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Usi-ls027627 Determination From Well Logs oF the Total

.Orgtinic Carbon Content in Potential SourceRocksJ.L. i-in, Dswirw Petroleum Inst. ;H. A. S.E.~&.-c.~,, U.. of New 9oyth .Wales;

COPYRIGHT~SO.CIETY .OF PETROLEUMEKGINEERSThis manuscript was provided to the Society of Petroleum Engineersdistribution andpossible publication in an SPE Journal. The Contents of forthispaper (1) are sub ject to correction by the author(s) and (2) have not undergoneSPE peer review for technical accuracy. Thus , SPE makes noclaim about the..contents of the work. Permission to copy or use is restricted to an abstract ofnot more then 300:wor.ds.Write SPE Book Order Dept. , Library Technician, P.O.Box..833836; Richardson .TX75083-3836 U.S.A. Telex 1632.45 SPEUT

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PUG i 21993 ,;, :=>,,. ..,, ._. . UNSOLICITEDDETERMINATION FROM WELL LOGS OF THE

TOTAL ORGANIC CARBON CONTENTIN POTENTIAL SOURCE ROCKS

J.L. Lin - Daqing Petroleum Institute, P.R. ChinaH.A. Salisch - Centre for Petroleum EngineeringUniversity of New South Wales, Sydrrey-Australia ~ember SPE]APRIL, 1993

ABSTRACTThispaper discusses, in some detail, the log responses to total orgsrric cwbon [TOC] in theUpper and Middle Velkerri Formation in sn area of the McArthur Basin, Northern Territow,A~tdia. The Fotiation Density log was found to be superior to other standard weU logsin assessing values of TOC in the area shylied. A theoretical model was used to estimate TOC.. .fromthe Fomration Density log. The model was es@Mishedand ils .aqiicabdity was vcritiedby comparison with other models. Based on geochemiwd properties the Upper and MiddleVelkerri Forrmition are classified into three categories: non-source rocks, mature sorrrce rocksand immature source rock. They show significant diftleiences h the well Iog responses, thusdi.t%rentmodels had tobe established for the three categories to determine the TO.C.contentffom well logs. The compsrisim of the results of using a dfikrent model for each categoryinstead of a single model to cover tire three categories shows that the former gives moremeatigfid anawrzs....

JNTRODUCTIONTotal Organic Carbon [TOC] contenfpreient iit potential source rocks significantly affects theresponse of s&eral types of well logs. Wireline Iogs can be used to identify source rocks andserve as atr indicator for the source rock potentisl provided that the source rocks have aminimum thickness within the resohrtion of the mesaurements being made and that they arearrtllcicntly rich in orgsrric matter. Wireline methods for estimating organic matter contenthave the advantage of economy, readily avaiIable sources of data and the continuous samphngof a vertically heterogeneous shale section .A pilot arm was selected within the general area in which an integrated reaesrch effort tocharacterise the organic matter in the VeIkerri Formation had been initiated. The objectivewas to attempt to establish in the pilot area a quantitative correlation between standard welllogs and total orga~c carbon [TOC] corrtcnt.

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SPE27627.Thk correlative work was performed for the Upper and Middle Velkerri Formation, in theMcArthur Basin of the Northern Territory, AustrN1a. The formation is made up mainly ofcIaystone and siltstone. The Upper Velkern Formation is commoidy shale and appears tocontain no source rocks. The Middle Velkerri Formation does contain mature and/or immaturesource rocks.

Four key wells. were included in this study: They will be called here wells A, B, C and D.The surface d~tances between wells is indicated on the location map at the end of the paper. IThe following well logs, run in the early 80s, were available: -InductionResistivity logs-Sonic logs-Formation Density/Neutron logsMI logs had natural gamma-ray curves. Two-arm caliper curves were available.Formation waters are known to have a salinity in excess of 150,000 ppm of NaC1. Thedrilling fluids were basically simple fresh-water clay muds with an estimated 4% content of! KCLA comparison was made of different log responses in relation to a large number ofgeochemical analysis data made available for this study. The Formation Density log responsesgave the most dependable estimates of TOC in this area. Literature has been published on theuse of density measurements for the determination of TOC.QThe models used in some of theliterature are based on linear and non-linear eqnations which were derived by regressionalmethods. Irrthis paper a theoretical model is being presented for an estimate of TOC content,based on a volumetric model and principles of log measurements. The results of correlationand error analysis indicate that the model is superior to others in this area in calculating TOC -.content by using single log responses ,In this study the source rock evaluation from well logs was hased on grouping the Upper andMiddle Vel.kern Formation into three distinct categories, based on measured geochemicalcharacteristics. They are.- Source rocks with mature organic matter- Source rocks with immature organic matter, and- Non-source rocks.The three categories are different in their electric facies. The equations derived for eachcategory have made it possible to calculate TOC content from Formation Density logresponses only.Cross-plots and Bayes mrrhi-gronp discriminant analysis were used to determine the rockcategories as listed above.The methodology was later apptied to a fifth well, outside of the original pilot stndy. Theresults were equally consistent with geochemical anatysis data.

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,,.. . . .: .$,. S~~27627LOG RESPONSES IN SOURCE ROCKSAccording to a study at the Institute Francais du Petrole [unpublished], source rocks from 18sedimentary basins showed an average of 1.82%of Total Organic Carbon [TOC]. If thisaverage is reduced to the case of shrdes and silts only, the average rises to 2.16%. Hunt(1961). found- iiii average vakre of 1.659oTOC in 200 shale formations in 60 sedimentarybasins. According to Jones (1970), a majority of the worlds oil accumulations originated insource rocks with a total carbon content in excess of 2.5 weight percent. The minimumconcentration of organic carbon content required for a source rock to generate commercialhydrocarbon accumulations has frequently been stated as being 0.5% by weight.Based on core and log anafysis data, the content in TOC of source rock in the VelkerriFormation is about 2%.Source rocks are commonly shafes and lime-mudstone that contain significant amounts oforganic matter. Non-source rocks also contain organic matter, but the amount is usually lessthan 1.0% by weight. ConceptrraJly, organic- rich rocks can be assumed to be composed ofthree componentrock matrix- solid organic_matter,. and- fluid(s) filling the pore space.

Non-source rocks are composed primarily of only two component the matrix and the fluidfilling the pore spaice.-In immature source rocks, solid organic matter and rock matrixcomprise the solid fraction, and formation water fills the pore space. As the source rockmatures, a portion ofhe solid organic matter is transformed into liquid [or gaseous]hydrocarbons which move into the pore space, displacing formation water. These physicaltransformations willhave an effect on geophysical log responses.:In the following pages an outline is given of different log responses in source rocks

Gamma-RayTogsOrganic-rich rocks can be relatively highly radioactive, i.e. they can have a higher gamma rayreading than non-sonrce shales and limestone, ~k natural radioactivity is usually due touranium enrichment. It can be postulated that plankton absorb uranium ions that are generallypresent in sea water together with other trace elements and that uranium thus becomesconcentrated in the source rock. It has been found that Iacustrine source rocks have no gammaray anomrdies, owing to the scarcity or absence of uranium ions in fresh waterfFigures 1 and 2show the gamma ray curves for two of the wetts included in this study. Ineach case it is indicated that the Gamma Ray log will identifi source rocks in the VelkernFormation in tlds area.

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WE27627Resistivity LogsSource beds are geirrmlly thin, discrele layers even in thick source rock formations. Thusrichness can vary considerably in a vertical dkction and a high vertical logging toolresolution is, therefore, desirable. In principle any resistivity log may be used to evaluateimpermeable formations such as source rocks.c Shallow and deep-penetration logs should givethe same reading unless affected by borehole or anisotropy effects or by tool characteristics.Source rocks are generally laminated and thus are electrically anisotropic. This increases theresistivity measured by spherically focussed logs. When source rocks become mature, free oilis present in voids and fractures and with maturity the resistivity of a source rock increasessignificantly. This makes it possible to use resistivity as a snaturi~ indicator for a given source rock formationFigures .l.and 2 show the deep resistivity curves in the Velkern Formation for the two weltsindicated. Higher resistivitics are displayed in mature source rocks [lower part of Figure 1]than in immature source rocks [upper part of F@tre 2] and in non-source rocks [upper partof Figure I and lower part of F@re 2]. Resistivity increases whh the degree of maturity. Thesource rock resistivities in the Velkern Formation of wells A, B and C, in all of which theorganic material is mature, are much higher than those of non-source rocks in the same wells.There is little difference, however, between the re.sistivities of source rocks and non-sourcerocks in the Velkern Formation of well D, as the organic material is immature.

Formation Density LogsThe Formation Density log measures the bulk density of the formation. This density consistsof the combined effects of matrix density and fluid density. The more fluid a formationcontains, the more porous it is. In shakes with a similar degree of compaction and similarmatrix arid fluid density, water saturation should also be equaf. Sofid organic matter has asimilar density to that of water [approx. 1.0 g/cc]$and thus less than that of the surroundingrock matrix. If the density read in source rocks is lower than the density read in normalshales, it must be a function of the amount of organic matter which is present. At a shaledensity of about 2.25 g/cc or greater, the minimum concentration of organic matter for theFormation Density log to respond is about 1.0 % by weight.Figures 1 and.2 display the density curves for the same two wells, in the Velkern Formation.It is apparent that in source rocks the density is lower than in non-source rocks. The figurealso indicates that mature rocks have lower densities than immature rocks.

Sonic LogsLike Formation Density logs, Sonic logs afso show the difference between organic-leansedments and source rocks. Sonic logs afone cannot be used to estimate the organic contentof source rocksbecause interval transit time is affected by the water/organic matter ratio,mineral composition, carbonate/clay content and grain-to-grain pressure.

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SPE2?627Figures 1 and 2 show the interval transit time curves for the two wells. Source rocks can beidentified by their transit times longer than those of non-source rocks. Source rocks withimmature organic material have longer transit times than source rocks with mature organicmaterial.

Neutron LogsNeutron log porosity responses are higher in source rocks than in non-source rocks asdisplayed in F@rres 1 and 2. They show the neutron porosity curves for two of the wellsstudied.

CLASSIFICATION AND DETERMINATION OF SOURCE ROCKS

Thermal evolution of the source rocks during diagenesis, catagenesis and mutagenesis changedphysical and chemical properties of the organic matter? These properties may be consideredas indicators for maturation..Well. log data contain much information about geophysical andgeochemical properties of rocks. Therefore, the correlation of well logs with geochemicalanalysis data from cores can be the basis for a continuous evaluation of the level ofmaturation of source rocks.

SignificanceIn looking at the correlation between several log variables and TOC content the study foundthat the relationships between different log responses and the TOC content are dissimilar inthe wells studied. This is due, mainly, to the fact that source rocks from these four wells arenot at the same stage of maturation. It is thus necessary to classify source rocks and toestablish separate mathematicrd modets for source rocks at different stages of maturation toobtain accurate values of TOC content.Figures 7 and 8 are density - TOC cross-plots for the four wells and for the three distinctcategories plotted individually. Figure 7 shows that the relationships between TOC and thedensity log response is different for each of the four wells. By using the same equation todetermine TOC for afl four wells, the error in the results is high [SE=l.3 183]. Figure 8indicates the relationships between TOC content and the density log. responses for eachd~tinct category in each of the four welfs attrdled. The accuracy by using this groupingmethod into categories is significantly h@her [SE=O.8841].

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m., - - . ...,. SPE27627

ClassificationFour cross-plots were established to study the maturity of the organic matter in source rockThey are:-01 [Oxygen Index] - HI.[Hydrogen Index] cross-plot-TOC [Total Organic Carbon] - S,+S2 [Production Potential] cross-plot-TOC [Total Organic Carbon] - PI [Production Index] cross-plot, and-TOC [Total Organic Carbon]- 01 [Oxy~en Index] cross-plot.Figure 3 represents the 01-HI cross-plot for the four wells. It can be used to study thematurity of organic matter in source rocks in thk area. Temperature and pressure variationsare responsible for the maturation of organic matter. This process tends to decrease the valuesof both HI and 01. The maturity of source rocks in well C is shown to be relatively higherthan that of source rocks in wells A and B. Source rocks in well B appear to be moremature than those in well A. Source rocks in well D stand out as being much less mature.Figure 4 indicates that well D has higher values of TOC and 01 than the other wells.Figure 5 shows this same relative. maturity development and that well D has higher values ofTOC and of [S1+S21.Figure ISindicates that the PI values in the Velkern Formation in well D are lower than in theother wells. PI is an indicator of maturity.Baaed on the above cross-plot analysis and core data it is apparent that the organic matter inwell D is basically immature, while the organic matter in wells A, B and C is mature. It alsoaPPears that the maturity of the organic matter in the source rocks of wells C, B and A goesfrom higher to lower, in ttds order. ThK,was born out by geochemical anatyais.The results of the work described above confirmed that it was correct to divide the Upper andMiddle VeIkerri into three categories non-source rocks, mature source rocks and immaturesource rocks.The relative well log responses for these three categories can be spelled out as follows

1] for non-source rocks- lowest gamma ray values .,- lowest resiativities- highest bulk den@ies.- lowest interval transit times- lowest neutron porosities .

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s~E27627

2] for sourcefocks with mature orgariic matter- highest gamma-ray values- highest resistivities- highest neutron poroaities- medium range intervat transit times3] for source rocks with immature organic mattec- lowest bulk densities- highest interval transit times- lower resistivities than in mature source rocks- higher gamma- ray vahres than in non-source rocks

IdentificationBayes discriminant analysis was applied in order to attempt to dkcnminate among the threerock categories. For this purpose the responses read from the Gamma-Ray, Resistivity, Sonic,Formation Density, and Neutron logs were used.The Bayes discriminant function Fi(x) is derived from Bayes discriminant rules.

i(x)n(q)W+zHXi=l, 2, .... G;

wherex=(x],x?,....x.} a sample for discriminant analysisv -~number of variablesG -.number of categories (G=3)q=ni~N - tobl riiirnber of samplesni- totaf number of ith category samplescOi, ~- discriminant factor

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Dkcriminant factors were then determined. They are expressed in matrix form as follows

{

5.566 118.842 2450,405 2784.091 -17,305 -9346.955-7.035 116.943 2481,073 2777.143 -17,052 -9324.8041.511 108.438 2334.586 2824.507 -17.890 -9183.656 1

The discriminant method requires that a sample X = (x,, x,, .... x.) for discriminant analysisbe entered into the above discriminant functions to calculate function values.If Fl(x) = MAX { Fj(x)} j =.1, 2, .... GSample X belongs to the ith category.The correct discriminant ratio is close to 95% for both source rocks with mature organicmatter and source rocks with immature organic matter, It is 85% for non-source rocks.

DETERMINATION OFTOCTotaf organic cmbon is an important parameter in the evaluation of source rocks. Based ongeochemical characteristics in the Upper and Middle Velkern Formation, a technique wasdeveloped to estimate the amountof TOCfrom well logs.Atotalof228 sampIeswithTOCanafysis results from wells A, B, C and D were used in thk study.

Selection of the log variableCorrelation anafysis was used in the selection of log variable to estimate TOC, Correlationanafysis is a mathematical method to study correlation between variables. The correlationcoefficient [R] is described as follows.

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2(xi-x) . (Yi-n=d%-=iE_.. .

Where xi - ith sample value of the x variablex -ith sample v~ue of the y variableN - totat number of samplesTwo variables are more- linearly correlatable the closer the value of R to 1 or -1. In thisstudy correlation is used to look at the relationships between log variables and thegeochemiczd parameters, and to evaluate the results of log analysis.Table 1 gives the vahres of R[correlation coefficient] for TOC and log variables or logtransform variables. Theresults of the correlation may help in the proper selection of logvariables to estimate TOC.It also shows that the correlation of TOC with formation density, sonic transit time andneutron porosity is good for each well; that values of gamma-ray, formation resistivity andinterval transit time increase with increases irr TOC and that values of formation densitydecrease with increases in TOC.

Study of the ModelThe correlation analysis between log responses and core datu armlysis rcsulls for TOC in theVelkerri Formation on wells A, B, C and D shows that the Formation Density log has thehighest correlation coefficient [Table 1]. The Formation Density log was, therefore, selectedto estimate the TOC content.Four forrtis of presentation were considered for the bulkdensity of the formation (ph), forcorrelation and error analysisp, - linear! Iog( p~) - logarithmicexp( p~) - exponential, and1/ p~- reciprocal

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SPE2762?

TABLE 1- CORRELATION COEFFICIENTS [TOC]--. _--- c

R WELL A WELL B WELL C WELL D. FOUR WELLS

GR 0.04160 0.51435 0.64851 0.61560 0.04090lJGR 0.02961 -0.38581 -0.63686 -0.62890 -0.01512LOG(GR) 0.00235 0.44968 0.64270 0.62638 0.02511EXP(GR) 0.09675 0.38653 0.68191 0.10024 0.06815

RT 0.79916 0.77246 0.83713 0.70132 0.50237IIRT -0.79983 -0.60691 -0.87572 -0.74331 -0.49805LOG(RT) 0.85250 0.73304 0.87001 0.74434 0.53271EXP(RT) 0.15808 0.3325.1 0.31046 0.36231 0.08800

RHOB -0.84590 -0.72338 -0.86197. -0.83394 -0.79915l/RHOB 0.84676 0.72679 0.87167 0.83523 0.80120LOG(RHOB) -0.84632 -0.72518 -0.86692 -0.83465 -0.80041EXP(RHOB) -0.84334 -0.71795 -0.84835. -0.S3172 -0.79416

DT 0.41247 0.61719 0.65409 0.74260 0.62933.l/DT -0.40481 -0.60883 -0.65562 -0.74884 -0.60593.LOG(DT) 0.40884 0.61337 0.65498 0.74656 0.61860EXP(DT) 0.25143 0.25218 0.25573 0.34887 0.30130

PHIN -0.13278 0.66114 -0.11195 0.72213 0.09069lffHIN 0.13026 -0.63235 -0.00185. -0.51604 0.00786LOG(PHIN) -0.13246 0.64887 -0.05509 0.67427 0.04484EXP(PHIN) 0.06226 0.22816 -0.25144 0.37239 0.24428

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SiPE2762?Error analysis is used to determine the form of log variable. Standard error [SE] was usedin this study and it is given as follows:

r (T,-TI=,) 2SE= N-2where

N - total number of samplesTCi -trot [cores] value of the ith sampleTi--Iog derived value of the ith sample

Table 2 shows the rrsrslts of the error analysis

Table 2- standard error for TOC content

Pb log (p,) ~P (Pb) llpbSE 1.3533 . 1.3495 1.3681 1.3.471

The results of both correlation and error analysis indicate that the reciprocal mode of RHOB,[p,], gives the best answer in regards to correlation coefficient and standard error.It is assumed that he sortrce rock is composed of two parts pure shale and organic matter,and that the Formation Density log response follows the volumetric model so thsi~

Pb = p,h(l-var) + Po,vo,or VOX( pb - p* )/(por-p,h)where:P, - the density of the source rockP,, - the density of pure shalePw- the density of the organic matterv,h - the fraction~ volume of pure shale, andv., - the fractional volume of the organic matter.

-II- ,..=

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SPE27627The weight percentage of organic matter, POW, is described w

Pow = 100 Vo,po)pbTOC is assumed to be related directly to POW9so that

TOC = k POW= k 100 VO#Ojp,= a +b lp~where

!a =-k 100 pO,/(p,~ -pO,)b = k 100 pi poj( p,, -Per)k= factorBased on the above analysis results the reciprocal form of p~is taken as the interpretativemodel to estimate the TOC content from the FormationDensity log.

EQUATIONS

Equation for the model which groups the whole interval into one categoryRegression analysis is used to obtain a regression equation. The equation for calculatingTOC from the Formation Density log is

TOC = -42.97115+114.18641p,The correlation coefficient [R]= 0.801189. The standard error [SE] = 1.347122.

Equations for the model which groups the interval into three distinctcategories

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Based on the analysis done a reciprocal model of density is used in the regression for eachcategory. The results of the regression arfx

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s~E27627- for.. source rocks with mature organic rrmttexTOC=-26.6694+76.36593/pb _- for source rocks with immature organic matterTOC = -77.6585+194.1856/pb- for non-source rocks:1OC= -l Mii+31.5691pb

ANALYSIS OF RESULTSA total of 228 samples with core data from wells A, B, C and D were studied by bothmethods mentioned above. The correlation coefficient [R] and standard error [SE] betweenthe TOC content from ~e model of grouping the whole interval into one category and theTOC content from core data a& respectively 0.8841 and 1.3183.,The correlation coefficientand standard error TOC from the model of grouping the interval studied into three distinctcategories are, respectively, 0.9167 and 0.8012.Table 3 gives the two resrdts determined from the Formation Density logs of five welL$inthe area, includhg the four wells in the pilot area. One of themis for the model of groupingthe whole interval into one category; the other is for the model of grouping the intervalstudied into three distinct categories. The regression equations were derived from core andlog data from the four wells.

TabIe 3- comparison of results

Wells A B c D E The fourwelts ofthe pilotareaR[l] 0.847 0.727 0.872 0.835 0.602 0.801R [3] 0.885 0.862 0.910 0.874 0.789 0.917SE [1] 1.184 1.418 1.076 2.216 1.257 1.318SE [3] 0.909 0.942 0.756 1.485. 0.961 0.884

[1] = model which groups the whole interval into one category[3]= model which groups the interval studiecIinto three distinct categoriesTable 3 shows that the results determined from model [3] have higher correlation coefficient

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SPF27627vahres and lower standard error values than those from model [1]Flgtrres 9 and 10 compare the results for two wells in the pilot area. F&gure9 shows that inthe upper shale interval, from 390 metres to 610 metres, the results obtained from bothmodels are identical to the TOC content values measured on cor~. In the interv~ from 66ometres to 720 metres and in the interval from 910 metres to 940 mitres the TOC valuesobtained fromlogs are lower than those measured on corex however, the error in the resultsfrom model [3] is less than that from model [1]. Figure 10 indicates that in the inteival from340 metres to 416 metres the TOC vahres obtained from model [1] are too low and have ahigher error and that the TOC values obtained from model [3] tie very close to the TOCvalues measured on cores.

CONCLUSIONS1.- Well logs can be used with reliable results to evaluate source rocks and to estimate theirTOC content irr the area studied in the McArthur Basin. The area comprises wells A, B, Cand D. The model was also veritled on a well outside of the pilot area [well E].

2.- A model of grouping the interval studied into three distinct categories: source rocks withmature organic matter, source rocks with immature organic matter and non-source rocks hasshown to provide good results in the estimate of TOC content from conventional well logs.3.- The Formation Density log is superior to other standard well logs in assessing values ofTOC conteut in the givenenvironment.4.- The reciprocal mode of the Formation Density log variable is used with preference overother modes linear, logarithmic and exponential, for an estimate of TOC content.5.-The organic material in well C appears to be the most mature, followed by well B andwell A in stage of maturity. The source rock in well D appears to be immature. Theseconclusions are in agreement with the results of the geochemical analysis of well samples.

ACKNOWLEDGMENTSThe authors wish to express their appreciation for the assistance of CRA Limited and PacificOX1and Gas Pty LtdLimited which provided the well data as well as to personnel from theCentre for Petroleum Engineering of the University of New South Wales who assisted duringthe work carried out for the development of the project

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SPE27~27REFERENCES1- A Practical Model for Organic Richness from Porosity and Resiativity Logs Passey Q.R.,Creaney S., Kulla J.B., Moretti, F.J., Stroud J.D.- AAPG Bulletin, V.74, No.12, 19902- Oil Generation Inferred from Formation Resistivity- Bakken Formation, Williston Basin,North Dikota Schrnoker J.W., Hester T.C -SPWLA 30ttr Ann. Logg. Symposium, 19893- Well Log Evaluation of Lacystrine Sour% Rocks of the Jjagoa .Feia Formation, LowerCretaceous, Carnpos Basin, Offshore Brazik Abrahao,D.- SPWLA 30th Annual Logg,Symposium, 1989 4- Total Organic Carbon Content Determined from Well Logs Feral W.H., Chllingar C.V.-SPE .15612, ~986 .= - ..:5- A Preliminary Assessment of the Application of various Geophysical Techniques to OilShale Resource Evaluation: Coshell L., McIver R., Fraser N.,[Unpublished]6- Identification of Source Rocks on Wireline Logs by Density/Resistivity and Sonic TransitTime/Resistivity Cross-plots Meter B.L.,Nederlof M.H - AAPG Bulletin Vol 68, No 2, 19847- Determination of Organic-Matter Content of AppafachlanDevonian Shales from GammaRay Logs: Schmoker J.W.- AAPG Bulletin, Vol 65, 19818- Determination of Organic Content of Appalachian Devonian Shales from FormationDensity Logs: J.W. Schriroker - AAPG Bulletin 63, 19799- Petroleum Formation and Occurrence, Tissot B.P., Welte D.H., Springer Verlag, 1978

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SPE27627

WELL LOCATIONSMc.XRTI-lUR BASIN, AUSTRALIA

IC.zrpenl.arIoy _

o

lW IuDoly Waler,

17 - 17..___ ._.

[0 20 0 7.(J4(J60 ~~1 Km , II3X 13< 135 13W 130-30

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Cz@EIl LOg CUtW?S - Well A UpperandMiddleVelkerriI I

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