cation exchange

SPWLA TWENTY-SEVENTH ANNUAL LOGGING SYMPOWLIM,JUNE 9.I3, 1986

ABSTRACT

,...

CORRELATION OF CATION EXCHANGE CAPACITYUITH CORE SPECTRAL 6AWl RAY L06S

mJames E. Atwater

GEOTECHnical resources ltd.Calgary, Alberta

Cation exchange capacity (CEC) is a well known index of the electricalconductivity of sedimentary rock fabric due to the electrostatic adsorp-tion of ionic species from connate formation water onto the urfaces ofcla lamellae.

8in the present paper, the ionic natures of ?KO, 13i214,

T12 8 and other nuclides of the natural uranium and thorium decay chainsare exploited in the radiometric determination of CEC in intervals ofhomogeneous lithology and diagenetic history. Good agreement is obtainedbetween CEC and the activity of gamma emitting radionuclides determinedfrom spectral garmna ray logs of oil and gas well drill cores. Depthresolution is optimized through the use of expanded scale core gamma raylogs presented on a 1:40 scale. Core is zoned into units of homogeneouslithology. For each zone, CEC is determined by chemical analysis atvarious depths. Using L2 approximation theory and matrix operations, asolution vector is obtained which relates meq/loOg CEC to GR (API), K(%), U (ppm) and Th (ppm). CEC values of reasonable accuracy can then bederived from subsequent cored intervals of similar lithology using highresolution spectral gamma ray logs and the appropriate correlationequation for each zone.

INTRODUCTION

Cation exchange capacity (CEC) is becoming an increasingly importantparameter for use in the evaluation of potential oil and gas bearingstrata. lts magnitude represents the extent of adsorption onto clay sur-faces of positively charged counterions from the electrolytic medium.Cationic counterions are bound by electrostatic fields to negativelycharged sites at the clay surface arising from crystal lattice defects(l). The phenomenon of ion exchange is intimately associated with clayswelling behavior in fresh water environments. Osmotic forces propelwater into the interlamellar spaces of clay minerals to neutralize theelectrochemical potential between the high ionic strength micro-environ-ment of the clay surface and the low ionic strength environment of thesurrounding pore space. In general the swelling tendency of claysincreases in direct proportion to the equivalent or molar cation exchangecapacity of the mineral in question. Thus CEC can provide a useful esti-mation of the effective clay content or swelling tendency in zones withfresh formation waters or under waterflood with low salinity injectionwaters.

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SPWLA TWENTY-SEVENTH ANNUAL LOGGING SYMPOSIUM, JUNE 9-13, 1986

Clay exchange counterions are also responsible for the electric doublelayer effect to which matrix electrical conduction in shaly sands hasbeen attributed (2). In general, the higher the cation exchange capacityof an interval, the greater is its propensity for matrix conduction. CECper unit pore volume appears as the Qv term in the models of Hill andMilburn (3), Waxman and Smits (4), and Calvier et al. (5) which providebases for the evaluation of wellbore resistivity logs in regions of highclay content. The utility of these shaly sand models has received amplesupport in the literature (6-11).

In the laboratory cation exchange capacity is determined using a varietyof classical titrimetric procedures (12-14). An indirect method has beendescribed which employs hydration of clays under controlled humiditydrying conditions (15). Due to the considerable cost of direct CECdeterminations in core samples, lesser quality data is often used for theevaluation of resistivity logs in shaly sand intervals. Correlations ofCEC with other petrophysical parameters such as porosity (16) and totalgamma ray activity (17) are common. In the present study a method isdescribed for the estimation of cation exchange capacity based uponcorrel~tion of precise CEC values determined in the laboratory with highdepth resolution spectral gamma ray logs of core. Correlation isobtained using least square (L2) approximation theory for separatezones of homogeneous lithology. CEC is evaluated in subsequent cores

through spectral gamma ray logging and mathematical analysis. It ishoped that data of intermediate quality between chemical assay and well-bore logging will result.

Beyond the commonly accepted generalization that shales tend to havehigher levels of natural gamma ray activity due to the presence of clayminerals, there is additional information to suggest a potential connec-tion between the phenomenon of cation exchange and levels of naturalradionuclides within the rock fabric. In studies of preferential cationadsorption it has been demonstrated that divalent cations are bound morestrongly than monovalent cations, and that among homologous series ofconstant valence preference of adsorption is inversely proportional tothe hydrated ionic radius (18-21). Large ions have smaller hydratedradii than small ions due to more efficient screening of nuclear chargeby orbital electrons. The cationic forms of natural uranium, naturalthorium and their radioactive decay products have valence of at least twoand are all very large. On the basis of both hydrated radius and valencethese radionuclides should be adsorbed preferentially from the aqueousmedium resulting in relatively high concentrations of radioactive speciesat the clay-water interface.

The quantity and kind of adsorbed radionuclides within a given lithologi-cal unit will necessarily depend upon many factors which determine theunique diagenetic history of the sediments. The chemistry of formationwater and surrounding rock, porosity, permeability and topography ofhydrodynamic flow will certainly be important. The operation of disequi-libriummechanisms such as alpha particle recoil and diffential volubility(22,23) may particularly influence the distribution of natural uranium

.,..,,

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..-

#“’-

daughter radionucl ides. Thus it is to be expected that proximate zonessubjected to the influence of divergent diagenetic factors may yielddissimilar distributions of radionuclides as adsorbed clay counterions.For the purposes of the present study the converse was assumed, thatzones of homogeneous lithology and common diagenetic history can be iden-tified for which fluctuations in radionuclide content evince variation ineither type or quantity of clay minerals present, and give an indicationof cation exchange capacity.

CORE SPECTRAL GAMMA RAY LOGGING

Spectrometric gamma ray logging of core has been applied in mineralexploration (24) and more recently in oil and gas well core analysis.The gamma ray spectrometer used in this study has been described else-where in detail (25). In brief, the system consists of twin 3 X 3 inchthallium activated sodium iodide scintillation gamma ray detectors,housed within a low activity lead shield and optically coupled to photo-multiplier tubes, multiplexed to a common charge sensitive preamplifier.Preamplifier output is routed to a spectroscopy grade pulse processinglinear amplifier and Wilkinson type 13 bit analog to digital converter.Coincident counting can be prevented using pulse pile-up rejection cir-cuitry which gates an inhibit pulse to the analog to digital converterwhen distorted waveforms are detected by the amplifier. The digitalsignal is transfered via a CAMAC dataway to an on line PDP 11/44 minicom-puter for multichannel pulse height analysis in software. Consistentwith standard geophysical practice, energy windows are set at 1.46 MeVfor 40

I1.76 MeV for Bi214 (natural uranium channel), and 2.61 MeV for

T120 (na’turalthorium channel).

Core gamma ray logs are obtained by passing the core at precisely regula-ted velocity into the detection chamber via a conveyor belt. The resul-tant time varying signal is recorded as intensity versus depth orderedpairs and stored on hard disc in separate potassium, uranium, thorium andtotal gamma ray files. For routine core analysis applications, spectralgamma ray logs are recorded using a logging speed of 1.0 meters perminute for data presentation on the 1:200 or metric 1:240 verticalscales. In circumstances where optimal depth resolution is desired,spectral logs are acquired using a logging speed of 0.2 meters per minuteand displayed on 1:40 or metric 1:48 vertical scales. Further improve-ments in depth resolution using even slower logging speeds are impracti-cal due to instrument workload. Cation exchange capacity can often varyrapidly over small depth increments. Optimal depth resolution was deemedessential for correlation of radioelement distributions with CEC valuesdetermined at point depths by chemical assay. To this end, deconvolutionof spectrometric gamma ray logs has been evaluated as a means of furtherenhancing spatial discrimination.

Deconvolution techniques have been judged of limited utility to the loganalyst as an aid to the evaluation of natural radioactivity and soniclogs (26,27). In contrast, deconvolution has been used with consider-

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able success in gamma ray spectrometry of uranium exploration boreholes(28-30). The output signal of the core gamma ray spectrometer may beconsidered as the convolution of the true gamma emitting radionuclidedistribution with the detector response function. Given an infinitelythin zone of radioactivity (impulse), the resultant instrumental output(impulse response) will appear as a Gaussian peak of appreciablethickness. The thickness of the peak is attributable to the detectorresponse function. As the radioactive zone approaches the detector,levels of gamma activity observed gradually increase to a maximum valuewhen the radioactive zone is immediately adjacent to the detector, andthen fall off with the square of the source-detector distance as the zonemoves away. The end result is considerable loss of spatial resolution inthe gamma ray log.

In the deconvolution procedure, the spectral gamma ray log is convolvedwith a discrete digital filter approximating the inverse of the detectorresponse function. In theory, the deconvolved log will reflect the trueradioe”lement distribution devoid of any contribution from the instrumentresponse furlction. Due to the similarity of gamma logger smoothingalgorithms to rate-meter time constants, and for simplicity, the inverserate-meter response function was selected for deconvolution. Therate-meter impulse response function has been given by Conaway andKilleen (28) as,

zf(z) = ~ e ‘~ .

By taking the Fourier transform of the impulse response, an inversefunction is readily obtained in the frequency domain,

r z-—-F(W) = + ~ e VT ‘Wz dz = 1+ iwvT ,

F ‘1 (w) = 1 + iwvT .

Applying the inverse Fourier transform back into the t-the inverse rate-meter response function is obtained,

rf-l(z) = + ~m (1 + iwvT) eiwz dw = f(z)

The derivative of f with respect to z is approximated by,

me (depth) domain,

‘v% .

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SPWLA TWENTY-SEVENTH ANNUAL LOGGING S’fMPOSIUM, JUNE 9-13, 1986

#--

,...

leading to the discrete three point inverse filter,

(2%’1’ )-2% .Deconvolution procedures for core spectrometric gamma ray logs will bepresented in greater detail elsewhere (31).

CORRELATION USING L~ APPROXIMATION THEORY

Core spectral gamma ray logs exist as discrete intensity versus depthordered pairs, with a constant depth increment between points. Theordered pairs located closest to the exact point depth of samples submit-ted to chemical analysis are extracted from log files. Data are thenfitted to a linear equation in four independent variables of the form,

CEC(meq/100g) = Al+ A2Gt (API) +A3K(%) +A4 U(ppm) +A5 Th(ppm),

using L2 approximation theory (32). The set S is formed from the sum-mation of the squares of the difference terms for each depth at which CECand gamma ray data are available,

S =3(CECi - Al - A2 Gti2

‘A3Ki-A4ui-A5Thi) “i=l

S is differentiated with respect to the coefficients Al through A5and the partial derivatives are set equal to zero,

(la

resulting in five linear equations in which the coefficients A1-A5are unknown. The equations are conveniently represented in matrix nota-tion as,

XA=Y

#“--

-5-


,-

where the 5 x 5 matrix X is given by,

x=

n

‘li

‘2i

‘3i

‘4i

xxlix2i

and the column vectors are given by,

Zxzixqi

()AlA2A= A3

{)A4A5and

Yi

)XliYi

X’2iYj-

‘3iyix4iYi

)‘4i‘4i

‘4i

The simultaneous system of equations ismultiplication. The solution vector A is

solved by matrix inversion andgiven by,

Correlation coefficients are determined by linear regression of cationexchange capacities calculated from the model versus known values fromchemical assay, to assess the validity of the L2 approximation.

CORRELATION IN THE DE!30LTFORMATION

Multiple dolomitized limestone cores from the I.)ebolt formation,containing illite, montmorillonite and mixed layer clays, were examinedfrom two wells. The objective of the study was the determination ofcation exchange capacity as an index of effective clay content versusdepth. High resolution spectral gamma ray logs of each core wereacquired using logging speeds of 0.2 meters per minute and plotted on a1:40 vertical scale. A typical core spectral gamma ray log from thisformation is given in Figure 1. In general, potassium levels ranged frombelow the lower limit of detection to a few tenths of a percentage,uranium values fell between O - 3 ppm, and thorium varied from 1 - 10ppm. Spectral gamma ray logs were deconvolved using both three point andfive point inverse filters. Thirty two samples were taken for CEC

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. ..

/--

determinations from locations representing typical lithological trendsalong each cored interval. Cation exchange capacities were determined byconductometric titration using a modified method of Mortland and Mellor(14). The CEC values obtained fell within the range of 1.81 - 5.24meq/100g. The core was segmented into three zones (A, B and C) basedupon lithology, permeability and production characteristics.

Single parameter L2 linear approximations were generated between CECand total gamma ray, uranium and thorium activities taken separately.Potassium was excluded due to the high frequency of values below thelimit of detection. Correlation between single radionuclide activity andCEC for the formation as a whole and for discrete zones was in generalnon-existant or poor. Two marginal exceptions were the total gamma rayanti uranium activities of zone B which yielded correlation coefficients(r2) of 0.395 and 0.498 respectively.

A higher degree of success was attained through correlation of CEC dataas a coinbined function of total gamma ray, potassium, uranium and thoriumactivities using the methods described above. CEC values were calculatedusing the resultant equations in four independent variables and crossplotted against true CEC obtained through chemical analysis. The degreeof correlation for the formation as a whole was poor, as indicated by thecorrelation coefficient of 0.123. However, individual correlationswithin the discrete zones showed strong indication of positive correla-tion. Zone A, which contained six samples, showed the highest degree ofcorrelation (Figure 2), with an r2 of 0.7965. Zone B, represented by15 samples, yielded a correlation coefficient of 0.5438 (Figure 3). ZonePL, containing 11 samples, showed a correlation coefficient of 0.6207(Figure 4). The composite cross plot, given in Figure 5, shows good

linearity between CEC values calculated from the three correlations withtrue CEC levels across the entire formation. One-to-one correspondenceof the two parameters is indicated by the 45 degree angle which the datamakes with both x and y axes.

The three sets of coefficients A1-A5 obtained for zones A, B and Crespectively were used to calculate CEC logs along the full length of thecored intervals, operating on digital gamma ray spectroscopy logs.Typical 1:40 vertical scale sections of derived CEC logs from zones B andC are illustrated in Figure 6. Track 1 contains the core total gamma raylog, track 2 the calculated CEC log plotted on a horizontal scale of 1meq/lWJg per chart division. Horizontal bars in track 2 give the valuesof CEC obtained by chemical assay. Inspection of these plots demonstra-tes good agreement between calculated and actual levels of cation exchan-ge capacity. It can be infered that, given subsequent cores of equiva-lent lithology, cation exchange capacities may be determined with reason-able accuracy from high resolution core spectral gamma ray logs and thederived multielement correlation equations of the appropriate zones.

CEC correlations were obtained for zone A usinq deconvolved s~ectralgafi

–,---ma ray logs generated with both three point ;nd five point inverseters. The three point deconvolution (Figure 7) resulted in a corre-

QQ

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Iation coefficient of 0.9971. A correlation coefficient of 0.9999 wasobtainea for the log deconvolved with the five point inverse filter(Figure 8). in zone A a trend is evident, showing consistent improvementof the correlation between CEC and radioelement distribution as the depthresolution of the gamma ray spectrometric data is successively enhanced.The degree of correlation is improved from good prior to deconvolution,to excellent following deconvolution. Minor depth discrepancies of theorder of a few centimeters were discovered in the gamma ray logs fromzones B and C, when core was no longer available for analysis. Thisprecluded the use of deconvolved logs for the generation of correlationequations in these zones, as the depth uncertainty was of the order ofmagnitude of the expected improvements in spatial discrimination.

CONCLUSION

The feasibility of estimating cation exchange capacities through correla-tion of precise CEC values obtained through chemical analysis with radio-nuclide distributions quantified by spectrometric gamma ray logging ofcore has been demonstrated. Candidate reservoirs are those whose varia-tions in rock fabric can be effectively segregated into discrete zones ofhomogeneous lithology and common diagenetic history, and those from whichgood core recoveries can be obtained.

The data from the Debolt formation seem to indicate a decreasing degreeof correlation as the number of samples used to establish the correlationequations increases. The differences in correlation coefficients betweenzones A, B and C are in part attributable to statistical artifacts of theL2 approximation method and do not totally reflect significant diffe-rences in the abilities of the equations for these zones to predict CEClevels from radioelement distributions. As the number of coefficients inthe correlation equations approaches the number of samples used to gene-rate them, the degree of correlation will necessarily appear to improve.However, that the correlation procedure, as a whole, is not too stronglyinfluenced by statistical effects, is amply demonstrated by the dramaticimprovements in correlation attained for zone A using deconvolved spec-tral gammd ray logs. Under the operation of statistics alone, bothimprovement and deterioration of correlation would be equiprobablefollowing enhancements of depth discrimination. This is clearly not thecase. While the correlation methodology shows promise, considerably morecareful experimentation is required to define the limits of applicabi-lity.

..

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SPWLA TWENTY-SEVENTH ANNUAL LOGGING SYMPOSIUM, JUNE 9-13,1986

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TABLE OF SYMBOLS

f(z) = Detector impulse response functionF(w) = Fourier transformF-l(w) = Inverse Fourier transformf-l(z) = Inverse impulse response function

= Logging velocityY = Time Constant

= Depth:Z = Distance between depth, intensity ordered pairsw = FrequencyAl - A5 = Coefficients of multivariable L2 approximation equationxl = Total gamma ray activity (API)X2 = Potassium (%)x3 = Uranium (ppm)x4 = Thorium (ppm)Y = Cation exchange capacity (CEC), meq/100g

REFERENCES

1.

2.

3.

4.

5.

6.

7.

8.

9.

-

VAN OLPHEN, H., An Introduction to Clay Colloid Chemistry, 2nd Ed.,John Wiley & Sons, New York, 1917.WINSAUER, ‘W.O. and McCARDEL~ W.M., “Ionic Double Layer Conductivityin Reservoir Rock,” Trans. AIME, vol. 198, p.41, 1953.

HILL, H.J. and MILBURN, J.I)., “Effect of Clay and Water Salinity onElectrochemical Behavior of Reservoir Rocks,” Trans. AIME, VOI.207, pp 65-72, 1956.

WAXMAN, M.H. and SMITS, L.J.M., “Electrical Conductivity inOil-Bearing Shaly Sands,” Sot. Pet. Eng. J., June, pp 107-I22,1968.

CLAVIER, C., COATES, G. and DUMANOIR, “The Theoretical andExperimental Basis for the Dual Water Model for the Interpretationof Shaly Sands,” paper presented at 52nd Annual Fall TechnicalConference and Exhibition of SPE of AIME, Denver, October 9-12,1977.

HILL, H.J. SHIRLEY, O.J. and KLEIN, G.E., “Bound Water in ShalySands - Its Relation to Qv and Other Formation Properties,” LogAnalyst, May-June, 1978.

ORTIZ, 1. Jr., VON UINTEN, W.D. and OSOBA, J.J., “Relationship ofthe Electrochemical Potential of Porous Media with HydrocarbonSaturation,” paper presented at SPWLA 13th Annual Logging Symposium,June 4-7, 1972.

WAXMAN, M.H. and THOMAS, E.C., “Electrical Conductivities in ShalySands - I. The Relationship Between Hydrocarbon Saturation andResistivity Index; II. The Temperature Coefficient of ElectricalConductivity,” J. Pet. Tech., February, pp 213-225, 1974.VINEGAR, H.J. and WAXMAN, M.h., “Induced polarization of ShalySands - The Effect of Clay Counterion Type,” paper presented atSPWLA 25th Annual Logging Symposium, June 10-13, 1984.

ml

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SPWLA TWENTY-SEVENTH ANNUAL LOGGING SYMPOSIUM, J UNE 9-13, 1986

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VOLK, L.J. RAIBLE, C.J. and CARROL, H.B., “Influence of ShaleConductivities on the Electrical Conductivity of Low PermeabilityRocks,” J. Pet. Tech., May, PP 865-867, 1980.

JOHNSON, W., “Effect of Shaliness on Log Response,” CWLS J., Vol.10, No. 1, pp 29-57, 1978.

MEHLICH, A., “Determination of Cation and Anion Exchange Propertiesof Soils,” Soil Sci., Vol. 66, p 429, 1948.

PRATT, P.F. and HOLOWAYCHUK, N., “A Comparison of Ammonium Acetate,Barium Acetate, and Buffered Barium Chloride Methods of DeterminingCation Exchange Capacity,” Soil Sc. Sot. Proc. Vol. 18, pp365-368, 1954.

MORTLAND, M.M. and MELLOR, J.L., “Conductometric Titration of Soilsfor Cation-Exchange Capacity,” Soil Sc. Sot. Proc., Vol. 18, pp363-364, 1954.

BUSH, D.C. and JENKINS, R.E., “CEC Determinations by Correlation withAdsorbed Water,” paper presented at SPWLA 18th Annual Logging Sympo-sium, June, 5-8, 1977.

PIRSON, S.J., Geologic Well Log Analysis, 3rd Ed., Gulf, Houston,1983.

HILCHIE, D.W., Advanced Well Log Interpretation, Douglas W. HilchieInc., Golen Colorado, 1982.BOLT, G.H., “Ion Adsorption by Clays,” Soil Sci., Vol. 79, pp267-276, 1955.

ROGERS, W.J., SHIAO, S.Y., MEYER, R.E. and WESTMORELAND, C.G., “IonExchange on Mixed Ionic Forms of Montmorillonite at High IonicStrengths,” paper presented at Symposium on Suface Phenomena inEnhanced Oil Recovery, 3rd International Conference on Surface andColloid Chemistry, Stockholm, August, pp 20-25, 1979.GAST, R.G., “Standard Free Energies of Exchange for Alkali MetalCations on Wyoming Bentonite,” Soil Sci. Sot. Proc., Vol. 33, pp37-41, 1969.

GAST, R.G., “Alkali Metal Cation Exchange on Chambers Montmorilloni-te,” Soil Sci. Sot. Proc., Vol. 36, pp 14-19, 1972.

LEVINSON, A.A. and BLAND C.J., “Examples of the Variability of Dise-quilibrium and the Emanation Factor in Some Uraniferous Mate-rials,” Can. J. Earth Sci., p 15, 1978.

KILLEEN, P.G., CARMICHAEL, C.Pl. and OSTRIHANSKY, L., “RadioactiveDisequilibrium Determinations,” Geological Survey Paper 75-83,Ottawa, 1976.LOVBORG, L., WOLLENBERG, H., ROSE-HANSON, J. and LETH NIELSON, B.,“Drill-Core Scanning for Radioelements by Gamma-Ray Spectrometry,”Geophysics, Vol. 37, p 675, 1972.

ATWATER, J.E., “Spectrometric Gamma Ray Logging of Core,” CWLS J.,Vol. 13, NO. 1, pp 29-39, 1984.

LOOYESTIJN, WJ., “Deconvolution of Petrophysical Logs: Applicationand Limitations,” paper presented at SPWLA 23rd Annual Logging Sym-posium, Paper W, 1982.

SNYDER, D.D. and FLEMING, D.B., “Well Logging - A 25 year Perspecti-ve,” Geophysics, Vol. 50, No. 12, pp 2504-2529, 1985.

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28. CONAWAY, J.G., and KILLEEN, P.G., “Quantitative UraniumDeterminations from Gamma-Ray Logs by Application of Digital Time (laSeries Analysis,” Geophysics, Vol. 43, No 6, pp 1204-1221, 1978.

29. CONAWAY, J.G., BRISTOW, Q, and KILLEEN, P.G., “Optimization ofGamma-Ray Logging Techniques for Uranium,” Geophysics, Vol. 45,No. 2, pp 292-311, 1980.

30. ‘dRISTOW, Q., CONAWAY, J.G. and KILLEEN, P.G., “Application of Inverse Filtering to Gamma-Ray Logs: a Case Study,” Geophysics, Vol.49, No. 5, pp 1369-1373, 1984.

31. ATWATER, J.E., “Enhanced Resolution of Thin Zones ThroughDeconvolution of Core Spectrometric Gamma Ray Logs,” submitted toGeophysics

32. ESCH, R., “Functional Approximation,” in Handbook of Applied Mathematics, C. Pearson, (Ed.), Van Notrand Reinhold, fdew York,1974.

,-.

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-.

1:40 VERTICAL SCALE CORE SPECTRALGAMMA RAY LOG-CORE ZONE

o fJoTAssl(JM mII 1 % / CD O uRANIIJM

t . . .

0 GR API 1!

~-+-<r;;.,_, --.–,—-

–+--,-_i:. ---*

1 .+-+-

)

4

4

4

4

4

4

735

745

755

765

775

785

‘ 2 PPm/CD o THORIUM

FIGURE 1

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CALCULATED CEC VERSUS TRUE CEC

ZONE A

CORRELATION COEFFICIENT :.6438lo-

@

a

=7

~

~

~e /

u

80 6-

: /<

5

: i0

*

3.

a /

1

O,QII I 1111 1111 Ill I 1111 Ill JJ-Jll 1111 111 I Ill I0 1 2 3 4 6 6 7 8 0 10

TRUE CEC (m@100d


ZONE B

FIOURE a

C0RRELA710N COEFFICIENT= .020110

e

a

;7

:

:~ a

$/

u

a 6:

<

:u 4

:*

o *

+3

%

a / ‘

1

01 II I Ill I Ill I Ill I Ill I Ill I Iltl Ill I II II II II01 a 3 4 6 *’ 6 10

,,- ‘7RUE CEC(maQ1100dFWJRE a

-13-


CALCULATEDCEC VERSUS TRUECEC

ZONE c

CORnELAT1ON c0EFF8ClEMT =.020710

e

6

a 7— — — — — —

~

aJ e05n 6 / ‘Ill:

/

liv 4.2v

a.

2

1

on I Ii 1111 1111 II II II II II II II II II II 11 II II IL

01 2 3 4 6 e 7 8 D 10

TRuE CEC (IIWJI1OOQ1FIOURE 4


ZONES A,8,CCOMPOSITE

INDEPENDENT CORRELATIONOF ZONES

%. ZONE A

● ZONE @

0 ZONE C

10

0

s -

%1

:

.

0

:

0 6,

:6

s4-

:

IJ

3

2

00 t 2 34 s c T a

T,WE CEC (m. ollooa)ft9UFlE 6

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SPWLA TWENTY-SEVENTH ANNUAL LOGGING SYMPOSIUM, J UNE 9-13, 1986

SECTIONS OF CALCULATED CEC LOGS

ZONE B CATION ZONEEXCHANQECAPACITY

c CATIONEXGHANGECAPACITY

I

m

,-.

FI(3URE8

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CEC CORRELATION-ZONE A

3 POINT FILTER

0.-- . . . . . . . .

e

Z47

~

g e

v

zg 6

*

:

0 4

;

1-

00 1 z 3 4 6 e 7 8

TRUE CEC lmeollooo)FIWRE 7

CEC CORRELATION-ZONE A

5 POINT FILTER

CORRELATION COEFFICIENT = 0.000010

0

a

a7

8:-

0$: 6

!i:

iCJ

3

a

t

001 * * 4

TRUE CEC (mo@1100@)

FIOURE 8

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cation exchange

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