, Vol. 77, No. 1, May 1,1998, pp. 278-284.

6. Ezugwu, E.O., Bonney, J. and Yamane, Y.: “An Overviewof the Machinability of Aero Engine Alloys,” Journal ofMaterials Processing Technology, Vol. 134, No. 2, March10, 2003, pp. 233-253.

7. Esquiel, A.L. and Evans, K.R.: “X-ray Diffraction Study ofResidual Macro Stresses in Shot Peened and Fatigued 4130Steel,” Experimental Mechanics, November 1968, pp. 496-503.

8. Hilley, M.E., ed.: “Residual Stress Measurement by X-rayDiffraction,” Society of Automotive Engineers (SAE)Technical Paper J784a, 1971, pp. 21-24.

Fig. 5. Microscopic photo of the directionally solidified blade showing a micro-fracture.


Dr. Gasan Alabedi previously workedfor many years as a Research Fellowand Lecturer at Manchester School ofMaterials in the field of AdvancedCeramics, Thermal Spray Coatings andClay-Polymer Nano-composites. Hismain research interests were focused

on the utilization of advanced materials andnanotechnology in the oil and gas industry. Currently,Gasan is acting sub-team leader for ReliabilityEnhancement Technology within the Network IntegrityTeam at the Research and Development Center (R&DC).

He received his B.Eng. degree in Mining and GeologicalEngineering from the University of Tuzla, Tuzla, Bosniaand Herzegovina, and his M.Eng. degree from BelgradeUniversity, Belgrade, Serbia. Gasan then proceeded toreceive M.S. and Ph.D. degrees in Materials Science fromthe University of Manchester Institute of Science andTechnology (UMIST) and the University of Manchester,Manchester, U.K., respectively.

Dr. Syed R. Zaidi has been with SaudiAramco since 1992. His specializedarea of research is the mineralogicalcharacterization of geological samples(clay and bulk rock) by using the XRDtechnique. Syed is also responsible forXRD method development and

research work. He is familiar with other analyticaltechniques, such as XRF, SEM, FTIR, TGA, DSC and ICP.

Syed received his B.S. degree (with honors) and M.S.degree, both in Chemistry, from Aligarh Muslim University,Aligarh, India, in 1977 and 1980, respectively. In 1986, hereceived his Ph.D. degree in Inorganic Chemistry fromAligarh Muslim University, Aligarh, India.

Syed has published more than 20 papers in peer-reviewed journals. He is a member of the AmericanChemical Society (ACS) and the Society of PetroleumEngineers (SPE).

BIOGRAPHIES

Dr. Shouwen Shen is a ScienceSpecialist and X-ray Group Leader atthe Materials Performance Unit of theResearch & Development Center(R&DC). He has more than 25 yearsof experience in the petroleumindustry and academe. Before joining

Saudi Aramco in 2006, he worked at Southwest PetroleumUniversity in China as an Associate Professor, at theUniversity of Miami as a Visiting Scientist and at CoreLaboratories Canada Ltd. as an X-ray Specialist.

He has studied the seismic facies, sedimentary facies andsequence stratigraphy of Jurassic formations in the Turpan-Hami basin of China. Shouwen used piezoelectrictransducers to measure the sonic velocity of variousdolomites from the Madison formation of Wyoming andMontana, and developed an empirical formula to predictthe sonic velocity of dolomite according to thin sectiondescription. He also developed new XRD methods in-housefor quantitative mineral analysis of sandstone andsuccessfully solved the problem caused by the Rietveldmethod limitation. Shouwen’s specialties include sequencestratigraphy, clastics diagenesis, clay mineralogy andformation damage assessment, thin section description,XRF elemental analysis, XRD phase identification andquantification, crystallite size determination, and textureand residual stress analyses.

Shouwen received a B.S. degree from the ChinaUniversity of Geosciences, Wuhan, China, in 1982 and aPh.D. degree in Petroleum Geology from ChengduUniversity of Technology, Sichuan, China, in 1998.

Dr. Alaaeldin H. Mustafa joined SaudiAramco in December 2000 fromRolls-Royce Civil Aero-Engines,Derby, U.K., where he worked invarious positions during his period ofemployment, covering design, testing,overhaul and troubleshooting.

Alaaeldin works as a Specialist Gas Turbine MaintenanceEngineer in the Mechanical Shops Services Department.Presently, he is assigned to the Research and DevelopmentCenter (R&DC) for a period of 3 months to investigate theintegrity of hot gas path components in gas turbineengines.

Alaaeldin received his B.Eng. degree in MechanicalEngineering from Brighton University, Brighton, U.K., hisM.S. degree in Thermal Power from Cranfield University,Cranfield, U.K., and his Ph.D. degree in MechanicalEngineering from Dublin City University, Dublin, Ireland.

on the utilization of advanced materials and

Alaaeldin works as a Specialist Gas Turbine Maintenance

research work. He is familiar with other analytical

Saudi Aramco in 2006, he worked at Southwest Petroleum



Dr. Husin Sitepu joined SaudiAramco’s Research and DevelopmentCenter (R&DC), Technical ServicesDivision, in 2008. Since then, he hascontributed to several research projectsby providing crystallographicinformation on developed materials,

including black powder, nano-materials and catalysts.Before joining Saudi Aramco, Husin worked at the well-established national and international laboratories at theNational Institute of Standards and Technology (NIST)Center for Neutron Research in Gaithersburg, MD; atVirginia Tech University in Blacksburg, VA; at Ruhr-Universität Bochum in Bochum, Germany; at the InstitutLaue-Langevin (ILL) Neutrons for Science program inGrenoble, France; at the University of British Columbia inVancouver, Canada; and at the Curtin University ofTechnology in Perth, Australia.

He has authored and coauthored 35 papers in severalpeer-reviewed journals, including the International Unionof Crystallography’s Journal of Applied Crystallography,with the Herfindahl index of 5. Husin has a very strongbackground in physics at a research level, and he is aworld-class expert in crystallography and diffractionscience through his extensive use of powder X-ray,synchrotron and neutron diffraction for studying materials.

He received his Postgraduate Diploma, M.S. and Ph.D.degrees in Physics from the Curtin University ofTechnology, Perth, Western Australia, in 1989, 1991 and1998, respectively.

Husin is a member of the International Center forDiffraction Data (ICDD), the International Union ofCrystallography (IUCr) and the Neutron Scattering Societyof America (NSSA).

Dr. Ihsan M. Taie joined SaudiAramco’s Research and DevelopmentCenter (R&DC) in 2001. Currently, he is the team leader of the NetworkIntegrity R&D Team. Prior to this,Ihsan worked as a Research Scientist at the Canadian Ministry of Natural

Resources. He received his Ph.D. degree in High Temperature

Materials and Corrosion from Manchester University,Manchester, U.K., in 1992.

including black powder, nano-materials and catalysts. Resources.



ABSTRACT distribution, sand slurry and pack retention tests, and a filtercake flow back test. The deployed stand-alone screen comple-tions are vertical to highly deviated wells, with screen intervalsranging from 100 ft to more than 1,000 ft in length across thepay zone. These completions are mostly 4½” monobores thatare completed with a 7” permanent packer, 4½” carbon steeltubing and 4½” stand-alone screens. Figure 1 shows a com-mon wellbore schematic in the subject field.

Deployment of Screen Completions

After drilling the 5 ” open hole section to total depth (TD),the following basic completion steps to deploy the screen are:1. Make a final reaming trip in the open hole with a rotating

scraper.2. Displace the hole with conditioned mud.3. Spot clean brine from TD to the 7” liner top.

Wells in gas field MN, south of the giant Ghawar field, arecompleted with stand-alone screens across a pre-Khuff sand-stone formation as a sand control measure. Although prolificproducers, some suffered a severe decline in performance aftera period of production, triggering needed diagnostic work.Consequently, screen plugging was confirmed and collectedsamples of present fill were analyzed. Results called for acoiled tubing (CT) clean out campaign to restore lost produc-tivity. The objective of this article is to detail the whole operationof the fill clean out jobs, which includes the fill diagnostic process,assessment of clean out methods, initial job design, choice offluids, CT bottom-hole assembly (BHA) tools, execution andfield experience, and post-clean out performance evaluation.

The CT wiper trip method used here has been implementedin previous clean outs with either milling or jetting tools. Anewly developed, rate-activated circulation valve can be de-ployed to aid in lifting solids at high pumping rates as well asin jetting acid across the screen interval after fill removal. Thefill clean out campaign was very successful in restoring wellproductivity, as compared to pre-clean out and initial post-drilling well performance. A total incremental gas rate of 340million standard cubit feet per day (MMscfd) has been re-stored to date from 16 clean out operations. Unprecedented,interesting and valuable findings are shared in this article re-garding the nature of the fill formed inside and/or above thestand-alone screens, recommended milling practices to protectthe CT BHA and minimize CT fatigue, the experience of incor-porating acid jetting and squeeze in the CT wiper trip methodto stimulate the damaged formation pack behind the screens,and the preventive measures taken to cope with the fill accu-mulation issue.

INTRODUCTION

Stand-alone screens have been identified as the optimal com-pletion strategy in gas field MN, which produces from a highlyunconsolidated pre-Khuff sandstone formation in Saudi Arabia.Based on initial pilot testing of several cored samples from thefield, stand-alone screens made of 300 micron premium meshand 13% chromium were implemented. Performed standardtests for screen selection included sieve analysis of particle size


Coiled Tubing Fill Clean Out and NearWellbore Acidizing of Plugged Stand-AloneScreens: Highly Successful Campaign inSaudi Arabian Gas Wells Authors: Murtadha J. Al-Tammar, Khalid S. Al-Asiri, Saad M. Al-Driweesh, Mohammed A. Asiri and Nahr M. Abulhamayel

Fig. 1. Common well completion configuration in gas field MN.


4. Run in hole (RIH) with the 4½” screen assembly, and set the liner hanger and liner top packer.

5. RIH with a permanent packer system, a polished bore receptacle (PBR) and a ceramic disk in the tail pipe, and set the packer.

6. Make a wellbore clean out assembly trip to reach a tail pipedown to 3 ft to 5 ft above the ceramic disk.

7. RIH with a seal assembly on the 4½” completion tubing string:a. Sting into the PBR and locate the neutral position.b. Determine the space out requirements.c. Pull the seals out of the PBR.

8. Perform tubing clean out and pickling.9. Circulate clean inhibited diesel into the tubing casing

annulus (TCA), leaving clean diesel in the tubing.10. Sting back into the PBR and land the tubing hanger.11. Pressure test the TCA to 6,000 psig.12. Nipple up and test the production tree.13. Make a drift run using a 3½” gauge cutter on a slick line

down to 3 ft to 5 ft above the ceramic disk or as deep as possible in highly deviated wells.

The ceramic disk, run as part of the tail pipe assemblyabove the screens, is used to isolate the reservoir interval andprotect the screens during well completion deployment prior toflowing back the well.

Initial Well Flow Back

Prior to production startup to feed the gas plant, a well isflowed back through a sand management system to clean upthe completion fluids and fine solids left in the hole that mightlead to plugging of flow lines and vessels with solids. In addi-tion, well flow back is necessary to “cure” the stand-alonescreen completion, which means creating a formation packaround the screens that is mechanically stable. The integrity ofthe screens is also confirmed upon performing this initial flowback. While the rig is on location, the practice is to break theset ceramic disk and flow back the well at low rates for a shortperiod of time: typically, this flow back period is 12 hours af-ter gas reaches the surface. Afterwards, a rigless completionsite is moved to the location to perform a complete flow backuntil the target solids-free gas rate is achieved and specifiedcleanup criteria are met. Cleanup criteria include the following:1. Solids content of less than 0.2 lb/MMscfd on a decreasing

trend.2. Water cut of less than 10% on a decreasing trend.3. Chlorides content of less than 130 ppm on a decreasing

trend.

Declining Well Performance

After being on production for less than a year, many wells suf-fered a severe decline in productivity, exhibiting a significantdrop in gas rate as well as flowing wellhead pressure (FWHP).Consequently, screen integrity was questioned, and potential

fill that might be plugging the screens was suspected. An exam-ple of one such well’s decline is illustrated in Fig. 2. It can beobserved from the plot that the estimated gas rate in Well-Adropped drastically below 5 MMscfd and the FWHP fell be-low 4,000 psig after seven months of production.

DIAGNOSTIC WORK

Once well performance decline is realized, as in this case, diag-nostic work using a slick line should be performed by runningdifferent sizes of gauge cutters to the TD of the well, or to themaximum possible depth in highly deviated wells, to verifywellbore accessibility. In most cases, the gauge cutter tags wellabove the bottom of the screens, confirming the presence of asignificant amount of fill inside and/or above the screens. Thensand bailers are run on the slick line to collect solid samples ofthe encountered fill, Fig. 3. The collected solids are sent to alaboratory for compositional analysis and dissolution tests tobe performed. Figure 4 presents an example of the results obtained in this case. The results of the compositional X-rayanalysis performed on the solid samples collected from variousimpacted wells indicate an average of 75% calcite, CaCO3, inaddition to small proportions of dolomite, quartz, iron oxideand barite. The results of the dissolution tests show the highreactivity of the fill samples with acid; however, only partialdissolution could be achieved with acid due to the presence ofinsoluble components.

FILL CLEAN OUT JOB DESIGN

To restore lost productivity, a fill clean out campaign was inau-gurated after evaluating various potential clean out techniques.


Fig. 2. Productivity decline in Well-A.

Fig. 3. Pictures of fill samples collected using a sand bailer in Well-B.



Fill removal using acid bullheading is time consuming and pre-sented several concerns, as the deposited fill was not entirelysoluble in acid. Therefore, this option did not guarantee a suf-ficient hole cleaning. Therefore, coiled tubing (CT) was utilizedto mechanically clean out the fill deposited inside the screens.A CT wiper trip method with forward circulation was selected.In this method, fluids are pumped down the CT string andsolids are circulated up the CT production tubing annuluswhile performing frequent sweeping, or “wiper tripping,” asthe fill is penetrated.

Fluid Selection

The base fluid chosen for the clean out jobs was filtered 5%potassium chloride (KCl) brine, because of its compatibilitywith the pre-Khuff sandstone formation, serving as a clay sta-bilizer to prevent formation damage caused by fines migrationand clay swelling. Moreover, because reservoir pressure in theimpacted wells was relatively high, around 7,000 psig to 8,500psig, the brine had adequate hydrostatic pressure, enough tolower the surface treating pressure while performing the joband to minimize the CT snubbing force while lowering the CTstring inside the well. The brine also has good carrying capacity,enough to circulate out the solids while cleaning the fill. Forimproved solids lifting, alternating slugs of viscous gels, e.g.,30 lb/Mgal gel, with the brine was considered.

A 10% acetic acid was also selected for use as a contingencyif the encountered fill could not be cleared. The acetic acid wasutilized after fill clean out as well, to wash out the screens andstimulate the formation pack behind the screens in the nearwellbore region by breaching the calcite-based fill deposits. Although a weaker organic acid than hydrochloric (HCl) acid,acetic acid was more compatible with the formation at the prevailing high reservoir temperature of around 300 °F. The reaction of HCl acid with formation clay at high temperaturescauses damage through precipitation as a result of primary,secondary and tertiary reactions. The 10% concentration ofacetic acid was selected because it was below the critical value

of 12%, above which damaging byproducts can precipitate. Asurfactant was added in all used fluids to aid in liquid recoveryand the regaining of relative gas permeability after the treat-ment.

CT Bottom-hole Assembly (BHA)

Either 2” or 2⅜” CT strings can be used for clean out jobswith the following BHA components, from top to bottom, Fig. 5:1. Motorhead assembly that includes:

a. Double-flapper check valves.b. Ball-activated disconnect sub.c. Ball-activated circulation sub.

2. Fixed centralizer.3. Either a motor and mill or a jetting tool:

a. 2⅞” positive displacement, high torque, downhole motor with 3½” step, tapered or flat bottom junk mill.

b. Jetting tool.

Procedure

Fill clean out jobs should follow this basic outline:1. RIH with a gauge cutter on a slick line to tag the fill and

confirm the top of fill accumulation prior to the job.2. Load the well with filtered 5% KCl brine.3. RIH with CT at 60 ft per minute (fpm) with the well shut-

in, while performing pull tests and breaking circulation every 1,000 ft by pumping 2 bbl of brine.

4. Reduce CT speed 100 ft above the slick line tag to 15 fpm, and perform a dry tag with pumps shutoff.

5. Pick up the CT 50 ft, open the well and establish circulation.6. RIH to the fill top, penetrate 50 ft of the fill while pumping

brine, perform a 50 ft wiper trip while pumping gel, and RIH again to penetrate the next 50 ft bit with brine; an example of a fill clean out schedule is shown in Table 1.

7. If no progress is achieved at penetrating the fill, spot a 10 bbl slug of acetic acid on top of the fill, allow one hour for the acid to soak, and try again.

Fig. 4. Fill samples’ composition and solubility, Well-B.

Fig. 5. CT BHA used in fill clean out operations – milling BHA.



8. Repeat steps 6 and 7 until reaching TD.9. Pump 20 bbl to 40 bbl of viscous gel with the CT stationary

at TD.10. Perform a bottoms-up by pumping brine with the CT sta-

tionary at TD until clear returns are seen on the surface.11. Squeeze acetic acid across the screens with the well shut-in.12. Pull the CT out of hole to the surface at 60 fpm with the

well shut-in to allow the acid to soak, breaking circulationevery 1,000 ft by pumping 2 bbl of brine.

13. Flow back the well until the above mentioned cleanup criteria are met.

14. If needed, utilize CT nitrogen lifting.

JOB EXECUTION AND OPERATIONAL ASPECTS

Well Loading

At the start of a clean out operation, one wellbore volume offiltered 5% KCl brine is pumped to load the well. After load-ing the well with filtered brine, it is kept shut-in while runningin hole until starting fill clean out. Opening the well prior tothat is unfavorable as it might cause natural unloading of thewell. Consequently, loading the well with brine is not possiblein some instances when there is no injectivity, resulting in asharp increase in wellhead pressure after pumping a smallamount of brine. In such cases, the well is kept open at a lowchoke size setting while running in hole, and brine is pumpedcontinuously to load the well until reaching the fill top.

Monitoring Pressure

While cleaning out the fill, wellhead pressure is maintained ata value predetermined from the simulation software that allowsthe clean out to be performed in a slight pressure overbalancecondition by adjusting the surface choke size setting as needed.This is helpful to avoid/minimize gas influx from the formationthat might lead to very high annular velocities and possiblycause damage to surface equipment. Also, differential pressureacross the CT should be reduced as much as possible to mini-mize CT fatigue. A positive string pressure should be main-tained all the time, i.e., CT treating pressure should be kepthigher than the wellhead pressure.

Annular Velocity

Simulation results predicted that a sufficient annular velocitycould be achieved during the job to efficiently lift fill debrisbased on CT size, optimum pumping rate for the selected clean

out tool, carrying capacity of selected fluids, material to becleaned and wellbore geometry. The annular velocity is muchhigher than the settling velocity of the fill particles once theyare entrained by the clean out fluids. Any interruption of fluidscirculation during fill penetration would cause unfavorable de-bris settling. Therefore, pumps should be on all the time whilecleaning and care should be taken to avoid losing pump prim-ing at any time that might lead to the pumps’ shutdown. Nev-ertheless, pump shutdown is inevitable in certain cases, such asmotor stalls, described in the subsequent section.

Milling Operation

Prior to starting fill penetration in a clean out process, the wellis opened and the pumps are brought up to the optimumpumping rate of the downhole motor. Fluid returns at surfaceare checked to confirm good circulation. Once the pressure ofthe pumps stabilizes, the CT BHA is lowered slowly until aslight increase in treating pressure is seen, coupled with a slightreduction in CT weight. This marks the point when the mill isbarely touching the fill. The mill is left in a stationary positionon top of the fill for several minutes. Then the CT weight on themill is slacked off very gradually and steadied, while monitoringpressure and weight responses. After that, penetration is startedat a very low rate – less than 0.1 fpm. The penetration rate is keptlow until a reduction in pressure and/or an increase in weight areobserved, indicators that the encountered fill has been milledout. After the mill breaches the encountered fill, the penetrationrate can be increased very gradually – no more than 10 fpm.

Patience should be exercised when engaging the fill to mini-mize the chance of stalling the motor. If a motor stall does hap-pen, the pumps should be shut down immediately and pressureallowed to equalize before picking up the mill off the bottom;waiting to restore normal operational parameters before re-suming further milling attempts.

Unexpectedly, the fill deposited in the screens of the impactedwells did not cover the whole screen interval. The encounteredfill was instead composed of a couple of sand bridges near thetop of the screens. The very first sand bridge encountered wasusually several feet thick – 10 ft to 20 ft – and was the hardestand most compacted. The other bridges tended to be 1 ft to 3ft in thickness and less compacted than the first one.

While milling, filtered 5% KCl brine was circulated out ofthe mill with a 10 bbl to 15 bbl slug of gel when performingwiper trips, Table 1. Wiper trips were performed every 50 ft;however, once the sand bridges in the upper portion of the

Step No. ActionStart

Depth(ft)

End Depth

(ft)

Bite Length

(ft)

CT Speed(fpm)

Fluid at Downhole Nozzles

Pump Rate

(bpm)

Duration(min)

Volume(bbl)

Cumulative Volume

(bbl)

FWHP(psig)

1 Penetrate 50 ft 15,420 15,470 50 10 Filtered 5% KCl Brine 2.5 5 12.5 12.5 1,700

2 Sweep 50 ft 15,470 15,420 50 -10 Viscous Gel 2.5 5 12.5 25 1,700

3 RIH 50 ft 15,420 15,470 50 10 Filtered 5% KCl Brine 2.5 5 12.5 37.5 1,700

Table 1. Example of fill clean out schedule


screens were cleared, wiper trips could be performed less oftenand CT speed was increased for the remaining interval to opti-mize the operation. Based on the length of the screen intervaland the amount of fill encountered, the bit length taken to pen-etrate the fill was adjusted as the operation progressed.

Acetic acid may be used as a contingency when no progressis achieved after a couple of milling attempts at the same spot.A slug of 10 bbl is pumped down the CT, and the well is shut-inonce the acid reaches the tip of the CT. After allowing the acidto soak for one hour, the well is opened and milling is resumed.Usually, one slug of acid makes it possible to mill out the fillobstruction, if needed at all.

Fill Clean Out with Jetting Tools

Jetting tools have also been implemented for fill removal, in-cluding fluid oscillation-based tools. A similar methodology to themilling operation is followed except that fill removal using thesetools is performed by the jetting or fluid oscillation effects on theencountered fill. If fill cleanout attempts are unsuccessful usingthe jetting tool, after spotting acid as a first contingency, the CTcan be pulled out of hole and the BHA replaced with a motorand mill as a second contingency. Given the 50% success rateamong clean out jobs performed using the jetting tools, millingwas deemed more feasible for the impacted wells due to thehighly compacted nature of the deposited fill inside the screens.

Bottoms-up/Acid Squeeze

After reaching the TD of the well in a clean out operation, 20bbl to 40 bbl of viscous gel are circulated out, followed by a1.5 wellbore volume of filtered brine to clean out any remainingor settled debris, keeping the well in a slightly overbalancecondition as much as possible. Then a certain quantity ofacetic acid is pumped down the CT, and once it reaches thedownhole nozzles, the well is shut-in to squeeze the acid evenlyacross the screens while moving the CT from the bottom to thetop of the screen interval. The acid is then displaced by filteredbrine. To achieve higher pumping rates, a proper size ball isdropped to activate the circulation sub, which is above the motoror the jetting tool, at the start of the bottoms-up part of the cleanout process. Pumping the fluids through the circulation subalso prevents unnecessary passage of acid through the down-hole motor, if used, while squeezing acid across the screens. Al-though most motors used in clean outs are resistant to acid, itis recommended to minimize the exposure of the inside parts ofthe motor to acid. After all the acid has been squeezed into thescreens, the well is kept shut-in while pulling the CT string outof hole to the surface, allowing time for the acid to soak.

Use of the Rate-Activated Circulation Valve

In some of the performed jobs, a newly developed circulationvalve was deployed for the first time in the Kingdom, whichwas the second place it had been used worldwide. This valve israte activated and capable of operating in both milling modeand circulation mode, depending on pumping rate. Above a

pre-set threshold rate (3.2 bpm to 4.0 bpm), the tool shiftsfrom milling mode to circulation mode, and vice versa whenthe rate drops below that rate. The valve provides the flexibilityto pump at higher rates both while performing the wiper tripsin the clean out job and also while pumping the bottoms-up after reaching TD, resulting in a better hole cleaning. More-over, the valve is equipped with slightly uphole nozzles, whichis advantageous in terms of lifting solids, as compared to thedownward or radial nozzles of the mill or the conventional circulation sub.

Monitoring Returns and Collecting Samples

Throughout a clean out job, fluid returns at the surface arecontinuously monitored, verifying that good circulation isachieved and solid samples are recovered at the surface afterpenetrating the fill. Two choke manifold systems are used because of high wellhead pressure during the operation, alongwith 200 micron sand filters to prevent hazardous damagingof the surface equipment. The sand filters should be bypassedwhen the gel is seen at the surface, because it plugs the filtersvery rapidly, causing high differential pressure across them.Once the slugs of gel have passed, the flow can then be divertedback to the sand filters. The filters are frequently flushed, andcollected solids are sampled and sent to the laboratory for furtherevaluation and analysis. Figure 6 shows some sample picturesof the collected solids in Well-C. The pictures show some blackgreasy materials and shreds of the broken ceramic disk thatwere recovered in addition to the calcite-based fill.

POST-CLEAN OUT PERFORMANCE EVALUATION

At the end of a clean out process, when the CT is at the surfaceand rigged down partially, the well is opened to flow back andassess the need for nitrogen lifting prior to rigging down theCT equipment completely. In almost all performed jobs, thewell had high enough formation pressure to unload naturallyand flow back on its own without nitrogen lifting. In general,the well is flowed back for cleanup by gradually increasing thechoke size from 16/64” up to a maximum of 42/64” in a step-wise manner. The flow back is continued until the solids-freerate is achieved and the aforementioned cleanup criteria are met.

All wells identified as fill clean out candidates after perform-ing the diagnostic work were successfully cleaned out, reachingdown to the bottom of the screen interval. Moreover, all per-formed clean out jobs have been very successful in restoringthe productivity of the impacted wells. To gauge this success,


Fig. 6. Pictures of solids recovered from surface filters during clean out in Well-C.


two comparisons were made:• Pre-clean out vs. post-clean out well performances.• Initial well performance when flowed back for cleanup

prior to starting production vs. post-clean out well performance.

As compared to the pre-clean out performance, productivitygains were significant, in some cases as extreme as turning adead well into a prolific producer of more than 30 MMscfd.Also, the post-clean out flow back results show only a fewhundred psi drop in FWHP and a 0 MMscfd to 4 MMscfddrop in estimated gas rate, as compared to the well’s initialperformance. A sample flow back comparison is illustrated inFigs. 7 and 8, showing that Well-D was flowed back at 26MMscfd both initially and after the fill clean out operation onthe same choke setting (34/64”) with around 475 psi reductionin FWHP. The slight pressure decline can fairly be attributed tonatural reservoir decline in the period over which the wellswere put on production.

Table 2 summarizes the results of the fill clean out campaignin the stand-alone screen completions in gas field MN. A totalof 340 MMscfd estimated gas rate was successfully restoredfrom 16 clean out operations.

The long-term performance of the subject wells has yet to bemonitored and evaluated, since the fill clean out campaign wasonly recently started in December 2010. The subsequent performance of the wells, however, has been reassuring so far,with no signs of fill reaccumulation. Figure 9 provides an example of post-clean out well performance in Well-E over aone-year production period.

RECOMMENDATIONS

Several preventive measures have been taken to resolve the fillaccumulation issue in wells completed with stand-alone screens:1. A research study has been launched to investigate plausible

causes of the fill/scale accumulation. Preliminary results point primarily to the possible incompatibility of the cur-rent Naformate-based drill-in fluids and the calcium-rich formation brine, which results in precipitating CaCO3.

Consequently, alternative drill-in fluids are to be evaluated, along with the feasibility of implementing a scale inhibition squeeze program to inhibit the precipitation of CaCO3. Detailed findings and outcomes of this research study will be discussed thoroughly in a future publication.

2. Another potential cause of the fill deposits is the high fine solids invasion into the producing formation while drilling using the current drill-in fluids. These fine solids might be produced slowly over time back into the wellbore while the well is on production, causing screen plugging. Therefore, two new drill-in fluid systems have been evaluated, and can-didate wells have been selected to perform pilot tests for these new fluid systems. The systems deliver best-in-class practices for drill-in fluid management that minimize solids invasion into the pay zone.

3. Gas well completion practices have been revised with a focus on improved cleanup procedures and fluid return quality specifications while running the different compo-nents of the stand-alone screen completions.

4. The old procedure of breaking the ceramic disk while the rig is on location and flowing back the well for a short period of time has been abandoned because of the tendency

Fig. 7. Well-D initial flow back for cleanup prior to production startup. Fig. 8. Well-D post-clean out flow back for cleanup.

Fig. 9. Well-E post-clean out production plot.



of solids to settle and gravitate down onto the screens whenthe well is shut-in after the short flow back and prior to performing a complete flow back. A new procedure has been implemented where a rigless site breaks the ceramic disk and performs the complete flow back until the cleanup criteria are met.

5. A more aggressive flow back schedule has been adopted, where the well is flowed back for cleanup on larger surface choke settings – up to 42/64” as compared to a previous maximum of 34/64”. This is to help in producing, to a greater extent, the fine drilling solids from the formation prior to production startup.

6. Production performance is being continuously monitored for any trends towards gas rate or pressure drops in the re-cently cleaned wells, as well as in the rest of the wells in gas field MN. Also, frequent TD tags with gauge cutters are scheduled for all wells to monitor the fill accumulation process. These measures will allow the operator to react proactively before a drastic drop in well productivity in casea fill clean out operation is needed.

ACKNOWLEDGMENTS


This article was presented at the SPE Young ProfessionalsTechnical Symposium – Saudi Arabia Section, Dhahran, SaudiArabia, March 19-21, 2012, and at the SPE-SAS Annual Tech-nical Symposium and Exhibition, al-Khobar, Saudi Arabia,April 8-11, 2012.


Well

Pre-Clean Out Post-Clean OutEstimated Gas Rate Gain

(MMscfd)Gas Rate (MMscfd) FWHP (psig) Gas Rate (MMscfd) FWHP (psig)

A 14 1,600 28 5,730 14

B 0 0 28 5,750 28

C 0 0 32 5,900 32

D 6 2,000 28 5,900 22

E 5 3,400 32 5,170 27

F 2 1,600 23 4,550 21

G 10 4,700 25 5,600 15

H 9 4,110 31 5,650 22

I 0 0 28 5,600 28

J 0 0 24 3,900 24

K 7 3,660 21 3,560 14

L 6 5,980 28 5,676 22

M 10 5,400 30 5,480 20

N 10 5,300 32 5,760 22

O 3 4,250 18 4,270 15

P 12 5,690 26 5,762 14

Total Gas Rate Gain = 340 (MMscfd)

Table 2. Summary of incremental gain in productivity from the fill clean out campaign



Mohammed A. Asiri joined SaudiAramco in December 2005 as aPetroleum Engineer. He has worked invarious positions within the company,including the Gas ProductionEngineering Division (GPED) and Gas Well Completion and Services.

Mohammed is the GPED representative for testingmultiphase flow meters (MPFM) on wet gas wells.

He received a B.S. degree in Petroleum Engineering in2005 from King Fahd University of Petroleum andMinerals (KFUPM), Dhahran, Saudi Arabia.

Mohammed is a member of the Society of PetroleumEngineers (SPE).

Nahr M. Abulhamayel began hiscareer in 2004 as a Petroleum Engineerworking with the Gas ProductionEngineering Division. He has workedin various positions, such as aReservoir Engineer and an OperationForeman at Gas Well Services.

Currently, Nahr is a Senior Engineer and is deeply involvedin sandstone formation and production enhancements.

In 2004, Nahr received his B.S. degree (with honors) inPetroleum Engineering from Montana Tech of theUniversity of Montana, Butte, MT.

He has participated in many Society of PetroleumEngineer (SPE) events and other oil and gas industry relatedevents over the span of his career.

BIOGRAPHIES

Murtadha J. Al-Tammar joined SaudiAramco in 2010 as a PetroleumEngineer and spent 3 months workingfor the Production Technology Teamin the Exploration and PetroleumEngineering Center – AdvancedResearch Center (EXPEC ARC) prior

to starting his assignment with the Gas ProductionEngineering Division in the Southern Area.

In 2010, Murtadha received his B.S. degree in PetroleumEngineering from the Colorado School of Mines, Golden,CO.

He is an active member of the Society of PetroleumEngineers (SPE).

Khalid S. Al-Asiri is a Gas ProductionEngineer in the Southern AreaProduction Engineering Department(SAPED). He worked with theMinistry of Petroleum and Mineralsbefore joining Saudi Aramco in 2002.Khalid has worked in several areas

within the company, including Gas Production Engineeringand Gas Well Completion and Services.

In 1999, he received his B.S. degree in PetroleumEngineering from King Saud University, Riyadh, SaudiArabia.

Saad M. Al-Driweesh is a GasProduction Engineering GeneralSupervisor in the Southern AreaProduction Engineering Department(SAPED), where he is involved in gasproduction engineering, wellcompletion, fracturing and stimulation

activities. His main interest is in the field of productionengineering, including production optimization, fracturingand stimulation, and new well completion applications.Saad has 24 years of experience in areas related to gas andoil production engineering.


activities. His main interest is in the field of production

Mohammed is the GPED representative for testing

Currently, Nahr is a Senior Engineer and is deeply involved

to starting his assignment with the Gas Production

within the company, including Gas Production Engineering


ABSTRACT wells’ production potential and to ensure the deliverability ofthe forecasted oil targets. The field under study will have waterinjection wells, and the producers will require electrical sub-mersible pumps (ESPs) to achieve the desired flow rates.

The approach to obtain the PIs described in this article wasdeveloped to be fit for purpose, using all the information avail-able at the time when the study is done so that results are con-sistently based on actual measured data.

The main challenge to accomplishing this goal in the studyfield was that the majority of the available data from well test-ing corresponded to old vertical wells, except for seven hori-zontal producers. The PI values from the seven horizontalwells were used as a benchmark and control values for estima-tion of the future horizontal wells’ PI. Estimated values werealso quality checked by analytically calculating the PIs of thewells using the known reservoir information from core and logdata; PI values from both sources closely matched.

The horizontal well PI values thereby calculated were usedto create contour maps of horizontal well PIs per reservoir.These maps and the coordinates of the increment producerswere used to assign a PI value per well. The maps generated inthis study represent a useful tool for future PI estimations andare meant to be updated whenever new data become available.

PROCEDURE

The following is the procedure used to generate the horizontalwell PI map using limited vertical well data:

• Determine the vertical well PI using pressure buildup, and quality check the data.

• Generate vertical well PI contour maps.• Define the ratio of horizontal vs. vertical wells’ PI by area.• Estimate the horizontal well PI.• Generate horizontal well PI contour maps.• Estimate future horizontal wells’ PI based on contour

maps.• Validate with actual results, and adjust the contour maps

as required.

REPRESENTATIVE DATA GATHERING AND QC

The first step was to ensure that all data utilized are represen-tative. All PIs obtained from well testing were adjusted accord-ing to the following considerations.

Productivity index (PI) is one of the most important well pa-rameters when making an optimum reservoir developmentplan in terms of well spacing, number of wells required and as-surance of the deliverability of the production target. Having acorrect PI estimation is also crucial to optimizing the artificiallift system design, when required.

This article discusses the methodology to estimate horizontalwell PI using actual limited data from existing vertical well performances in a giant field that is still in the developmentphase. The vertical wells’ PIs were calculated based on a pressuretransient analysis (PTA), taking into account the correction forstabilized bottom-hole flowing pressure (Pwf) and reservoirpressure (Pr). As a means of quality control, the calculated vertical well PI was compared against the radial flow equationusing the transmissibility value obtained from the well testdata. PI maps for the vertical wells were constructed, and thenverified against the reservoir properties distribution, which iswell developed in the crest of the field. Converting PIs fromvertical to horizontal well configurations involves an analyticalcalculation that was further tested against actual PI results.The ratio between a horizontal well’s PI and a vertical well’s PIis obtained by comparing Joshi’s and Darcy’s equation. Con-version factors per reservoir and area were determined and ap-plied to generate horizontal well PI contour maps. These mapswere used to assign a PI value to each of the future producersin the field. The estimated values exhibited a reasonable matchwith actual existing data. Notwithstanding this match, minordiscrepancies between estimated and actual PI are analyzed inthis article to further improve the proposed methodology.Reservoir heterogeneities and effective lateral length, whichcontributes to the total well flow, are the main reasons for thedifferences. The impact of the effective lateral length on the actual PI was evaluated and sensitized for better prediction ofthe well performance, whereas the reservoir heterogeneity influence was assessed using a correlation that includes theknown petrophysical properties to estimate the PI of newlydrilled and undrilled wells.

INTRODUCTION

Whenever a new field is in the development phase, an estima-tion of the productivity index (PI) is essential to calculate the


Estimating Horizontal Well PI to Develop Giant Carbonate Reservoir with Artificial Lift Authors: Majid H. Al-Otaibi, Cesar H. Pardo, Ronny Gunarto and Mohammed S. Kanfar


Pr and Drawdown Adjustment

Due to the short testing periods in this field, PI calculationswere based on Pr instead of on the last static measured pressureduring the shut-in period. Short testing periods do not allowthe shut-in reservoir pressure to stabilize, resulting in an under-estimated drawdown, and thereby an overestimated PI. Additionally, the short flowing period may also lead to anoverestimated PI because the drawdown for a vertical well lo-cated in the crest of the field is not completely established atthe end of the flowing period before shut-in, Fig. 1. Pressure is

plotted in the figure in green dots, and it shows that the Pwfhad not yet stabilized when the well was shut-in for buildup.Therefore, an adjustment on the drawdown was made to havea more accurate calculated PI.

On average, the PI adjustment due to Pr vs. the lastrecorded pressure was 7%, while the correction due to theshort flow period averaged 10%.

Influence of Fluid Properties on Flank Wells

Data from all vertical wells tested in the heavy oil zone and inthe aquifer were discarded from this study, as the fluid proper-ties are significantly different there compared to the area wheremost of the producers are placed. The oil viscosity can go upto 1,000 centipoises towards the flanks. Additionally, the reser-voir quality observed at the flanks is noticeably poorer. So, it isnot advisable to use these wells as a reference for PI calculation.

Vertical Well PI Maps

Using the corrected vertical well PI, contour maps like the oneshown in Fig. 2 were generated.

Estimating Horizontal Well PIs

The next step was to convert the vertical well PI maps to hori-zontal well PI maps. Horizontal well PIs were calculated fromvertical well PIs by using a conversion factor. The factor wasestablished by dividing the Joshi’s equation for the horizontalwell PI by the Darcy’s equation for the vertical well PI. TheJoshi’s equation was selected because the wells are expected tobe under constant pressure support. The wells should performunder steady-state conditions, given the pressure maintenanceprovided by water injection. Therefore, the pressure can be as-sumed as constant in the boundaries, and PIs can be calculatedaccordingly.

Based on observation of core data, logs and correspondingmaps, the reservoir’s properties are horizontally isotropic andvertically anisotropic, with significant vertical permeabilityvariations (kv/kh assumed as 0.1):

where and is the Joshi’sequation to estimate horizontal well PI.

Table 1 summarizes the resulting average conversion factorsper area and reservoir. Horizontal wells are expected to have aPI about 1.8 to 2.3 times that of the vertical wells, dependingon the well location.

The horizontal PI contour map is then generated based onthe horizontal PI per well, Fig. 3.

VALIDATING RESULTS

PI maps were validated by comparing the estimated horizontalwell PIs to the actual values. The estimated PIs reasonablymatched the actual PIs with a difference of +/- 11 BPD/psi, Fig.4. The actual PI is determined using either pressure transientanalysis (PTA) or well models calibrated with actual results ofmulti-rate production tests.


Fig. 1. Adjustment on the drawdown, not established due to the short flow period.

Fig. 2. Vertical well PI contour map.

North Flanks Center

Reservoir A 2.2 2.0

Reservoir B 2.3 1.8

Table 1. Average PI conversion factors

where and is the Joshi’swhere and is the Joshi’s



The differences observed in Fig. 4 were assessed to furtherimprove the accuracy of this methodology as follows.

Case 1: Actual PI Is Less than Estimated

After a review of the detailed actual well performance, it was con-cluded that one of the major reasons for a lower actual horizontalwell PI compared to the estimated value is the well’s effective lat-eral length. Effective lateral length is the fraction of the lateralthat contributes to the total well flow. The effective lateral lengthis conventionally determined using a production log by evaluatingthe spinner response along the lateral section.

Note that the horizontal well PI is inversely proportional toliquid viscosity and directly proportional to the effective lateral

length. In the presence of heavy oil or significant viscosity vari-ation vs. depth, it is important to evaluate the actual well tra-jectory to fairly judge the effective lateral length. Some of thelateral section could be exposed within heavy oil, which be-comes inefficient and should not be included in the effectivelateral length calculation.

Figure 5 shows the example of using a flow meter log todetermine effective lateral length. The fourth track from theleft is the typical presentation of the flow meter log. It can beobserved that only a certain portion of the lateral contributesto the flow, and there is no flow contribution from the lower50% of the well. The first track shows the concentration ofthe heavy oil (tar and pyrobitumen), which indicates the pres-ence of heavy oil in the lower 50% of the lateral. The forma-tion pressure while drilling measurement confirms the lowmobility at this section due to high oil viscosity. The effectivelateral length is thereby calculated to be 600 ft compared tothe total length above the heavy oil of 1,500 ft and also com-pared to the total lateral length of 2,900 ft. The other tech-nique to determine effective lateral length is using PTA. Theactual length contributing to the flow can be observed in thePTA as the period of linear flow in the derivative curve, thered line in Fig. 6. Wells with more effective lateral length willshow a longer linear flow period in the PTA. Figure 7 is thecomparison between the actual effective length determinedfrom the production log and the estimated figure from PTA.This approach can be used in the absence of a flow meter logto qualify the lateral length effectiveness, especially in thescreening process for acid stimulation candidate selection.

Case 2: Actual PI Is Higher than Estimated

The other factor influencing the differences in PIs between ac-tual and estimated figures is the reservoir heterogeneity. Theactual horizontal well may have better average permeability

Fig. 4. Comparison between actual and estimated horizontal well PI.

Fig. 5. Example of using PLT to determine effective lateral length.Fig. 3. Horizontal well PI contour map.



compared to the offset vertical wells, which were used to buildthe PI contour maps.

Illustrating this point is the horizontal well shown in Fig. 8,which has an average porosity of 26%. This well was placed atthe top of the reservoir, where better reservoir quality is ob-served compared to the bottom layer. The offset vertical wellswere completed across the whole interval with an averageporosity of 23%. These porosity differences cause an underes-timated horizontal well PI due to nonuniform reservoir qualityacross the layers observed in the vertical wells vs. the horizon-tal wells placed at the top layer at the best reservoir quality.

ESTIMATING PI USING ACTUAL PETROPHYSICALPROPERTIES

For the wells drilled but not yet tested, actual reservoir proper-ties, such as permeability, porosity and net lateral length, canbe utilized to estimate the PI. The process normalizes the dif-ference in the permeability and lateral length between actualand assumed figures in the PI contour mapping. The typicalanalytical calculation for horizontal PI estimation, like theJoshi’s equation, shows that the PI will be proportional to thepermeability X length, assuming that the other parameters areconstant for the same reservoir with a consistent development

strategy and some well spacing. Since the porosity is normallyin the logarithmic relationship with permeability, the PI is ex-pected to have an exponential relationship with porosity Xlength. A correlation was established between these petrophysical

Fig. 6. Example of using PTA to determine effective lateral length in a horizontalwell.

Fig. 7. Comparison between actual effective length determined from PLT andestimated figure from PTA.

Fig. 8. Reservoir quality difference between vertical and horizontal wells.

Fig. 9. Correlations between reservoir properties and actual PI in tested wells,Reservoir A (top) and Reservoir B (bottom).


properties vs. actual PIs from tested wells in each reservoir.The net lateral length is determined using a 5% porosity cutoffto exclude non-effective sections. Sections within heavy oil arealso excluded. To account for the effect of initial water satura-tion on the relative permeability of oil and PI, the correlationincludes the term of So, in addition to porosity, permeabilityand net lateral length.

Figure 9 illustrates the correlations found in the two pro-ducing reservoirs of this field.

Actual PIs of wells tested in Reservoir A exhibited a goodcorrelation with porosity, while PIs of wells tested in ReservoirB correlated better with permeability. These correlations willbe continuously updated as more wells are drilled and tested.They can also be used in undrilled wells for given estimatedpetrophysical properties from the geological model.

CONCLUSIONS AND RECOMMENDATIONS

The PI is a major parameter for making an optimum reservoirdevelopment plan. It dictates the number of wells required andthe spacing needed to meet the production target. Additionally,the PI information is critical to achieving an optimum artificiallift design. The practical approach outlined in this article pro-vides an alternative method to reliably estimate the PI in anundeveloped field, especially in the absence of a simulationmodel and limited dynamic data.

Further enhancement should be made to improve the esti-mation process and the accuracy of the estimated PIs. This en-hancement includes a factor to take into account possibledifferences in the average permeability between the verticalwells’ interval and the target interval for the horizontal wells’placement. Additionally, other factors, such as effective laterallength, should be considered in determining horizontal well PIto avoid overestimating the figures.

ACKNOWLEDGMENTS


NOMENCLATURE

a half the major axis of drainage ellipse, ftBo oil formation volume factor, RB/STBh reservoir thickness, ftJh horizontal well productivity index, BPD/psiJv vertical well productivity index, BPD/psiK average well permeability, mdKh horizontal permeability, mdKv vertical permeability, mdL horizontal well length, ftre drainage radius, ftrw wellbore radius, ftreh effective horizontal drainage radius, ftrev effective vertical drainage radius, ft

Sm mechanical damage, dimensionlessµo oil viscosity, cp SQRT(Kh/Kv)

BIOGRAPHIES

Majid H. Al-Otaibi has 15 years ofexperience with Saudi Aramco. Duringthis time, he has worked in a variety ofdisciplines, including productionfacilities, production engineering,drilling engineering and reservoirmanagement. Majid has participated inmultiple increments that Saudi Aramco

has put onstream in recent years, including HRDH-III,KHRS and NYYM. In reservoir management, he led theupscale development of a thin oil zone in a giant maturecarbonate reservoir in Saudi Arabia. Majid now works asthe Upstream Team Leader for the Manifa Increment.

He received his B.S. degree in Chemical Engineeringfrom King Fahd University of Petroleum and Minerals(KFUPM), Dhahran, Saudi Arabia, and his M.S. degree inPetroleum Engineering from the University of Texas atAustin, Austin, TX.

Cesar H. Pardo has 22 years ofexperience with E&P companies. Hejoined Saudi Aramco in 2006 andworked for 1 year for the GasReservoir Management Department(GRMD) as a Senior ReservoirEngineer. In April 2007, Cesar was

moved to the Manifa Reservoir Management Division(MRMD), where he currently works as a PetroleumEngineer Specialist. In 1987, he began working atEcopetrol (the Colombian state company), where heworked for 4 years in drilling, workover and productiontechnology engineering.

In 1990, Cesar joined Shell Colombia (Hocol) as aWorkover Engineer. In 1992, he was promoted toProduction Technology Engineer and successfully designedand implemented a fracturing campaign for 30 producerwells, and an ESP and gas lift campaign for over 70 wells.In 1996, Cesar was promoted to Reservoir Engineer,working in classical reservoir engineering and numericalreservoir simulation with Eclipse; he performed an OFMstudy, identifying new infill drilling and workoveropportunities. In 2002, he was promoted to SeniorReservoir Engineer and given the additional responsibilityas a Team Leader (Asset Manager Deputy); he preparedand coordinated the Field Development Plan (FDP) for aheavy oil field. In 2004, Cesar was promoted to ReservoirEngineering Network Leader for the whole company inColombia; he coordinated and prepared the new Hocolbooks for forecast and reserves, coordinated calculationprocedures, and coordinated the annual reserves reviewand auditing for 2 years.

Cesar received his B.S. degree in Petroleum Engineeringfrom the Universidad de America, Bogotá, Colombia.


moved to the Manifa Reservoir Management Division


Ronny Gunarto joined ChevronIndonesia in 1997 as a ProductionEngineer in charge of workover designand the supervision of several oil fields.He was involved in detailing the wellintervention program and its execution,including hydraulic fracturing,

acidizing, logging, perforation jobs and artificial liftinstallation. Starting in 2000, Ronny worked as a ReservoirEngineer on the Asset Team assigned to lead the fielddevelopment plan for both primary and secondary recoveryoil fields, including an infill drilling proposal, simulationstudy and asset management plan. He managed bothperipheral and pattern waterflood projects and successfullyimproved the field’s performance. Ronny was assigned tovarious fields within Chevron Indonesia, including a short-term assignment at Chevron headquarters in San Ramon,California.

In 2004, he moved to Total Indonesia as Head ofReservoir Engineering for a major gas field in Balikpapan,Indonesia. Ronny was responsible for managing thereservoir surveillance and development plan of a 700MMscfd gas field in a challenging environment withmultilayered reservoirs. He led the drilling initiative fornew wells and the well intervention campaign, whichsuccessfully increased the field rate more than 50% in 2years.

In 2006, he decided to take on a new challenge inPetronas Malaysia as the Staff Reservoir Engineer in chargeof all producing oil and gas fields in Malaysia. Ronnyworked closely with all international oil and gascompanies, i.e., Shell, ExxonMobil, Murphy, Nippon, andothers, to ensure optimum reservoir development andimplementation of the production strategy in all fields.

Then in 2008, he joined Saudi Aramco as SeniorReservoir Engineer in the AFK fields. Ronny led thereservoir management of both Abu Hadriya andKhursaniyah fields. Recently he was transferred to theManifa Development Project, which currently is the biggestincrement in Saudi Aramco.

Ronny has written and published a number of technicalpapers, both in Production and Reservoir Engineering, andpresented papers in local and international forums.

He received his B.S. degree in Chemical Engineering in1992 from the Bandung Institute of Technology, Bandung,Indonesia.

Mohammed S. Kanfar joined SaudiAramco in 2009. He is a PetroleumEngineer working for the NorthernArea Reservoir ManagementDepartment. In 2010, Mohammedjoined the Society of PetroleumEngineers - Saudi Arabia Section (SPE-

SAS), serving on the SPE Young Professionals and StudentOutreach Committee.

He received his B.S. degree in Petroleum Engineeringfrom Louisiana State University, Baton Rouge, LA, and iscurrently pursuing his M.S. degree in PetroleumEngineering from Texas A&M University, College Station,TX.


acidizing, logging, perforation SAS), serving the SPE


creo

ABSTRACT how further optimization of ESP well performance with fre-quent testing is also accomplished with MPFMs, which in turnimproves the sweep efficiency of the reservoir, accelerates theproduction of recoverable reserves and environmentally helpsto improve pump run life. It also elaborates on the benefits at-tained from installing MPFMs in mature offshore oil fields,with a focus on special cases like MPFM in-series testing andtesting of artificially lifted wells, smart well completions andnewly completed wells exhibiting an indirect support in achiev-ing the production targets. Different principles and theories behind MPFMs are highlighted, along with their advantagesand a vision of the way forward. To further the benefits of installing MPFMs, this article also discusses lessons learnedand improved guidelines imposed over wellhead sampling(WHS) that benefits from the success of the MPFM; theseguidelines effectively minimize sampling in wells equipped withMPFMs.

INTRODUCTION

Well testing provides an effective way to evaluate and monitorthe performance of a producer by measuring the flow rates ofeach individual phase. The traditional approach to the meas-urement of produced effluent required the separation and inde-pendent measurement of the oil, water and gas. In complexdevelopment environments, however, like those offshore orclose to residential areas, where space and weight are of a majorconcern, the large size and weight of the conventional separatorsmade testing, in most cases, physically infeasible. One methodused to overcome this situation was the installation of the con-ventional separator on a test barge, which could be mobilizedfrom one platform to another to facilitate the necessary testingof each well on multiple platforms. As this kind of well testing,involving mobilization from one platform to another, wasavailable only during favorable weather conditions, considerablenonworking (standby) time accrued each year (about a third ofa year) due to bad weather conditions. Therefore, a new testingmethod for offshore wells had to be established.

Multiphase measurement is the quantification of oil, waterand gas phases in a production stream without the separationof the phases before the stream enters the meter1-5. A multi-phase flow meter (MPFM), compact and lightweight comparedto conventional separators, can generate accurate flow meas-

Prior to the broad implementation and utilization of multi-phase flow meters (MPFMs) in Saudi Arabian offshore oilfields, rigorous in-series testing was performed utilizing MPFMsystems in conjunction with Saudi Aramco’s testing fleetequipped with conventional separator testing traps. For abouta year, sets of data were collected simultaneously from differ-ent wells through different MPFMs implemented in differentreservoirs to compare and validate MPFM results against thoseof conventional traps. The accuracy of the MPFM proved tobe within engineering’s acceptable margin of error for all parameters, and in most cases, its results matched those ofconventional methods. Offshore platforms are now beingretrofitted with MPFMs to enable operators to test all thewells on the platform by selectively switching them one at atime through a test line, physically and remotely.

Since its pioneer implementation almost a decade ago,MPFM testing has improved considerably in accuracy and thetechnology. The use of the MPFM has many advantages intesting operations, especially during periods where demand ishigh. Accurate and frequent well testing becomes decisive intimes of maximum production rates, since the results from welltests facilitate determining which wells are experiencing signifi-cant decline and which have increasing water cut in a real timefashion, especially in fields with a large number of wells. Thequick identification of these problems leads to taking immedi-ate action to restore the wells’ productivity and to maintainoptimal production rates. The MPFM, which offers real timewell performance monitoring through the Supervisory Controland Data Acquisition System (SCADA), has an added benefitof shorter test rate stabilization times. Additionally, the recentinduction of the remotely operated selector switch in the unitshas allowed full automation of the process of switching re-motely among different wells for well testing on a multi-wellplatform; this minimizes human involvement and provides op-erational flexibility. Finally, MPFMs reduce the waiting timefor well switching due to natural limitation factors, such asbad weather offshore.

This article largely addresses the reliability and accuracy ofMPFMs as compared to a conventional separator using electri-cal submersible pump (ESP) optimization applications to iden-tify what method gives more accurate testing. The article notes


Moving Toward Intelligent FieldApplications: MPFM for Production RateTesting and Beyond

Authors: Karam S. Al-Yateem and Nami A. Al-Amri


urements and operate in a wide range of flow regimes andchanging fluid conditions5. Initially, the driving force behindMPFM development was primarily the need for subsea multi-phase metering to enable development of marginal fields at ac-ceptable and economically justified costs. Another importantmotivation for MPFMs was the attractiveness of topside use ofthe technology. Over the last decade, MPFM technology hasimproved significantly, and its test results are becoming in-creasingly accurate and repeatable.

One offshore field in Saudi Arabia has more than 150 plat-forms with over 500 producers. These platforms differ in phys-ical size and vary from a single well to 10-well configurations.The majority of the wells are equipped with two-gauge perma-nent downhole monitoring systems (PDHMSs). This providesan excellent opportunity for data integration that will be addressed with futuristic views. Therefore, the field has been elevated from a brown field (conventional) to a green field (intelligent). It is equipped with measurement, communication,control and software enabling real time and automated assetmanagement and field rate optimization. It is all about infor-mation, whether improved downhole data that can unlockreservoir secrets with cutting edge exploration techniques orways to enhance production.

MULTIPHASE FLOW METER OBJECTIVES ANDOPERATING PRINCIPLE

MPFM measurement accuracy has evolved through the years.With many different MPFM techniques employed by variousproviders, the user must carefully evaluate the pros and consand field applicability of each technology. The application environment (onshore vs. offshore) and the produced fluidpressure-volume-temperature (PVT) data, including salinity,viscosity and density, are all parameters that should be consid-ered. Gas volume fraction (GVF), content of hydrogen sulfide(H2S) and water cut, among others, are also key parameters inselecting a design and method of operation.

Ideally, the output will be the exact measurement of oil flowrate, along with the associated gas and/or water production, ifany, to engineering’s acceptable range of accuracy2. A devicethat can provide such a measurement in a direct manner, with-out dependence on other measurements, is unfortunately notavailable yet. Therefore, most of the efforts in tackling thischallenge have been oriented towards the utilization of instantvelocity and cross-sectional fractions in estimating volumefractions with the identical velocity of each flow stream6. Consequently, the effect of gas and/or water over oil must bemeasured and identified.

Some meters utilize the Coriolis flow meter methodology,combined with a microwave that can measure water cut in therange of 0%-100%2. Using this meter on production at a lowgas-oil ratio (GOR) does not require separation to make theoil, water and gas rate measurements. Such MPFMs consist ofa Coriolis mass flow meter, a pressure transmitter and a differ-ential pressure transmitter2. The transmission of the raw data

from incessantly measured mass flow, pressure, density andtemperature, along with the dielectric properties of the flowstream, enables the determination of the gas, water and oilflow rates in real time for the subject test flow path. The meterfirst computes the water volume fraction (WVF) measuredthrough the water cut meter, articulating the actual liquid den-sity with the utilization of provided PVT data; for this reason,it is of paramount importance to provide the meter with asmuch accurate PVT data as feasible. The Coriolis measures themass flow rate and fluid density. From the combination of themeasured fluid density and the calculated liquid density, thegas fraction is estimated, and consequently the flow rates aredetermined in accordance to three governing flow equations5.

wc = cw1-μ

pm = pl (1-a) + pg * apl = po (1-wc) + pw * wc The MPFM further includes a venture meter, a differential

pressure device that calculates the velocity of the mixture flow-ing through the pipe. It also has a capacitance and inductivesensor that determines the water-oil ratio of the fluid. Thegamma densitometer calculates the density of the fluid.

Data from the meter’s sensors are sent to a computer, wherecomplex algorithms determine the three phases flowingthrough the pipe. The data can then be downloaded or accessed through the SCADA system.

The meter therefore consists of a venture section, a gammasource and a detector. Fluid flow should be in the upward direction, which allows the meter to differentiate the threephases (oil, water and gas). The basic principle of the meter isfairly simple: the total flow is multiplied by the oil volumefraction (OVF), the WVF and the GVF to give the three differ-ent fluid component rates. To get the OVF, WVF and GVF, thedifferential pressure determines the total flow for the meteracross the venture section. The three components of the fluidare determined by the high and low energy level count ratesfrom the gamma source. The high and low energy count ratesare cross-plotted to form a solution triangle. Every test pointmust fall within the solution triangle (operational envelope),which gives the OVF, WVF and GVF of the liquid. The OVF,WVF and GVF can then be multiplied by the total flow rate togive the rates for oil, water and gas.

MPFM ACCURACY VALIDATION AND ASSESSMENTS

Saudi Aramco launched a number of comprehensive testingprograms to evaluate the performance and suitability of varioustypes of compact MPFMs7. These trial tests showed that theaccuracy of the testing data from some types of MPFMs iswithin acceptable marginal errors when compared to datafrom testing separators7.

This initial testing was followed by extensive testing of vari-ous MPFMs through a three-month period in one offshorefield. The test was conducted utilizing over 160 wells underdifferent operating conditions4. A MPFM was installed on atest barge with a conventional separater so that individual




offshore wells could be tested in-series with traditional separatormethods. For the subject trial, tested wells had a total liquidrate ranging from about 300 to over 12,000 barrels per day(bpd), and a water cut from 0% to 70%. The trial showed thatover 93% of the well test results using MPFMs were within +/-10% of test barge separator results for all liquid, oil and watercut measurements. For measurements of the GOR, the compar-ison was made between the measured values and the historicalGOR data from field PVT data, since the field under testingproduces from an undersaturated reservoir with no free gas, sothe produced gas is equal to the solution gas.

The three-month trial was followed by a longer test. For almost a year, the meters were tested in the field utilizing thetest barge, which essentially meant that two sets of data werecollected simultaneously. As a result, the accuracy of the metercould be directly compared against the test barge separatordata. This approach was also beneficial in reducing the timerequired for the initial profile (envelope) setup of the MPFMsduring the installation process. Over 350 well tests were ana-lyzed to determine their accuracy. The meter results, whencompared against the test barge separator values, proved extremely accurate over wide production ranges. For this ex-tended trial period, the total liquid rate ranged from around1,300 bpd to over 12,000 bpd, water cut ranged from 0% to50%, and GOR fluctuated between 150 to 350 standard cubicfeet/stock tank barrel. The MPFM accuracy was proven to bequite good for all four essential parameters: (1) liquid rate, (2)oil rate, (3) water cut, and (4) GOR. Data evaluation indicatedthat both the liquid and oil rates were within +/-10% and thewater cut measurement was within +/-5%.

To date, two main types of MPFMs have been widely installedin large numbers in Saudi Arabian offshore fields, since thesetypes satisfied the company’s qualification criteria in additionto their light weight and small size.

In recent years, more than 3,000 flow rate tests have beenconducted by MPFMs. In addition to providing data, tremen-dous economic savings have been realized due to a significantreduction in operating expenditure (OPEX) associated with welltesting activities. Comparisons of production rate and watercut for newly tested wells are shown in Figs. 1 and 2. These encouraging results led to a certain level of trust and comfortwhen dealing with MPFMs in Saudi Aramco, enough so thatthe separator testing units on platforms equipped with MPFMsare used to conduct tests only once a year as a quality assurancemeasure. More visits by the testing barges are considered whenthe questionable performance of a well suggests the need for areevaluation of the well performance to verify if a MPFMneeds calibration and to cross-check the performance of thesubject well. Well rate testing using the conventional separatorson testing barges is widely considered to be relatively more accurate and so is used to benchmark the performance of theMPFMs. This cross-check is especially important for producersduring a peak production period. From over the recent fiveyears of experience in utilizing different types of MPFMs to

test oil wells, it was found that MPFMs need calibration on anannual basis in most cases.

From the corporate testing database, a set of testing datawas selected for this analysis.

The testing data results exhibited a very good coverage ofthe locations and the flow rates of wells in the entire field. Theflow rates covered wide ranges of fluid flow rates, with watercut ranging from zero up to 55%. Comparison of the testingdata obtained from the testing barge/separator with that fromthe MPFM reveals that a high percentage of testing data fromthe MPFM either matched the testing data from the testingbarges’ separators or fell within acceptable engineering marginalerror. Further investigation into those testing data that did notmatch well led to the finding that the majority of those testingdata from the MPFMs had actually been requested by engineersto cross-check the questionable performances of meters theysuspected needed calibration. Excluding the test data obtainedfrom MPFMs requiring calibration, over 80% of the testing datafell in a range of 10% difference in flow rates and water cuts.

As confidence in the MPFMs grew larger, a MPFM was installed in-series with a test separator on one of the testbarges. This installation was thought to increase the test

Fig. 1. Total liquid rate comparison plot of two different MPFM readingscompared to the separator reading.

Fig. 2. Water cut comparison plot of two different MPFM readings compared tothe separator reading.



barge’s efficiency, due to the shorter stabilization and testingtime required, and was supported by the encouraging results ofthe MPFMs over the years. Having a MPFM aboard the testingbarge not only has achieved its main goal of increasing testingefficiency, but has also led to shortening the calibration timefor newly commissioned MPFMs and to discover when cali-bration is needed in other MPFMs. A few rate tests were conducted using the three testing meters at once: i.e., platformMPFM, test barge MPFM and test barge separator. The plotsin Figs. 1 and 2 exhibit the results from testing with the differentMPFMs compared to the separator as a reference measurement.

Another accuracy validation came from the wells artificiallylifted with an electrical submersible pump (ESP), where theperformances of wells and pumps are closely monitored usingspecialized ESP monitoring software applications. The applica-tion compares actual vs. modeled parameters to optimize ESPwell performance and is used to validate different rate testings.In the validation process, while all other variables are checkedand kept constant, water cut and the GOR measurements fromthe separator testing or from the MPFM readings are enteredinto the model, then the model simulates the total fluid rate expected based on the values entered. When there were discrepancies between the readings of the MPFM and of theseparator, it was noticed that fluid rates were more accuratefrom separator testing, Fig. 3, but water cut and GOR readingswere more accurate using the MPFM reading. The water cutmeasurement discrepancies may have resulted from the emul-sion phases that came into existence after the installation ofthe ESP. Emulsion results from the mixing of oil and water athigher velocities to create a dispersion of droplets of one liquid in another. Thermal and chemical treatments are required to account properly for this emulsion effect, whichrenders basic sampling with a centrifuge machine inaccurate.Therefore, proper measurement of water cut in the presence ofemulsion would happen only when using a fraction meter thatis capable of interacting with elements smaller than the scale ofthe emulsion, i.e., the length of investigation should be smaller

than the diameter of the smallest inclusion of the emulsion6.This is the case for the gamma ray meters, as they interact atthe atomic level, much smaller than the inclusion diameter,which is why MPMFs are more accurate than the separatorwhen making water cut measurements in ESP wells.

MULTIPHASE METER BENEFITS

The benefits of multiphase metering of well production havebeen well documented for both naturally flowing and artifi-cially lifted wells1, 3-5, 8. Multiphase measurement allows theelimination of test lines to the platform, the test separator’s infrastructure and potentially even the expense of slug catchers.This is extremely important when the economic justification ofoffshore and marginal projects is evaluated: MPFMs will reducecapital expenditures in mature fields’ increments through theelimination of expensive conventional testing requirements,and it is more effective in new field developments by eliminatingthe need for installing test lines. MPFMs are also low mainte-nance, and that will reduce OPEX. Moreover, the meter supportsthe improvement of well testing efficiency by providing accept-able accuracy in flow measurements without the need for fluidseparations, while data are transmitted to SCADA in real time,availing continuous real time monitoring opportunities.

In an offshore environment, MPFM installations minimizethe need for test barges to travel from one platform to another,and therefore, reduce offshore traffic, decrease the probabili-ties of accidents, and allow better resource utilization, therebyaugmenting work in a safer environment. Another benefit tohealth, safety, security and environment is that installing aMPFM on a production platform will reduce human interaction,which becomes more important with live wells having highH2S concentrations.

The use of the MPFM has many advantages in testing oper-ations, especially during periods where the demand is high. Accurate and frequent well testing can sound the alarm forearly water breakthrough or unexpected gas cusping, if coningeffects are carefully noted. This rather intangible benefit of rig-orous installation and use of MPFMs mounts up to considerableearnings, especially if the right action is taken to mitigate suchscenarios. More optimization benefits can be attained fromcollecting real time rate testing, such as ensuring adherence tothe field production strategy. Target rates are set based oncomprehensive modeling of all the different facets of the reser-voir; the simple act of following the production plan can prolongthe life of the wells and assure better asset management.

Additionally, the recent induction of the remotely operatedselector switch in the units has allowed full automation of theprocess of remotely switching different wells for well testing ona multi-well platform. It both minimizes human involvementand provides operational flexibility. Adding to the MPFMs’advantage is their small size, as these meters take up much lessspace and weigh much less, which is important for offshore environments where space is limited. In addition, usingMPFMs reduces the waiting time for switching wells due to

Fig. 3. Total liquid rate comparison plot of MPFM and separator readings for ESPwells.


natural limitation factors, such as bad weather in the offshorearea. Further optimization of the ESP well’s performance withfrequent testing is also accomplished with MPFMs, which inturn improves the sweep efficiency of the reservoir, acceleratingthe production of recoverable reserves.

The existence of MPFM facilitated flow rate testing enabledinflow performance determination of all laterals of a smartwell completion. This was conducted in real time and providedan opportunity to make instant rate modification by using theinflow control valves (ICVs) to restore the optimal rate setting.Moreover, the existence of archived historical data in SCADAmade it easy to back allocate and simulate the results that supported an overall evaluation of two of the first horizontalmultilateral smart well completions6. The test was run for twodifferent wells with two different completion configurations.This practice helped optimize the completion design (tubingsize, number of multilaterals, etc.) of the dual-lateral wellswith ICVs to maximize their production9.

WELLHEAD SAMPLING (WHS) OPTIMIZATION

Through a comprehensive reconciliation of the existing WHSguidelines, MPFMs have supported the establishment andadoption of new guidelines for data acquisition and WHSpractices in 10 onshore and offshore fields, resulting in a majorcost saving, operational avoidance and utilization of optimalresources. This optimization led to a significant reduction inproduction engineering requirements, from over 18,000 toaround 8,000 samples per year10. Assessments of salt, sandcontent, basic sediments and water, and geochemical samplesare basic tools used by production engineering to carry out keyresponsibilities and assist in implementing fundamental pro-duction engineering strategies. These data are also beneficialfor close monitoring of field water conformance and flood-front salinity for fields under water injection and will assist inwide-scale field development strategies. WHS optimization wascarried out by focusing on the fiscal responsibility to take overall of the inherited requirements while utilizing practices basedon an individual field’s specifications. It should be noted thatWHS enhancement was successfully achieved with the help ofnew technology utilizations, MPFM in particular. For instance,the MPFM installations have drastically reduced most of theWHS to detect water cut, replacing that sampling with relianceon the MPFM’s attractive real time water cut measurements,Fig. 4.

For example, in one deliverable from the study, the numberof water samples required for wells with water cut above 5%decreased to none, due to the continuous good MPFM testdata. As indicated, it was found that almost all of the MPFMsare showing accurate water cut measurements for wells pro-ducing water cut above the 5%. Therefore, over 1,000 in-stances of WHS were eliminated from offshore fields alone.

THE WAY FORWARD

The second-generation multiphase meters introduced the dual-

velocity method (gas and liquid traveling at different speeds),and phase fractions now were calculated based on capacitanceand conductivity measurements in combination with a singleenergy gamma densitometer and venture section. The newermeter does not require mixers to homogenize the flow or sepa-rators to split the flow before measurement, providing a wideroperating range10. This change dramatically improved the accuracy of multiphase metering.

Other key improvements of the second-generation meter include long-life parts, so that they can operate in harsh envi-ronments, and reduced power consumption. For all its improvement and benefits, however, some limitations to thesecond-generation multiphase meters remain. It still provides asimplification of complex flow patterns; the nucleonic gammasource continues to pose environmental concerns; and the integration of MPFM with other sources is still required forreal time monitoring. Even newer MPFMs, the so-called next generation MPFMs, will address all the issues previously mentioned, with better accuracy to provide more detailedknowledge on flow rates and complex flow patterns and awider operating envelope. A radioactive source is one optionalcomponent in the second-generation MPFMs; although the radiation levels are very low, managing the radioactive sourceis still complicated.

Another feature needed from the new MPFMs is remote access to virtually all functions of the meter, including softwareupgrades. This can benefit the operator, allowing expert operatorsonshore to download data for analysis and to provide expert assistance in configuration/analysis or troubleshooting,irrespective of weather conditions, the availability of local personnel and other operational constraints. In addition to thecost-saving benefits, downtime would be reduced to a minimumin case reconfiguration/setup is necessary.

The MPFM data logger has a large data storage capacitythat is capable of receiving sensor signals every second andstoring running averages. Data logger information can later bedownloaded to a computer and analyzed. Nowadays, theMPFM has been recognized as one important element of intel-ligent field management. One obvious application of a down-hole MPFM is for multi-zone production through a singlestring, where the only alternative method of zonal allocation is


Fig. 4. Water cut measurements obtained from WHS vs. those attained fromMPFMs against time.


by intervention and production logging on a regular basis. InSaudi Arabia’s offshore fields, more and more multilateralwells are being drilled. Downhole flow monitoring and meter-ing will play a more and more important role in lateral pro-duction optimization and measurement.

CONCLUSIONS

In summary, MPFM technology has proven beneficial at vari-ous scales in the industry. Some of the major benefits are: • More flexible operational logistics are available with remote

control and monitoring capabilities; artificial lift wells can be monitored and controlled without visiting the site. This is associated with a reduction in manning requirements.

• Well performance diagnostics and optimization in a real time fashion can provide alerts for the first time the well becomes wet, there is a sudden increase in water cut, etc. The ability to perform well test analyses and achieve perform-ance trends is another advantage.

• Through SCADA, the integration of other intelligent field equipment, such as PDHMS, is valuable, especially in meas-uring the effectiveness of chemical treatment in real time.

• Operation expenditure in the case of developed fields, and capital expenditure and operational expenditure for new developments, is minimized, mainly in lowering the equip-ment installation attended for similar objectives and in the reduction of site visits. Therefore, it brings a dramatic reduction in nonproductive time for field services personnel.

ACKNOWLEDGMENTS

The authors would like to thank Saudi Aramco managementfor their permission to present and publish this article. A spe-cial thank you goes to the technical review committee of theNorthern Production Engineering & Well Services Department(NAPE&WSD) for their comments, Wenrong Mei for his in-sightful addition and contribution, Reja Khaldi for his closefollow-up and recommendations, Ahmed A. Almutairi for hisvaluable input and assistance, and Konstantinos Zormpalasfor his technical and overall review. Appreciation is also due tothose who participated in the work.

This article was presented at the SPE Intelligent Energy Inte-national 2012, Utrecht, The Netherlands, March 27-29, 2012.

NOMENCLATURE

α calculated gas void fractionρ| fluid density measured by the Coriolis meterCw water concentration in the fluid measured by the water

cut meterρw,o,g density of water, oil and gas at the meter conditions

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6. Handbook of Multiphase Flow Metering, NorwegianSociety for Oil and Gas Measurement and the NorwegianSociety of Chartered Technical and Scientific Professionals.

7. Al-Taweel, A.B. and Barlow, S.G.: “Field Testing ofMultiphase Meters,” SPE paper 56583, presented at theSPE Annual Technical Conference and Exhibition,Houston, Texas, October 3-6, 1999.

8. Busaidi, K. and Bhaskaran, H.: “Multiphase Flow Meters:Experience and Assessment in PDO,” SPE paper 84505,presented at the SPE Annual Technical Conference andExhibition, Denver, Colorado, October 5-8, 2003.

9. Alysed, S. and Yateem, K.S.: “Testing Methodologies forSmart Wells Completion Optimization and ProductionRate Setting for Maximum Hydrocarbon Recovery,” SPEpaper 150014, presented at the SPE Intelligent EnergyInternational, Utrecht, The Netherlands, March 27-29,2012.

10. Makki, Z., Jose, V. and Nasir, S.: “Wellhead Sampling Optimization Study,” Saudi Aramco internal technical evaluation report.



Nami A. Al-Amri is a ProductionEngineer working at the Safaniya fieldin the North Area ProductionEngineering Department. Hisexperience includes working withreservoir management, productionengineering and field operations. Nami

is also enrolled in the corporate Production EngineeringSpecialist Program (PESP) working on an artificial liftspecialty with a primary focus on ESP applications. Hereceived his Society of Petroleum Engineers (SPE)Petroleum Engineering Certification in 2012.

In 2003, Nami received his B.S. degree in PetroleumEngineering from the University of Tulsa, Tulsa, OK. Healso received two M.S. degrees in Petroleum Engineeringand in Engineering & Technology Management (ETM)from the Colorado School of Mines, Golden, CO, in 2010.

BIOGRAPHIES

Karam S. Al-Yateem started hisprofessional career with Saudi Aramcoimmediately after graduation. Sincethen, he has completed severalassignments in various onshore andoffshore field locations. Karam hasworked as a Reservoir Engineer, Field

Engineer, Testing Engineer and Production Engineer. Heworked with the Computational Modeling TechnologyTeam as a summer student trainee. Karam later worked onthe 3D Well Planning and Analysis System Project and wasa mentor to many newly hired young professionals.

He has authored and coauthored several technicalpapers. Karam has represented Saudi Aramco in variousinternational forums and conferences, and he chaired thefirst Society of Petroleum Engineers (SPE) YoungProfessionals Technical Symposium (YPTS) in 2007. He isthe recipient of the 2008 Young Member OutstandingService Award. Karam is an active SPE member andcurrently serves as a member of the Young ProfessionalsTask Force of Production & Operation, as an executiveboard member of the Saudi Arabia Section of SPE and as aboard member of the Saudi Oil and Gas and Brazil Oiland Gas magazines. Karam is also an executive boardmember of the University of Southern California (USC)Alumni Club of Arabia. He is a member of the ArabianSociety for Human Resource Management (ASHRM),Society of Exploration Geophysicists (SEG) and SaudiCouncil of Engineers. Karam received his SPE PetroleumEngineering Certification in 2012.

In 2005, Karam received his B.S. degree in PetroleumEngineering from King Fahd University of Petroleum andMinerals (KFUPM), Dhahran, Saudi Arabia. In 2010, hereceived his M.S. degree in Petroleum Engineering from theUniversity of Southern California (USC), Los Angeles, CA,specializing in Smart Oil Field Technologies andManagement.

is also enrolled in the corporate Production Engineering

Engineer, Testing Engineer and Production Engineer. He




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Nonmetallics and Their Role in Shaping the Future of Saudi AramcoMauyed S. Mehdi and Hussain A. Bunaiyan

A! STRACT

In 2006, Saudi Aramco embarked on an ambitious Nonmetallic Program to help control corrosion, to encourage the conversionof oil into petrochemicals and to enhance the supply chain. This article demonstrates the role of nonmetallics in shaping thefuture of Saudi Aramco.

Triazine!! ased Scavengers! Can They ! e a Potential for Formation Damage!Yasser K. Al-Duailej, Dr. Mohammed H. Al-Khaldi and Saleh A. Al-Kulaibi

A! STRACT

Hydrogen sulfide (H2S) scavengers have been used extensively in different field operations, such as drilling and acid stimulationtreatments. Typically, H2S scavengers are preliminarily designed to react effectively at different in-situ conditions. For example,triazine-based scavengers are designed for neutral to high pH conditions, while aldehyde-based scavengers are intended for lowpH conditions.

Real!Time !ntegrated Petrophysics! ! eosteering in Challenging ! eology and Fluid SystemsMajed F. Kanfar

A! STRACT

Since the advent of horizontal wells, the oil and gas industry has come a long way to ensure optimal drilling and well placementpractices. The proper placement of these wells has meant that measurement while drilling (MWD) and logging while drilling(LWD) have come to play a primary role in geosteering, placement and evaluation of highly deviated or horizontal wells.

! igh Rate Sour ! as Wells! Solids!Free Clean OutAbdulrahman S. Ahmari, Elio A. Uzcategui, Samih M. Alsyed and Abdulrahman A. Ghamdi

A! STRACT

Saudi Arabia’s first offshore high rate dry gas field has an overpressured reservoir. Successful pressure control during drillingrequired the use of barite in the water-based drilling mud. Barite is very abrasive and is insoluble in any acid or solvent. Anybarite left in the reservoir due to mud losses has to be produced back to the surface after completing the wells.

Additional Content Available Online at! !!!!!audiaramco!com!!ot

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