JPT1999_10_IS

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I N T E L L I G E N T S Y S T E M S

An intelligent completion enables acqui-

sition of real-time data and provides a com-

pletion method that allows reconfiguring

well architecture whenever needed, with-out rig intervention. Although intelligent-

completion technology can assume several

configurations, this study considered only

downhole control valves and power/com-

munication umbilicals needed to monitorand control multiple completions in a sin-

gle wellbore. The study objectives were todetermine if the application of intelligent-

completion technology could improve theeconomic performance of a field in the Gulf

of Mexico (GOM) and to investigate meth-

ods for predicting this performance.

Many types of completion are used in the

GOM. The simplest is a well with a singletubing string to drain one reservoir for the

life of the field. When a single reservoir will

not support a well for the life of the field,

several reservoirs can be produced sequen-

tially through a single tubing string byrecompleting the well as each reservoir is

depleted. For two reservoirs, a single selec-

tive completion (sliding-sleeve circulating-

type device) can be used. A dual-tubing-string completion allows both reservoirs to

produce simultaneously. Because the stud-

ied field uses dry trees and targets a maxi-

mum of two reservoirs per wellbore, these

options are available.Candidates for intelligent completion are

wells drilled through multiple productive

reservoirs to capture reserves by simultane-

ous or selective production. The intelligent

completion allows monitoring and control

of each reservoir to optimize the perform-

ance of each well and the field continuous-ly. Intelligent-completion technology

allows controlling the completion from the

surface, eliminating the need for a

workover rig to change the downhole con-

figuration. Therefore, other completiontypes, such as multiple-tubing completions

(which can limit production because of

smaller tubing) are not needed for simulta-

neous production from several produc-

tive reservoirs.

PROJECT FIELD

The field chosen for the study is a deepwa-ter GOM field that produces oil from seven

Late Pliocene to Early Pleistocene reser-

voirs, named Z1 through Z7, from top to

bottom. Core porosities of the sand units

range from 15 to 35% and permeabilitiesfrom 10 to 2,400 md. The net-/gross-pay-

thickness ratio ranges from 0.4 to 0.95. The

structural trapping mechanism is a normal-

fault system. Hydrocarbon trapping also

occurs because of stratigraphic onlap.The original development plan entailed

drilling several highly deviated wells from a

single structure. Most wells in this field tar-

geted multiple reservoirs, some with singlecompletions that would require plugging

back and recompleting in higher reservoirs

as time progressed. Some wells were com-

pleted with dual tubing strings to permit

simultaneous production. All wells wouldrequire a workover. The operators reser-

voir-simulation model was run with this

development plan and the reservoir per-

formance analyzed. The results were used

to identify poorly drained areas (such asisolated fault compartments not produced

by any well), attic oil remaining in partial-

ly drained compartments, or areas where

the waterflood was not effective. An intelli-

gent completion would be applicable todrain multiple reservoirs simultaneously in

a controlled environment, even if the reser-

voirs are in different fault blocks in the

same reservoir or in different reservoirsseparated by shales.

Several wells were identified as candi-

dates for intelligent completion on the basis

of simulation results. The two wells chosenfor the study met the following criteria.

Intelligent completions would not beinstalled in water-injection wells.

The existing drilling schedule would be

honored, and wells were not considered if

intelligent-completion hardware could not

be obtained in time. Intelligent completions would not be

used in areas of high geologic risk.

SIMULATION MODEL

Because it was felt that the full-field modelwas too big for the purposes of this study,

the first step was to reduce its size. The sim-

ulation model provided by the operatorincluded all the reservoirs. However, the

only interaction between the upper and

lower reservoirs was through the surface

gathering system. No wells drilled to

deplete the lower reservoirs were ever com-pleted in the upper reservoirs and vice

versa. Because both of the wells selected for

possible intelligent completion had not

been completed in the lower reservoirs,these layers were eliminated from the sim-

ulation model for this study.

In addition, the east and west ends of the

original model were removed because the

two case-study wells were shielded fromthe new east and west boundaries of the

model by faults. The resulting model used

approximately 30,000 grid blocks, one-half

the number of grid blocks used in the orig-

inal model.

Intelligent Completions. A simple defini-

tion of an intelligent completion is that it is

a configuration with a valve to separate the

reservoir from the tubing. Opening thevalve reduces the pressure drop to that

required to obtain a given rate. Closing thevalve reverses the effect.

Essentially, this effect is the same as

adjusting the skin factor of the completion.

The difference is the location of the pres-sure drop. In the intelligent completion, the

pressure drop occurs after the fluid has

entered the wellbore. With the skin-factor

adjustment, the pressure drop occurs as the

fluid enters the wellbore. It was felt that thissmall difference could be ignored and that

changing the skin factor would simulatethe workings of an intelligent completion.

OPTIMIZING RESERVOIR MANAGEMENT

IN GULF OF MEXICO DEEP WATER

This article is a synopsis of paper SPE

56670, Application of Intelligent-

Completion Technology To Optimize the

Reservoir Management of a Deepwater

Gulf of Mexico FieldA Reservoir-

Simulation Case Study, by Stephen

Rester, SPE, Jacob Thomas, SPE,

Madeleine Peijs-van Hilten, SPE, and

William L. Vidrine, Halliburton Energy

Services Inc., originally presented at the

1999 SPE Annual Technical Conferenceand Exhibition, Houston, 36 October.

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The base-case response was obtained by

simulating the performance of the field

with the candidate wells initially opened in

one reservoir and, later, in a second reser-voir. The alternative response was obtained

by simulating the performance of the field

with both reservoirs open with the pressure

drop from the reservoir to the wellbore con-trolled by the skin factors of the two com-

pletions. The skin-factor values were

obtained by trial and error. First, a simula-

tion was run with given values. The rates

from the two reservoirs were studied todetermine when intervention would be

needed. Then, the skin factor for the prob-

lem reservoir was adjusted. This procedure

was repeated until the optimum production

performance was obtained.

Results. The operation of the first candi-

date, Well C1, was changed without makingany changes to the operation of the second

candidate, Well C2. Then, the operation ofWell C1 was fixed at its optimum while theoperation of Well C2 was changed.

The operation of the intelligent-comple-

tion case began with Well C1 completed in

the Z2 and Z4 reservoirs with skin factors

of zero for both completions. After a periodof commingled flow, the water cut from the

Z2 reservoir completion began to increase.

The simulation was rerun with an initial

skin factor for the Z2 reservoir equal to

zero, then it was increased when the watercut began to increase. This scheme corre-

sponded to starting with the intelligent

completion fully open, then partially clos-

ing the completion when the water cutbegan to increase. This scheme changed the

rate but not the water cut. After repeating

this procedure several times, it was deter-

mined that the optimum operation is to

shut in the Z2 reservoir completion when itbegins to water out.

The intelligent-completion operation

accelerated production from Well C1 by

shifting the production from the Z2 reser-

voir to the beginning of production. Also,the changed performance of Well C1 affect-

ed the performance of other wells in the

two targeted reservoirs, resulting in their

recovery of additional reserves.

In the original operation, Well C2 wascompleted initially in the Z3 and Z4 reser-

voirs (the Z3 and Z4 reservoirs were treat-

ed as a single reservoir) with the intention

of recompleting to the Z1 reservoir whenthe production rate fell to the economical

limit. In the 10 years represented by the

simulated production, Well C2 did not

reach the economical limit and, therefore,was never recompleted.

Operation of the intelligent-completioncase began with Well C2 completed in the

Z1, Z3, and Z4 reservoirs. After a period of

commingled flow, the water cut from the Z1

reservoir began to increase. Following the

procedure used for Well C1, the simulationwas rerun with the skin factor of the Z1

reservoir equal to zero initially, thenincreased when the water cut began to

increase. As was observed in Well C1, therate could be changed but not the water

cut. Thus, shutting off water production

was determined to be optimal.

Operation with the intelligent comple-

tion accelerated the production from WellC2 by shifting the production from the sec-

ond completion to the beginning of pro-

duction. Changing the performance of Well

C2 had little influence on the performance

of other wells in the field. Thus, the addi-

tional reserves obtained by converting WellC1 to an intelligent completion were not

lost when Well C2 was converted to an

intelligent completion.

COMPLETION OPTIONS

Because the two candidate wells target only

two reservoirs and the wellheads are on a

platform, completion options are available.First, a single selective completion can be

used to open one reservoir while closing a

second reservoir, which is analogous to a

recompletion option. Second, two reser-

voirs can be produced through separatetubing strings, which is analogous to the

intelligent completion. The differences

occur in the capital investment required

and the risks associated with completion

installation and operation. For this field, itwas found that smaller-diameter tubing

does not limit the production rate in the

dual completion. A comparison of the eco-

nomics of the four completion practiceswas made for Well C1 only. It was assumed

that the completion practices would be the

same for the second candidate.

ECONOMICS

Because only a portion of the original

model received from the operator wasextracted for use in this study, some of the

wells in the original model could not be

simulated. The production profiles for

those wells werecombined with those fromthe simulations to construct the full-field

performance. This action allows comparing

the results of the original model with the

results of this study.

The simulations were run for a period of10 years, at which time the economics were

evaluated. For each economic analysis, theoil price was held constant. Several values

of the oil price were used to determine the

sensitivity of the net present value (NPV).

Installing an intelligent completion inWell C1 increased production from the well

by 0.73% and from the field by 3.54%.

Individual-well performance is sensitive to

the performances of other wells in the field.

When Well C1 is completed with an intelli-gent completion, it produces less fluid from

the Z4 reservoir compared with the con-

ventional-completion scheme. Production

from both reservoirs in the intelligent-com-pletion case equals the production from the

Z4 reservoir alone in the base case. The Z4

reservoir is depleted slower than in the base

case, and another well initially completed

in the same zone does not invoke the auto-matic recompletion option as early as in the

base case. Therefore, the other well is still

completed in the Z4 reservoir when water

injection is initiated in that reservoir. Theimpact of water injection on that other well

causes a large increase in total production.

The incremental economic value comes

from replacing the high cost of recomple-

tion with the lower cost of a single selectivecompletion. Completing Well C1 with a

dual-string completion would have NPV

between 56 and 142% of the base-case drill-

and-complete cost of the well, depending

on the discount rate and the cost of recom-pleting the well. The improved economics

reflect the lower cost of the dual-string

completion compared with the intelligent

completion. However, a dual-string com-

pletion can consider only two reservoirs.Converting Wells C1 and C2 to intelli-

gent completions would raise the NPV of

the field by 98 to 342% of the base-case

drill-and-complete cost of Well C1,depending on the discount rate and the cost

of recompleting the well.

CONCLUSIONS

This study shows that intelligent-comple-tion technology has potential to improve

project economics in the GOM through

better reservoir-management practices. Thesimulations showed that an intelligentcompletion not only increased the ultimate

recovery from a single well, it increased the

total recovery from the reservoir as a whole.

Although the conclusions were drawn from

a simulation model, the capability to simu-late intelligent completions is still in a rudi-

mentary stage of development.

Please read the full-length paper for

additional detail, illustrations, and ref-

erences. The paper from which the

synopsis has been taken has not beenpeer reviewed.

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28 OCTOBER 1999

Permanent downhole gauge (PDG) systems

are an alternative to wireline-conveyed

downhole surveys. PDG systems avoid haz-

ardous operations and offer continuous

measurements, which enable better reser-voir management and production opti-

mization. Electrical pressure- and tempera-

ture-monitoring systems are most com-

mon. Other systems include the following. Permanent downhole flowmeters for

liquid-only mixtures.

Use of the power cable for data trans-mission in wells with electrical submersible

pumps. Fiber-optic well monitoring for meas-

uring pressure and temperature.

Cableless communication.

Surface-controlled reservoir-analysis

and -management systems.Installation of electrical gas-lift valves,

all-electrical inflow-control devices, and

reservoir-monitoring systems are planned.

Once these systems are available, the so-

called intelligent well concept, defined asa modular combination of downhole mon-

itoring and control systems, will become

reality. For all these systems, reliability is

key. Shells targets for monitoring systemsand actuators are 90% probability to sur-

vive 5 years and 10 years, respectively.

SYSTEM

Fig. 1 shows an electrical PDG system for

pressure and temperature measurement.

The sensing element is an electronic gaugemounted in a mandrel that is part of the

tubing string. The gauge is connected to the

metal-sheathed electrical cable that runs

along the tubing to the tubing hanger.The coaxial cable contains splices when

its length is insufficient or if the cable

breaks during installation. In a land or plat-

form system, the cable is fed through the

tubing hanger with compression fittings at

the top and bottom. The cable can exit the

tree through a downhole safety-valve-line

port or a flanged outlet. To provide a pres-sure barrier inside the tree, a bulkhead

splice is often made immediately outside

the tree. An instrument cable is used to

couple this connector to the surface acqui-

sition unit. In a subsea installation, a wetconnector is used between the hanger and

the tree. The wellhead outlet can be a

flanged wet connector coupled to the con-trol pod, to a control line in the umbilical,

or to an acoustic telemetry system througha diver-matable connector.

Data from the PDGs are fed into a PC

through an interface unit that can handle

several gauges. Data are transmitted to anylocation by use of a communication system,

such as a satellite link or even floppy disks.

FIELD DATA

Historical data were obtained from four

major suppliers of these systems. The data

were crosschecked with other sources,including articles in the literature and

information from operators. Data from 952

measurement systems, installed from 1987

through August 1998, were obtained.

Reports of all failed systems were collectedto determine the failing element.

ANALYSIS

The studied systems differ by their inherent

properties or by the external conditionsunder which they operate. Other factors

(such as the operator, field, well type, con-

tractor, and installation date) may influence

the failure behavior of the system. A physi-cal model explaining the influence of thesevariables on the reliability is not available.

Therefore, a nonparametric method was

used to analyze reliability. The results are

based on the observed track records of the

installed systems.

ANALYSIS RESULTS

Fig. 2 shows the number of installations for

each year, divided into subsea, platform,

and land installations. Before 1993, 30 sys-

tems were installed yearly, whereas approxi-

mately 100 systems per year were installedfrom 1993 until 1995, reaching a peak of

192 systems in 1996. After 1996, the num-

ber of installations decreased. Subsea instal-

lations account for 39% of the total; approx-imately 61% are platform installations; and

only a few are land installations.

Reliability. Every 2 to 4 years, a new gen-

eration of systems has come on the market.The reliability of each new system should

improve. Therefore, the survival probability

was calculated as a function of operational

time for six 2-year periods: 19871988,19891990, 19911992, 19931994,

19951996, and 19971998. Between 1987and 1992, substantial progress was made in

PDG-system reliability: the 5-year survival

probability improved from 40 to 75%.

However, since 1992 no further improve-ments have been observed. The result is a

5-year survival probability of 69% for the

period 19931998.

Failing Elements. PDG systems failedbecause of the downhole cable, fixed (such

as splices and the gauge-to-cable connec-tion) and matable connections, the down-

RELIABILITY ANALYSIS OF PERMANENT

DOWNHOLE MONITORING SYSTEMS

This article is a synopsis of paper OTC

10945, Reliability Analysis of Per-

manent Downhole Monitoring Sys-

tems, by S.J.C.H.M. van Gisbergen,

Shell Intl. Deepwater Services B.V.,

and A.A.H. Vandeweijer, Shell Intl.

E&P B.V., originally presented at the

1999 Offshore Technology Confer-ence, Houston, 36 May.

Fig. 1Subsea PDG system.

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hole sensor, and other failures. Fig. 3

depicts system status 1 year after installa-

tion and shows the percentage of installa-

tions still operating and the percentage thathave failed (split by failing element).

Failures of fixed and matable connectionshave declined from 59% during

19871988 to less than 7% during

19951996 and 19971998. Also, reliabili-ty of the cable has improved. However, the

number of gauge failures has shown an

increasing trend.

Current Generation. The authors arbitrar-

ily define the current generation as systems

installed during 19951998, 557 systems

for measuring pressure and temperature.

The dominant failing element is the gauge

(40%), followed by the cable (17%).Gauge Failure. Originally, PDG-system

gauges were identical to the memory gauges

used in well tests. The lifetime requirement

for well-test gauges is several months, com-

pared with 5 to 10 years for PDG systems.To improve gauge reliability, the authors rec-

ommend use of dedicated electronic circuits

and improved burn-in and vibration-test

procedures. Destructive sample testing is

recommended to verify performance.Testing should be done at actual conditions

(i.e., in the closed housing, instead of elec-

tronic boards tested in open furnaces). The

failure rate of electronic circuitry is temper-ature dependent. Most of the PDG systemsare operating at 100C or less. Use of dedi-

cated electronics and other efforts are

extending this limit to 200C.

Decreased reliability is expected withincreased temperature. As a rule of thumb,

the failure rate of electronic circuitry dou-

bles for each 8C temperature increase. A

decreasing trend of the 1-year system-sur-

vival probability of systems installed dur-ing 19951998 is a function of bottom-

hole temperature.

Cable Failure. Until 1990, all cables con-tained splices, a major source of failures.

However, splice-free cables in lengths of

more than 10 000 m are available. Also,

current cables use an Incoloy 825 sheath

rather than an American Iron and SteelInst. (AISI) 316L sheath to improve relia-

bility. Most cable-related failures occurredduring or shortly after installation. Some

cable failures occurred when the cable was

crushed by the tubing hanger while landingthe tree. These failures can be prevented by

use of a protective cap or centralizer for the

cable in the tubing section, immediately

below the tubing hanger.Tubing loads can crush the cable, espe-

cially in severe doglegs. To prevent these

failures, use of cables with bumper bars is

recommended where the load on the cable

is expected to exceed its crush resistance.Cable failures also occur when the cable

must be guided across large components in

the completion string. Use of special pro-

tectors is recommended. Another option is

to provide a recess in the component forthe cable.

Fixed-Connections Failure. Fixed con-

nections include splices and the connection

between the gauge and cable but exclude

the make-break connections, such as wet

connectors. With improved cable quality,

fewer splices are used. Also, the use of part-ly redundant metal-to-metal seals for fixed

connections has led to improvements.

Fixed connections may be a significant partof the unidentified failures. Therefore, theauthors see a need to improve the connec-

tions further and to use fully redundant

metal-to-metal seals.

Matable-Connectors Failure. Although

most matable connectors are the wet con-nectors in subsea completions, they also are

used at the wellhead outlet on platform and

land systems. Failures of these elements

often are caused by a broken seal where the

connector is attached to the cable or by an

improper electrical contact between the

cable and connector. Use of redundantmetal-to-metal seals has reduced failures.

Further improvements can be made by tak-

ing more care during installation.

Other Failures. Functional testing of the

complete PDG system after completion alsoshould be completed to ensure that the pod

interface and downhole system are per-forming to specification. Standardizing

downhole communication protocol could

result in fewer types of control cards.

CONCLUSIONS

Historically, PDG systems for measuring

pressure and temperature have exhibited

low reliability. During 19871992, substan-tial improvements were made that increased

the 5-year survival probability to 75% for

systems installed during 19911992.

However, since 1992, no further improve-

ments have been made in reliability.Needed improvements to achieve the tar-

get 5-year survival probability of 90%

include technical quality, care during instal-

lation, and management of the interface.

Financial incentives (such as making thesystem part of the well gain-share-incentive

scheme or pay-for-data schemes) could

stimulate improvements.

Improvements in reliability will berequired not only for PDG systems that

measure pressureand temperature, but also

for more complex downhole systems, such

as inflow-control devices, flowmeters, and

reservoir-monitoring devices. For all thesesystems, reliability will be a key issue in the

decision whether to install them. The

lessons learned from pressure- and temper-

ature-monitoring systems can be very use-

ful input to achieve the required high levelof reliability.

Fig. 3PDG system status (working or failed element) 1 yearafter installation.Fig. 2PDG installations by year.



erences. The paper from which the syn-

opsis has been taken has not been peer

reviewed. Copyright 1999 OffshoreTechnology Conference.

Year of Installation

Period of Installation

NumberofInstallations

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Designing a fracture-treatment schedule

that creates the desired propped length is a

challenge. For given reservoir conditions,

use of several fluid types and volumes,proppant types and concentrations, and

injection rates must be considered.

Hundreds of possible combinations exist

for modeling each treatment schedule. The

results of each run must be studied beforeinput parameters are altered for the next

run to get one step closer to the desired out-come. To reduce the complexity of

hydraulic-fracture design, an intelligenttool was developed. This tool uses virtual-

intelligence techniques, neural networks,

and genetic algorithms. Neural networks

are tools that (when trained properly) pro-

vide rapid results (output) for a particularinput. A series of neural networks were

used to replicate the functionality of a 3D

hydraulic-fracture computer model.

METHOD

To produce a desirable hydraulic-fracturedesign, neural networks were integrated

with genetic algorithms. The genetic algo-

rithm searches possible combinations of

input parameters and finds the most-desir-

able input combinations. Several neuralnetworks were trained for the design-opti-

mization process. The neural-network

model (NNM) is capable of designing treat-

ment ramp and stage schedules. Specific

rules (process constraints) can be intro-duced to prohibit unrealistic or unaccept-

able designs.

A 3D hydraulic-fracture model (HFM)

was used extensively to train the neuralnetworks. Designs developed with thismethod provide reasonable accuracy when

run in the HFM. However, fracture treat-

ments designed with the NNM require no

specific expertise in hydraulic-fracturedesign. The NNM provides a starting point

that is very close to the optimum design. As

shown in Fig. 1, the engineer provides

reservoir characteristics and the desired

fracture geometry as input. The NNM out-

put consist of fluid and proppant character-istics as well as a detailed treatment sched-

ule including the number of stages, amount

of fluid and proppant, and the pump rate.

RESULTS AND DISCUSSION

The full-length paper details two fieldexamples. In these examples, a successful

job designed by an expert engineer was

modeled with the HFM. The issue was

whether the NNM could design fracturetreatments comparable with those designed

by an expert. The NNM was provided with

reservoir characteristics and the target frac-

ture length (the same fracture lengthreached with the experts design).

The first design was a hydraulic fracture

pumped in a Redfork formation. The NNM

provided several potential designs that were

entered into the HFM, thus, giving the

engineer a choice in selecting the mostappropriate design. The process generated

four near-optimum designs having fracture

lengths within 3% of the desired value.

However, the proppant concentrations inthe fractures are different, a good starting

point for experts or those with little or no

experience with sophisticated 3D computermodels. The NNM is not a substitute for

high-performance computer models but

can be a useful companion to complement

such software and make them useful to

petroleum professionals who are not

experts in hydraulic-fracture design.The second example tested the NNM

against a fracture designed by another

expert in the Teapot formation of the Kaye

field. The original successful design had

eight stages. Modeling the original designwith the HFM, the fracture length and con-

ductivity were determined. The NNM pro-

vided four fracture designs, three with nine

stages and the fourth with seven stages. All

designs generated by the NNM are compa-rable with the original design by the expert.

The next step in developing the NNM

includes addition of two modules. The first

is a set of virtual-intelligence routines toreduce the need for detailed reservoir char-

acteristics that might be difficult to acquire.The user can provide a suite of wireline logs

(such as gamma ray, density, and resistivity)

and let the model generate reservoir char-acteristics. The second module is an eco-

nomic module to aid selection of the most

economical design from those provided by

the NNM.

INTELLIGENT SYSTEMS TO DESIGN

OPTIMUM FRACTURE TREATMENTS


57433, Intelligent Systems Can Design

Optimum Fracturing Jobs, by Shahab

Mohaghegh, Andrei Popa, and Sam

Ameri, West Virginia U., scheduled for

presentation at the 1999 SPE Eastern

Regional Meeting, Charleston, WestVirginia, 2122 October.

Fig. 1Data-flow schematic of the NNM.





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The goal of a European Drilling Engineers

Assn. joint-industry project is to integrate

an electric motor into a smart closed-loop

drilling system. It is believed that, on thebasis of feedback from near-bit sensors,

such a system could adjust drilling parame-

ters automatically to optimize drilling per-

formance. In most coiled-tubing-drilling

(CTD) services, downhole power is frompositive-displacement motors (PDMs). The

output profile of these motors is well suitedto the drilling environment, providing high

torque at low rotational speeds. However,short run life, poor performance in high-

temperature operations, and a limited

choice of drilling media restrict the effec-

tiveness of PDMs in many areas where an

electric motor offers an efficient and reli-able alternative.

Electric motors have been used success-

fully for horizontal-well drilling in the for-

mer Soviet Union. However, more-recent

attempts to integrate electric motors into arotary-drilling assembly have not succeed-

ed, mainly because of the difficulties of pro-

viding a high-capacity electrical link to the

downhole drilling assembly.Advances in artificial-lift technology

have enabled a new type of electrical-sub-

mersible-pump (ESP) installation on CT.

In these innovative completions, a high-

capacity power cable is installed inside theCT to isolate and protect the cable from the

downhole environment. This concept was

transferred to CTD, and the joint-industry

project was formed to produce a cost-effec-

tive electrical-CTD (ECTD) prototype. By

use of only existing technology, an ESP

motor was combined with a planetarygearbox and an electromechanical CT con-

nector. The motor was controlled from the

surface with a laptop computer connected

to a variable-speed-drive unit. A com-

mand/control software package was devel-oped that interrogated the drive to acquire

and record real-time drilling data from

the motor.

ECTDPhase 1 demonstrated fundamental benefits

of ECTD by providing superior feedback

from and control of drilling processes inreal time. The power output per unit length

of the Phase 2 motor is comparable to

PDMs, while longevity increases of one

order of magnitude are expected.

Drive Power. The electric downhole

motor (EDM) is controlled directly by the

operator as commands are sent through

the surface gear and computer, whereas a

PDM is controlled indirectly by variationsin the mud flow. The electric motor allows

complete direct control of the motor. Speed

may be increased or decreased with a joy-

stick or set with a keyboard instruction.

Motor stall may be avoided almost entirelyby setting current limits in conjunction

with weight-on-bit limits. As the motor

approaches stall condition, a feedback loop

to the CT unit reduces the weight on bit

automatically to obtain an acceptable cur-rent level. Thus, the system may be set to

optimize the rate of penetration (ROP)

without danger of overpowering the bot-

tomhole assembly (BHA).Hydraulic power is required only for

cooling and cuttings removal. This system

provides control of the drilling process

while allowing circulation flexibility, which

could be of high value when passing sensi-tive or weak formations.

Energized Fluids. The BHA is insensitive

to aerated or energized drilling media. Air

drilling may be considered with the electric

motor. A large range of underbalanced-

drilling techniques may be used, some of

which would reduce the performance ofconventional CTD motors.

High Temperature. The Phase 2 electric

motor was designed to operate at tempera-

tures up to 450F, making the motor suit-

able for high-temperature work where aPDM would have an extremely short life

span. Vane-type motors also have been pro-

posed as an alternative.

Feedback and Control. Continuous feed-back on hole condition, torque, weight on

bit, and lithology changes enables makingbetter drilling decisions that reduce hole

problems, speed up the drilling process,

and allow timely trajectory alterations toensure reaching geological targets. Bit-con-

dition and performance-drop-off indicators

from the electric motor may also enable

optimal timing for routine trips, such as bit-

change-out runs.

Scalable Motor. The electric motor has

been designed in 3.3-ft modular lengths

that may be combined to increase torque

and power output. Besides its drilling func-tion, the motor package provides a source

of electrical and mechanical power for aux-

iliary BHA functions, such as active trac-

tion and orientation tools and new devel-

opments in formation-evaluation and -test-ing equipment.

Real-Time Data Transmission. The

power line also provides a high-quality

telemetry link with the EDM and downholesensors. Real-time feedback from the BHA

enables precise control of the EDM. In

Phase 2 of the project, pressure, tempera-

ture, and weight-on-bit sensors are includ-ed in the BHA. Phase 3 will expand capa-bilities to include full directional drilling,

with an option to gather gamma ray and

correlation-resistivity data. Because high-

bandwidth communication is available

through the power cable, logging-while-drilling tools also could be incorporated

into the BHA.

Motor Longevity. The motor was designed

with a conservative target life span of more

than 1,000 hours (drilling in ambient mud

temperatures of approximately 150F). Onthe basis of preliminary results from the

ELECTRICAL COILED-TUBING DRILLING:

A SMARTER DRILLING SYSTEM

This article is a synopsis of paper

SPE 52791, Electric Coiled-Tubing

Drilling: A Smarter CT-Drilling

System, by D.R. Turner, SPE, XL

Technology Ltd.; T.W.R. Harris, SPE,

Shell Expro U.K. Ltd.; M. Slater, SPE,

Amoco Corp. E&P Technology; M.A.

Yuratich, SPE, TSL Technology Ltd.;

and P.F. Head, SPE, XL Technology

Ltd., originally presented at the 1999

SPE/IADC Drilling Conference,Amsterdam, 911 March.

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Phase 2 motor design, the life span could

increase to between 2,000 and 5,000 hours,

depending on the service environment.

Vibration. Unlike a PDM, the motor shaft

driving the bit is centered and dynamically

balanced to reduce vibration and increase

the longevity of the BHA, especially the bitand sensitive electronic instrumentation.Sensitive measurements, such as nuclear

magnetic resonance and gyros, could be

moved nearer to the drilling face.

Reversible Rotation. With suitable

(locked) connections, the EDM provides a

simple means of reversing the direction of

rotation. As Fig. 1 shows, reversal of BHA

direction could help to push the BHA

back up the hole in a sticking environment.Reversible rotation also could be advanta-

geous in sensitive cutting operations, suchas milling out casing shoes.

ECTD DEVELOPMENT

The joint-industry project was split into

three phases to reduce the overall risk

exposure. The objective of Phase 1 was to

prove the concept of ECTD. Existing com-

ponents were used wherever possible,including an ESP motor section to provide

downhole power. The motor was shrouded

to allow mud flow past the motor.

Phase 2 developed a fit-for-purpose

drilling motor. A 31/8-in.-outside-diameter(OD), hollow-shaft, brushless direct-cur-

rent motor was designed. The total length

of the BHA is 15.3 ft, with a motor length

of 7.2 ft. The EDM operates without a gear-

box in the 0- to 1,000-rev/min range with apeak power output of 28 hp at 500 rev/min

and a stall torque of 290 lbf-ft. Currently,

the EDM is undergoing tests to evaluate

the longevity and effectiveness. Fig. 2

shows the equipment setup used for allthree phases.

Phase 3 will produce an all-electric BHA

with electronically controlled directional-

drilling capabilities. Phase 3 adds gammaray, inclination, azimuth, and tool-facemeasurements to provide vital directional

and lithological information. A 31/8-in.-OD,

electronically controlled, dynamically

steerable system will provide orientation

and bend ahead of the motor for full direc-tional-drilling functions. A feedback loop

will be added between the surface con-

troller (the software command/control

functions) and the CTD unit. While this

represents a tentative step toward closed-loop drilling, it is intended that the intelli-

gent BHA will be able to react to changes inweight-on-bit measurements by controlling

the rate at which the CT unit injects tubinginto the well.

Initially, the system would optimize ROP,

though the implications of integration of

more-sophisticated geosteering feedback are

clear. Further developments should enable

the all-electric BHA to follow a predeter-mined course to locate geological targets

with small continuous changes in direction.

This method will ensure that the borehole

remains smooth and stable to minimize thechances of drilling a dogleg and having to

deal with its associated problems.

Further integration of formation-evalua-tion tools will provide a state-of-the-art intel-

ligent-drilling assembly. Initially, this devel-opment will be controlled by the operator

through surface software. Additional down-

hole sensors will enable an automatically

secured geological target, constant progress

review by the BHA to maximize ROP, andadjustment of drilling performance to main-

tain optimal hole condition.

OCTOBER 1999 33






Fig. 2Equipment schematic for testing the ECTD system.

Fig. 1Rotation effect on the passive-traction tool.

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34 OCTOBER 1999


Arco Alaska Inc. developed the West Sak

field on the North Slope with several new

technologies implemented with respect to

the control system and operations. Oneinvolved the use of an expert-system soft-

ware package to manage wells equipped

with electrical submersible pumps (ESPs).

The development plan included significant

automation of field drillpads and field oper-ations without increasing staff. Therefore, a

software tool was chosen, in addition to thebasic capability of a supervisory-control

and data-acquisition (SCADA) system, toanalyze and advise of abnormal situations

arising at individual wells. This application

uses first principles to operate producing

wells within design constraints of the

downhole equipment.

PROBLEM DEFINITION

Generally, production management has not

been treated as a real-time function.

Significant reductions of operating cost and

increased well productivity can be realizedthrough the use of intelligent systems that

combine real-time wellhead-sensor infor-

mation with knowledge of well characteris-

tics and production operations from people.

To reduce operating costs, this technologyaddresses increasing the well on-production

time and optimizing deliverability. The

SCADA system provides rapid data acquisi-

tion. Analysis tools are used that contain

elements of artificial intelligence to captureand apply practical knowledge and assist in

the management of field assets.

OBJECT-ORIENTED

PROGRAMMING

Traditional software platforms requiretranslation from knowledge held by the

end user of the softwarein this case, pro-

duction-technology expertsto the soft-

ware programmer. The object-oriented-

programming environment reduces thedevelopment time required to build the

application by enabling people with the

production-technology background to

build the application directly. With object-oriented software, characteristics of the

wells and drillpads are represented by an

object. Software operations act with theobjects to produce graphical displays that

represent the behavior being modeled.Each well object contains well-information

attributes. Instructions to drill and analyze

well performance start with the well object,

which is used generically. When expanding

the application for multiple wells, theproperties of the well object are inherited

each time a well is cloned.

ANALYZING WELL PERFORMANCE

An ESP system can be analyzed on the basis

of a single-point stabilized test where thepump-intake pressure and annulus-gas-

production rate are known. The results are

tubing flow performance, estimated pump-

discharge pressure, suction-to-discharge

pump performance, and a well-inflow-capability curve for a single point at the

top-of-perforations depth for the tubing-

head pressure during the test.

By applying known characteristics for the

producing zone, the well-inflow capabilityat the top-of-perforations depth can be

established for producing pressures ranging

between static reservoir pressure and zero.

Pressure-traverse procedures can be appliedto transpose the well-inflow characteristics

to the pump-intake depth, establishing the

well capability at pump-intake depth. Data

provided by the pump manufacturer are

overlaid on the pump-intake-depth well-capability data to provide a benchmark data

set of operating constraints.

RULES

Natural-language rules are used for generic

control of the behavior of the objects repre-

sented graphically. Variable interaction and

knowledge embedded in the rules make theapplication unique. The rules provide intel-

ligent analysis of situations that can be rec-

ognized according to sensor-data trends.

OPTIMIZATION STRATEGY

This application addresses the following

elements as criteria to accomplish the

desired result. These elements are solved in

the order presented.

1. Apply intelligent alarming diagnosticinformation in real time to infer downhole

conditions to determine when a well is introuble.

2. Operate within the design constraints.

3. Optimize field performance.A real-time on-line inventory of available

process-system capacities also can be main-

tained. Real-time on-line decisions can be

made to ramp up or ramp down indi-vidual wells to maximize the economical

benefit within the available processing-sys-

tem-capacity constraints.

A primary control-room operator re-

ceives the alarms and advice generated bythe application. While the operations staff

monitors production, surveillance engi-

neers can view historical performance

curves and production engineers can use

the application to test a pump configura-tion with well test data sets.

APPLIC ATION BENEFITS

Expert technology can solve complex oper-

ational and information-delivery problems

to lengthen equipment life, increase pro-duction, and reduce downtime. Knowledge

is captured and consistency established

throughout the facilities to reduce operat-

ing costs by reducing equipment failures.Production is increased by operating thedownhole equipment within design limits.

Continuous surveillance is achieved,

and production is accelerated by optimiz-

ing asset use and minimizing overall oper-

ating costs.

MANAGEMENT OF WELL PRODUCTION

WITH REAL-TIME EXPERT SYSTEMS


54635, Management of Well Pro-

duction Using Real-Time Expert-

Systems Technology, by Dan McLean,

SPE, Kenonic Controls Ltd., Jim

Wilcoxson, Arco Alaska Inc., and

Roger Clay,Arco E&P Technology, orig-

inally presented at the 1999 SPE

Western Regional Meeting, Anchorage,2628 May.





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36 OCTOBER 1999


Real-time monitoring of the bottomhole-

assembly (BHA) and drill-bit dynamicbehavior is critical to improving drilling

efficiency. It allows the driller to avoid

detrimental drillstring vibrations and main-

tain optimum drilling conditions through

periodic adjustments to various surfacecontrol parameters. However, selecting the

correct control parameters is not a trivial

task and several correction attempts may be

required. Therefore, development of effi-

cient methods to predict the dynamicbehavior of the BHA and methods to select

the appropriate control parameters is

important for drilling optimization.

A revolutionary step in the drillingdynamics field occurred with the develop-

ment of smart downhole-vibration meas-

urement-while-drilling (MWD) tools. A

multisensor downhole MWD tool acquires

and processes dynamic measurements andgenerates diagnostic parameters that quan-

tify the vibration-related drilling dysfunc-

tions. These diagnostics then are transmit-

ted to the surface in real time with MWDtelemetry. The transmitted information is

presented to the driller in a simple form

(e.g., as green, yellow, and red traffic lights

or color bars) on a display on the rig floor.Basic recommendations for possible cor-

rective actions also are presented alongside

the transmitted diagnostics. On the basis of

this information and by use of his own

experience, the driller can modify the rele-vant control parameters (such as hook

load, drillstring rotary speed, and mud

flow rate) to avoid or resolve a drilling

problem. This process may require several

iterations before the desired drilling modeis achieved, and, even then, the result may

not be optimized.

Advanced MWD dynamics tools and the

closed-loop vibration-control concept needa more reliable method of generating the

corrective advice presented to the driller.One modeling technique being investigated

is a neural-network (NN) -based method

that can be used to develop a real-world on-line adviser for the driller in the closed-loop

drilling-control system.

NN FUNDAMENTALS

The first conceptual elements of NNs were

introduced in the mid-1940s, and the con-

cept developed gradually until the 1970s.

The most significant steps in developing

the robust theoretical aspects of this new

method were made during the explosion incomputer technology and use of artificial

intelligence. More recently, interest has

been generated in applying NNs in controlsystems. These systems have proved reli-

able in situations with complex, nonlinear,

and uncertain parameters. Properties that

make NNs suitable for intelligent controlapplications include the following.

Learning by experience (human-like

learning behavior).

Ability to generalize (map similar

inputs to similar outputs). Parallel distributed processing.

Robust in the presence of noise.

Multivariable capabilities.

The basic processing element of NNs is

called a neuron. As shown in Fig. 1a, eachneuron has multiple inputs and a singleoutput. Each time, n, a neuron is supplied

with an input, p, it computes output, a, on

the basis of an activation function, ; a

weight, w; and a bias, b. Fig. 1c shows twoactivation functions.

Two or more neurons may be combinedin a layer (Fig. 1b). A layer may have a dif-

ferent number of inputs and neurons. A

network can have several layers. Each layer

has a weight matrix, a bias, and an output.The output from each intermediate layer

becomes the input for the following layer. A

layer that produces the network output is

an output layer. All others are hidden lay-

ers. Thus, the network shown in Fig. 2 hasone output layer and two hidden layers.

Once a topology and activation functionare defined, training procedures are

NEURAL NETWORKS FOR PREDICTIVE

CONTROL OF DRILLING DYNAMICS


56442, Application of Neural

Networks for Predictive Control in

Drilling Dynamics, by D. Dashevskiy,

U. of Houston, and V. Dubinsky, SPE,

and J.D. Macpherson, SPE, Baker

Hughes Inteq, originally presented at

the 1999 SPE Annual Technical

Conference and Exhibition, Houston,36 October.

Fig. 1NN basics: a. neuron components; b. neurons combinedinto layer; c. activation functions examples.

Fig. 2Multilayer NN used to simulate a dynamic system(TDL = tapped delay line).

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applied. In supervised learning, a set of

input data and correct output data (targets)

is used to train the network. The network,

by use of the training input, produces itsown output. This output is compared with

the targets, and the differences are used to

modify the weights and biases. The proce-

dure for modifying the weights and biasesof a network is called learning rules.

A test set (inputs and targets not used in

training the network) is used to verify the

quality of the NN and how well it can gen-

eralize. Generalization is an attribute of anetwork whose output for a new input vec-

tor tends to be close to the output generat-

ed for similar input vectors in its

training set.

CONTROLLED DYNAMIC SYSTEM

To simulate and control the dynamic

behavior of a drilling system with an NN,the structure of the system and its relation-

ship with the outside world must be for-

malized (Fig. 3). The surface and down-hole equipment is represented by the

object rig, and the following parameters

influence its performance.

Control parameters are those that the

driller can control interactively to affect rigoutput. These parameters include hook

load, weight on bit (WOB), rotary speed,

and mud flow rate and properties.

Plant characteristics are those that relate

directly to the drilling equipment, such asgeometric and mechanical parameters of

the BHA, characteristics of the drill bit and

downhole motor, and other technical para-

meters of the drilling rig and its components. Media parameters are those that affect

rig performance but whose values are

either unknown or only known to a certain

degree while drilling. These parameters

include formation lithology, mechanicalproperties of the formation, wellbore

geometry, and well profile.

Because the goal is to drill efficiently, rig

output defines only those parameters used

for control, namely rate of penetration(ROP), drillstring and BHA vibration,

WOB, and rotary speed.

Values of some of these parameters are

available in real time at the surface.

However, an MWD tool is required toobtain values of other parameters, a serious

limitation in the control process. The limit-

ed bandwidth of MWD mud-pulse teleme-

try results in an excessive delay in trans-mitting raw data to the surface. The down-

hole analyzer can identify each drilling phe-

nomenon and quantify its severity. The vol-

ume of data sent to the surface is reducedsignificantly and provides the driller with

condensed information about the most-

critical downhole dynamic dysfunctions.The combination of the key components of

the system is referred to as the plant.

SIMULATED RESPONSES

VS . REAL DATA

Because the amount of data used to train

the model was limited, the model was not

trained adequately for all possible combina-tions of input parameters. Therefore, when

parameter values fell outside the training

range, attempts to simulate system behav-

ior produced unsatisfactory results.

However, the results were sometimes quitemeaningful because a strong correlation

exists between the values of some down-

hole parameters (e.g., an increase in WOB

causes an increase in torque on the bit).

Good overall agreement was observedbetween real data and those simulated by

the NN model for ROP and for diagnosis of

whirl and bending moment. In most cases,

the simulation error was less than 50%.Interesting results were produced when

an automated optimizer was used. When a

severe whirl dysfunction and a moderate

bending dysfunction were entered, approx-

imately 15 to 20 time steps (5 to 6 min-utes) were required to stabilize the plant.

The corrective action requires approxi-

mately 10 of these time steps (3 minutes)

to cure the dysfunction and to bring the

system into the green zone. The drillstringrotary speed was reduced from 80 to 35 to

25 rev/min, as the WOB was reduced from

8,000 to 2,000 lbm. Two minutes later, the

WOB was increased gradually to 11,000lbm and the rotary speed was raised to 60

rev/min. By reducing the dynamic dysfunc-

tions, the ROP increased by 600%. When a

severe stick/slip dysfunction was intro-duced, the simulator recommended

increasing rotary speed while decreasing

WOB, then bringing the values of the con-trol parameters to new levels.

These and other simulated scenarios

demonstrated that the corrective actions

suggested by the simulator could optimize

the system in an efficient manner. Theseactions are in good agreement with com-

mon empirical steps used to resolve similar

drilling problems.

CONCLUSIONS

The NN simulator, with its predictive and

optimization capabilities, is a natural step

to improve a drilling-dynamics simulator.The power of NNs allowed a more accurate

simulation of the nonlinear drilling system

through observation of its dynamic behav-

ior. However, the following serious limita-

tions were encountered. A very limited amount of data was used

for training the model.

Data points were very localized and

provided an uneven distribution.

Several important parameters, such asmud properties, were not used for model

construction.

No deviated-well data were available.

No supplemental formation-evaluationMWD data were used in the simulation.

Overcoming these limitations should

help improve the models accuracy signifi-

cantly. In addition, experimental validation

of the modeling, prediction, and optimiza-tion capabilities of the simulator in the field

is crucial for its future application.

OCTOBER 1999 37






Fig. 3Plant definition and data flow chart.

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38 OCTOBER 1999


The lift-gas-injection rate correlates to the

oil-production rate. State-of-the-art elec-

tronic flow controllers are used to improve

the efficiency of the injection process.Traditional methods of controlling gas

injection use a fixed orifice or a gas-flow

regulator. Where the lift-gas-supply pres-

sure is reasonably stable, a simple choke

will suffice for gas control. When certainconditions exist, such as the presence of

hydrates or cool ambient temperatures,freezing may occur at the injection choke

and cause a reduction or complete blockageof injection. Where the lift-gas-supply pres-

sure fluctuates, a gas-flow regulator often is

placed upstream of the choke to inject gas

at a constant volume.

In a stable situation, the optimum ratewould remain constant; however, stability

is rare. Reservoir changes, injection pres-

sure, total gas available for injection, and

water production are dynamic variables

that affect overall production. With an elec-tronic controller, each of these variables can

be accounted for on a real-time basis and

adjustments can be made to the system to

yield optimum production.Electronic gas-lift controllers have

proved to be effective in maintaining the

production from constant-rate wells on a

controller-by-controller basis. Individual

controllers can be linked directly (hardwired) or remotely through radio, modem,

or microwave communication. Once

linked, data can be exchanged through a

supervisory-control-and-data-acquisition

(SCADA) system, which, in turn, can pass

data to a field-modeling program that per-forms complete gas-lift-system analysis.

Although the field-modeling program pro-

vides a more-in-depth field overview, use ofthe controller on a well-by-well basis can

optimize individual-well production if an

unlimited supply of lift gas exists. Because

an unlimited supply is unlikely, each con-

troller can be configured to restrict theamount of injection gas available to

each well.

Traditionally, the optimum gas-injection

rate is the flow rate that yields the maxi-

mum oil production. Now, it is recognizedthat a unique point exists on a gas-lift-per-

formance curve where the cost of the addi-

tional injection gas is greater than the addi-

tional profit realized from the increased oilproduction. This point is now considered by

most to be the optimum gas-injection rate.

Although the curve is generated by a step-

rate well test, determination of the optimum

point requires an economic analysis.

MULTIWELL INSTALLATION

On many offshore multiwell production

platforms, local compressors supply theinjection gas and the capacity is sufficient

to produce all the wells at their optimum

rates. When compressors are out of service

for repair or maintenance, the capacity

often becomes insufficient. In these circum-stances, it is important to have accurate

production-test data on each well to enable

proper injection-gas allocation.

This automated continuous-gas-lift con-

trol system has an electronic gas-lift con-troller that monitors injection-gas flow rate

and controls an automated choke. Each

wells gas-lift control algorithm is dynamic

and based on that wells performance. Oil-production-rate data are plotted as a func-

tion of gas-injection rate to generate the

gas-lift-performance curve. The controller

uses this data in its control logic to ensure

that each well receives its optimum injec-tion rate.

The systems primary objective is to con-

trol the injection gas to each well to opti-

mize the gas-injection rate. The rates are

held constant, even when the supply pres-sure varies. An economic analysis can use

the wells production-performance curve to

determine the optimum injection rate. Byuse of the compressor-output data to deter-

mine the total amount of injection gas

available, the controller can be configuredto optimize gas injection for each well.

Unlike a simple regulator, should the

injection gas become limited, the controller

can be configured to inject less gas to the

less productive wells but continue to injectthe optimum amount to the stronger pro-

ducers. As injection gas becomes limited,

the lift-gas-supply pressure will decrease

and, therefore, the total available gas-injec-tion rate also decreases.

APPLIC ATIONS

One of the benefits of electronic gas-lift

controllers is their capability to properly

use available lift gas in situations where all

necessary or desired gas is unavailable for

lifting purposes. Fields with limited gassupplies must be monitored to ensure lift

gas is properly allocated by gas injection to

wells that yield a higher production rate.

Proper allocation in a field where supply

pressures fluctuate becomes very difficult.These pressure fluctuations can be caused

by compressor-output problems, check-

valve failure, and system-back-pressure

fluctuations. Recent installations of elec-tronic gas-lift controllers have demonstrat-

ed that controlling the injection, regardless

of the pressure fluctuations, yields an over-

all field-production increase.

FUTURE PLANS

Design development and prototype testingare in progress to incorporate an optimizing

routine within the electronic gas-lift-injec-

tion controller. Performance curves gener-ated for each well could be transferred to amathematical equation by use of a curve-fit

routine. The controller then could be pro-

grammed to find solutions for gas-injec-

tion-rate allocations that would yield the

highest oil recovery. The primary improve-ment would be for the controller to opti-

mize allocation decisions.

AUTOMATED CONTINUOUS-

GAS-LIFT CONTROL


52123, New Automated Continuous-

Gas-Lift Control System Improves Op-

erational Efficiency, by Terry Bergeron

and Andrew Cooksey, Halliburton

Energy Services Inc., and J. Scott

Reppel, Texaco E&P, originally present-

ed at the 1999 SPE Mid-continent

Operations Symposium, Oklahoma City,Oklahoma, 2831 March.





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Technological advances in the oil and gas

E&P industry have improved the efficiency

of the processes required to search and pro-duce hydrocarbons. E&P companies can

apply these advances in reservoir-manage-

ment techniques and system technologies

to create intelligent, self-sufficient systems

for exploring and producing hydrocarbons.These intelligent systems provide precise

access to hydrocarbons, enhanced reservoirproduction over the asset life, and control

of produced-fluids processes to improve oilrecovery, decrease the number of unsched-

uled interventions, and minimize the envi-

ronmental impact.

Process inefficiencies can have a signifi-

cant impact on project costs, up to 30% ofthe overall costs for producing hydrocar-

bons. The need to optimize the processes

used to search and produce hydrocarbons

has driven the development and deploy-

ment of new technologies in the oil field.These new technologies should improve

access to hydrocarbons, decrease the num-

ber of wells drilled, optimize reservoir pro-

duction, improve produced-fluids process-

ing, and integrate data management foraccess to and updating of reservoir and pro-

duction information.

The use and integration of new tech-

nologies for optimized reservoir manage-ment and improved hydrocarbon recovery

will create more productive wellbores, in

less time, with fewer environmental risks.

Intelligent-system technology includes 4D-

seismic surveys, closed-loop drilling, intel-

ligent completions, downhole oil/waterseparation (DOWS), reservoir modeling,

and knowledge-management technology.

The petroleum industry relies on new tech-

nologies and processes to reduce hydrocar-bon-exploration costs.

TECHNOLOGY REQUIREMENTS

Optimization of hydrocarbon production

depends on sensor and material technolo-gies and new power-generation and fiber-

optic systems. Sensor technology for moni-

toring the parameters inside and outside the

well is critical for optimizing and under-

standing the exploration processes. Sensortechnology provides on-demand access to

the information needed to achieve hydrocar-bon-production and cost goals. Material

technology also is playing a critical role infulfilling exploration requirements.

Composite materials are entering the oil field

in areas such as coiled-tubing and drillable

completion tools. Deformable-pipe technol-

ogy will affect many sectors, includingdownhole multilateral junctions where pre-

fabricated joints with high-pressure integrity

can be built and deployed in the wellbore.

New power-generation systems, such as

fuel cells and fuel reformers, may allow elec-tricity generation at the wellsite from oil and

gas. New microgeneration plants could

improve industry economics in such areas

as heavy-oil production and processing.Fiber-optic cable and sensor technology will

improve the reliability of downhole systems

and the ability to place sensors in the well-

bore. Distributed sensors, embedded inside

the fiber-optic cable, will allow monitoringthe entire well instead of a specific zone.

Power from light can change the way ener-

gy is delivered to systems in the oil field.

WELLBORE CONSTRUCTION

New ways of extracting hydrocarbons are

vital to achieve breakthroughs in oilfieldeconomics in the new decade. The first step

is to design and build the main wellbore

and associated laterals that will comple-

ment the production systems. As these

wellbores are built, simultaneous advancedformation evaluations will be conducted

and the information gathered from these

evaluations will be integrated into reservoir

modeling programs, creating virtual pic-

tures of target reservoirs.Extended-reach-drilling, seismic-while-

drilling, smart-drill-bit, underbalanced-

PRODUCTION AND RESERVOIR

MANAGEMENT APPLICATIONSPaulo Tubel, SPE, Weatherford-SubTech Intelligent Systems

This paper (SPE 58956) is taken from

an original manuscript, Production and

Reservoir-Management Applications

Using Intelligent Systems, submitted at

the invitation of the Journal of

Petroleum Technology. This paper hasnot been peer reviewed.

Fig. 1Surface-system layout for UBD operation.

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drilling (UBD), geosteering, and coiled-tub-

ing-drilling technologies are improving

drilling efficiency, reducing the cost of

drilling, and minimizing the total number ofwells being drilled in fields. In this new

form of well construction, communication

and information management have new and

larger roles. Instrumentation is added to thedrilling equipment and then to the wellbore

to make the system intelligent. This sys-

tem can acquire and process more informa-

tion faster than conventional methods.

A key technology for wellbore construc-tion is UBD operations, which reduce dam-

age to the formations during drilling

(Fig. 1). With UBD, the bottomhole pres-

sure is designed to be less than the pressure

in the formation being drilled. This under-

balanced condition is achieved by loweringthe density of the drilling fluid by injecting

gas, such as nitrogen, into the system.Advantages of this technology include pre-

venting lost-circulation problems, minimiz-

ing damage to pay zones, increasing pene-tration rates, extending bit life, decreasing

mud loss, and enabling production

while drilling.

Most UBD operations have been onshoreapplications in the U.S. and Canada.

Concerns about safety, logistics, and equip-

ment have restricted the use of UBD off-

shore. However, new techniques and equip-

ment are being developed for offshore usein deep and ultradeep water.

PRODUCTION OPTIMIZATION

Production optimization requires down-

hole systems that enable maximum hydro-

carbon recovery with minimal interventionto maintain production at its maximum

level. Development of multilateral wells has

heightened the need for monitoring and

control of production parameters for each

lateral zone inside the wellbore. Remotecontrol of the pressure at each lateral

enables simultaneous production from

multiple zones within a single main bore.

The result is maximized rate of return onthe investment.

Fig. 2 shows an intelligent-completion

system (ICS) that is capable of controlling

the position, the state of the tools, and the

flow of fluids in wellbores. Normally, the sys-

tem is composed of surface control hardwareand downhole modules that permit the

operator to monitor and control, from a sin-

gle location, the activities of different zones

in a number of wells in real time. To fulfill

the needs in different areas of the world, ser-vice companies are developing two versions

of intelligent downhole completions: fullyelectric and hydraulic-actuated systems.

Frequently, water is produced with oil

and gas and, as the field matures, more

water than hydrocarbons is produced, caus-ing a negative impact on operations and a

reduction in the life of a field. The main

purpose of DOWS technology is to separate

water from oil downhole inside the well-

bore and leave the water in the ground.

IN-SITU POWER GENERATION

An emerging technology for processing

hydrocarbons at the wellsite is developing

rapidly. Converting gas and oil into elec-

tricity on location and connecting that elec-tricity to the local power grids may change

the way energy is processed and transport-

ed. Simple, efficient, and reliable fuel-to-

electricity-conversion technologies are

available. Promising technologies includefuel reformers, turbines, and fuel cells.

RESERVOIR MONITORING

New technology has improved the accura-

cy, resolution, and speed of data acquired

for the reservoir-monitoring process. Time-lapsed 3D-seismic surveys are used to

model water movement in the wellbore

during production, which enables a better

understanding of water encroachment intothe hydrocarbon-producing zones and

should help optimize hydrocarbon produc-

tion and achieve higher recovery.

Emerging seismic-sensor technology

will enable permanent placement ofsources and receivers inside the wellbore,

which will allow 4D-seismic surveys on

demand. Permanent placement of the

receivers in the wellbore will eliminate

position uncertainty of conventionalretrievable receivers and will generate data

with higher resolution and a better sig-

OCTOBER 1999 41


Fig. 2Technologies under development to optimize reservoir management and improveoil recovery.

8/22/2019 JPT1999_10_IS

14/14

nal/noise ratio than is achieved with sur-

face seismic surveys.

LEVERAGING FROM OTHER

INDUSTRIES

Robots are used in space exploration. The

same technology used to survey Mars may

be used in the oil industry. Permanentlydeployed learning systems will be capableof investigating, repairing, or replacing

equipment in the wellbore. Learning-

behavior machines will allow the operator

to retrieve information continuously, which

enables evaluation of reservoir and wellboreconditions. Advanced software techniques,

such as neural networks and fuzzy logic,

will provide the decision-making process

and autonomy required for these new

machines to operate inside the wellbore.Fiber-optic-based instrumentation is

moving from the telecommunications and

medical industries to the oil field. This new

technology can bring major changes in the

way data acquisition and processing, as

well as downhole-tool control, are per-formed. The functional properties of fiber-

optic sensors include remote operation,

immunity to electromagnetic interference,

use in high-temperature and -pressure envi-

ronments, small size, long-term reliability,and the capability of responding to a wide

variety of measurements. Real-time on-line

measurement and monitoring of key bore-

hole parameters are important to optimizedownhole production. Fiber-optic technol-

ogy can achieve improvements over electri-

cal-based systems in the areas of capability,

cost-effectiveness, and reliability. These

improvements can lead to reduction ofdevelopment and operating costs and to

increased hydrocarbon recovery.

CONCLUSIONIntelligent systems can improve operations

and optimize the processes used both

downhole and at the surface. Technology ischanging the way oil E&P is achieved, from

floating production, storage, and offloading

vessels, to fewer platforms for production

because of multiphase pumping, multilat-

eral drilling, and improved ICS.Integration of new sensor, hardware, and

communication technologies with existing

tools will be critical for complete systems

and successful introduction of new prod-

ucts. To optimize the E&P processes, sys-tems such as seismic, drilling, completions,

production, hydrocarbon processing, and

artificial lift should be integrated to provide

entire packages that will achieve productiongoals. Hardware and software standards are

needed for applications from drilling to

enhanced recovery. Plug-and-play systems

with an open architecture for hardware and

software will provide proper and timelyintroduction of systems and technologies in

the field without redesigning the host sys-

tem for each sensor upgrade. The ability to

review, use, modify, and integrate historical

and real-time data into shared-earth modelsis critical for improving drilling and pro-

duction processes. Knowledge management

will be used to evaluate hydrocarbon

reserves throughout the life of the well toincrease the recoverable resources from the

reservoirs significantly.

Partnerships among service companies

and between E&P companies and service

companies will enable resource sharing, todevelop new systems. These partnerships,

through joint-industry projects, will play a

significant role in the development and

introduction of new technologies tooil fields.


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