new concept of variable archie bound water exponent for ......ratio for the application of suitable...

New Concept of Variable Archie Bound Water Exponent for the Evaluation of LowResistivity Pays in Mesozoic Fluvial Reservoirs of Krishna Godavari Basin,

East Coast, India

Lalaji Yadav* and Troyee DasReliance Industries Limited, Navi Mumbai, 400701, India

[email protected]

KeywordsSeverely non Archie, Low Resistivity, Shaly Sandreservoirs, Krishna Godavari

AbstractLow Resistivity Pays of Mesozoic reservoirs ofKrishna Godavari Basin does not indicate anyparticular lithological cause of anomalous loweringof resistivity and does not fit to the application ofany conducting mineral or shaly sand models foraccurate petrophysical evaluation.

Anomalous reduction of tortuosity due to continuousinterconnectivity of micro pores of the reservoirexhibits severely non-Archie behavior with four foldreduction of formation resistivity factor againstrelatively clean sand layers. Precise computation ofwater saturation requires a pseudo-Archie methodwhere reduction of cementation ‘m’ and saturation‘n’ exponents are allowed to find their own levels totake care of anomalous reduction of formationresistivity factor. It is generally recommended to usecore measured ‘m’ and ‘n’ parameters for accuratepetrophysical evaluation, which are not available.

To ensure a consistent petrophysical interpretation,apparent in-situ values of Archie exponent of boundwater volume i.e. ‘mn’, in a simplified Archie’srelation, have been derived by combining the in-situmeasurements of resistivity and bound water volumefrom nuclear magnetic resonance log. Conventionalneutron and density log separation, showingexcellent correlation with bound water volume fromnuclear magnetic resonance log, has been used forprediction of in situ values of ‘mn’. For thecomputation of water saturation, continuous curve of‘mn’ has been generated using an empiricalrelationship evolved through the regression analysisbetween ‘mn’ and neutron density log separation.Values of apparent parameter ‘mn’ are varying in therange of 1.2 - 1.9. Its value is attaining maximum 1.9in clean sand reservoirs and 2.0 against shale beds.

Evaluation of Low resistivity pays with new methoddirectly estimates the apparent values of Archieexponent of bound water volume which serves the fit

for the purpose in situ values of cementation andsaturation exponents to compensate the anomalousreduction of formation resistivity related with artifactof pore geometry. Application of new methodologyhas resulted in a two fold increase of hydrocarbonsaturation as compared to conventional conductingmineral or shaly sand models. Water saturationvalues computed with new approach arecorroborating with the corresponding valuespredicted independently from J function heightmethod derived with core samples of the rock typeshaving similar pore size distributions or poregeometry.

IntroductionLow-resistivity pay (LRP) has been typically definedat or below the resistivity levels of the underlyingaquifers or nearby shale layers and are also referredas low resistivity low contrast (LRLC) reservoirs.Major hydrocarbon accumulations have beenproduced over the past 60 years in low resistivity,low contrast sands in the basins all over the worldviz. Argentina, Australia, Gulf of Mexico, India,Indonesia, Italy, Malaysia, Nigeria, North Sea,Philippines and Venezuela (Dolly and Mullarkey,1996, Gumilar, et al. 1996, Hassoun, et al., 1997,Turner, 1997, Worthington, 1997). For lowresistivity reservoirs an accurate determination of thepetrophysical parameters with the conventional logsis very difficult. Corresponding to different attributescontributing to the lowering of resistivity, differentinterpretation techniques are available that can beapplied to compute accurate water saturation.Identification/isolation of a particular cause oflowering of resistivity is the most fundamental forthe evaluation of LRP.

New logging technologies including modernelectrical anisotropy, magnetic resonance, elementalspectroscopy and high-resolution borehole imagescontribute significantly to solving for LRLCproblems. Recent application of nuclear magneticresonance (NMR) logging has provided a betteridentification of fluid type, grain size distributionand hydrocarbon saturation in these types of sands.Integration of different log and core measurements

11th Biennial International Conference & Exposition

Variable Archie Exponent For Evaluation of Low Resistivity Pay

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of LRP of Mesozoic reservoirs of Krishna GodavariBasin located in East Coast of India does not indicateany particular lithological cause of lowering ofanomalous resistivity and does not fit for theapplication of any shaly sand interpretationtechnique for accurate petrophysical evaluation. LRPof Mesozoic clastic reservoirs of KG basin exhibitresistivity similar to water bearing sands layers/nearby shale beds. Resistivity values vary in therange of 2-3 ohm-m and 4-5 ohm-m respectively inoil and gas bearing reservoirs and it is notdifferentiable from the nearby shale beds. Watersaturations estimated using conventional shaly sand/conduction mineral models are generally inunrealistically high range of 70-100% in relativelyclean sands with porosity of 22-28% (Figure -1) .

Figure 1: ELAN processing results using clay sand model withadditional conducting mineral in sand matrix. Nominal changes onwater saturation using results from electrical anisotropymeasurements are noticed due to either absence of sand shalelaminations or presence with identical values of Rv (green) andRh (blue) on second track

Total water volume (bulk volume water or BVW,product of porosity and Sw are easily estimated onNMR log presented in Figure-2. Clay (brown) in aswell as capillary (light yellow) bound water volumes(second track) trend in low resistivity ( ~ 4 ohm-m)reservoir, marked with red, indicates a typical trendof upward fining of grain size. Total bound watervolume is showing an upward increase fromapproximately from 5 porosity units in the bottom upto 10 porosity units in the top of the zone. Two foldincrease of water filled porosity should correspond toa fourfold decrease of in formation resistivity factor

or resistivity. However, such behavior is not seen onresistivity log which is not showing any decrease ofits values with increase of bound water volume. Itindicates that excess conduction of rock is notrelated with lithology i.e. either from kaolinite clayvolume or grain size variation or presence ofirreducible in microporosity.

Figure 2: Clay (light brown) and capillary (light yellow) boundwaters on Track-II of NMR log recorded against low resistivitypay LRP marked with red. Rt and permeability are shown onTrack-I and T2 spectrum on track-III

In this paper, based on an integrated petrophysicalanalysis of modern log data including mud log andshows, wireline formation pressure and sample tests,Nuclear Magnetic Resonance, Borehole Imaging,Electrical anisotropy and Special Core Analyses,improved concepts and workflows were developedfor the identification and quantitative evaluation oflow resistivity pays. New approach for evaluation oflow resistivity pays, where quantification is followedby identification of reservoir using formation factorratio for the application of suitable water saturationequation for the evaluation of these reservoirs.Evaluation of low resistivity pays with new methoddirectly estimates apparent values of cementationand saturation exponents for the precise evaluationof water saturation, which ensures a consistentpetrophysical interpretation. The technique is veryrobust and can be extended to the evaluation of otherfields of the world exhibiting anomalous lowresistivity related to the pore geometry and theirinterconnectivity.

Identification of low resistivity pays

Resistivity

Permeability

Shale

Sand

Conducting mineral



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Prior to defining a zone as LRP, presence of payneeds to be established from various sources, otherthan resistivity, such as mud log and shows, wirelineformation pressure and sample tests, or other testssuch as drill stem or production tests. Production anddrill stem testing could not be done separatelyagainst low resistivity pays due to higher costinvolved with deep water offshore rigs. Pressuregradient lines plotted in Figure-3, indicate that lowresistivity layers (marked with red) are charged withgas of similar density and are hydro-dynamicallyconnected with upper and lower gas bearing cleansand layers.

Figure 3: Identification of low resistivity pay (marked with Red)using pressure gradient and gas shows (yellow) on mud logs

Classification of low resistivity reservoirsClean and relatively clean water bearing reservoirsconducts electrical currents according to Archie’slaw. In case of deviations on the conditions thateither rock matrix exhibiting conductivity or verylow water salinity or both, conduction of electricalcurrents will not follow Archie’s law, and suchreservoirs are referred as non-Archie, shaly sandreservoirs. In these rocks excess conductivity can beincorporated into Archie equation as an extra rockconductivity due to non-Archie conduction, so thatC0 = Cw/ F* + Cr, Where Cr represents rockconductivity, when conduction through fluid is zero(Cw = 0).

A criterion for evaluating lithology effects can beestablished by rearranging equation (Waxman andSmits, 1968) to include as defined in Archie’sequation but expressed in terms of clay conductivityCc where Cr = Cc/F*

Co = Cw/F* + Cc/F*

Cw/F = (Cw + Cc) / F*

F*/F = (Cw + Cc) / Cw

The term F is the ratio Cw/Co, at electrolyteconductivity Cw and F is equal to the intrinsicquantity F* only if these effects are negligible at thatparticular electrolyte conductivity. In shaly sands,apparent formation factor F decreases with decreaseof Cw or salinity and shaly sands exhibits excessconduction Cc /F*. This equation shows that F*/F isequal to the ratio of total conductivity to the “clean”conductivity.

Figure 4: Reduction of formation resistivity factor i.e. F/F* ratiowith shaliness in classical shaly sand water bearing Mesozoicreservoirs of KG Basin

Worthington, 2006, classified three type of reservoirrocks as: i. Archie rocks for which F/F* 0.9, onecan use the Archie equation in such reservoirs. ii.Non-Archie rocks is defined as that for which 0.5 F/F* < 0.9. These are the conditions for applyingmost of the conventional shaly-sand equations. iii.Severely non-Archie, The reservoirs for which F/F*< 0.5 is associated with severely non-Archie effects,applicability of shaly sand equations can breakdown.

The ratio F/F* in LRP of Mesozoic reservoirssuggest that the behavior of the rocks is severelynon-Archie. The SEM and thin section studiessuggest that the rock fabric is dominated by micropores, has a high capillarity and high irreduciblewater saturation. As kaolinite is electrically inert, thewhole rock can be considered as clean sandstonedominated by micro pores with a high capillarity andhigh irreducible water saturation and which obeys



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the Archie law where bound water exponent isallowed to take its own level to match the formationresistivity factors derived from resistivity and NMRdata

New approach of evaluation using variable boundwater exponentNew approach for the evaluation of severely non

Archie low resistivity pays is capitulated infollowing steps:

Ratio F/F* is computed for the classification ofreservoir, where formation resistivity factors arecomputed as F = Rt/Rw and F* = 1/m* in waterbearing reservoirs where intrinsic value ofcementation exponent m* is presumed to be 2.0 inabsence of core measurements. In hydrocarbonbearing zone, is replaced with BVW.

BVW values from NMR log have been correlatedwith neutron density separations (DIFFND) asbound water volume indicator (Figure 5). There isexcellent correlation with following quadratic fitequation for the prediction of bound volume ofwater.Values of ‘mn’ are computed in severely non

Archie reservoirs as mn = Log (Rw /Rt)/Log(BVW), using combination resistivity and boundwater volume, BVW from NMR logs.

BVW = 0.0335 + 0.416899 DIFND -0.483995 DIFFND2

An empirical relationship has been evolvedthrough the regression between ‘mn’ and neutrondensity logs separation, DIFFND (Figure 6).

mn =1.06116+8.65DIFND–28.5DIFFND2 +30 DIFFND3

Finally water saturation value is computed usingnew values of ‘mn’ derived from separations ofneutron density logs where NMR logs are notavailable.

Validation of water saturationIn the absence of direct measurements of watersaturation on conventional core samples in lowresistivity reservoirs, core capillary measurementtechnique is probably the most practical andeconomic way to validate Sw from log data. Thereare various practical techniques for correlatingcapillary pressure curves according to rock type for aheterogeneous formation and generating field widesaturation-height function that relates capillarypressure curves to porosity, permeability or rock

type in general. The classic method is based onLeverett’s J-function (1941) approach.

Figure 5: Correlation of total bound water volume from NMR logwith neutron density log separation

Figure 6: Regression analysis of ‘mn’ derived from NMR andResistivity logs with neutron density logs separation.

Special core analysis (SCAL) measurements ofcapillary pressure, on core samples provide the mostreliable means to establish a dimensionless functionof capillary pressure, J-functions of rock types withsimilar pore geometries.Measurements of capillary pressure Pc are performedon each core plug and, after conversion to reservoirconditions, are then converted to J = 0.21645 (Pc

/cos ( values for each sample and plotted

against saturation. Where, is the interfacialtension (a fluid property is the contact angle(related to wettability and rock-fluid interaction), and is pore geometry factor for permeability Kand porosity, . The cos term was added later byRose and Bruce, 1949, to adjust for wettablility.



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For a set of samples with similar pore sizedistributions, a least squares regression analysis isthen performed using the J values as the independentvariable.

Figure 7: Regression analysis of Sw with J function derived fromcapillary pressure measurements on core samples

The best correlation is often obtained using a powerlaw equation of the form: J = a (Sw). The J-functionhas been used as a correlating group for all capillarypressure measurements using different fluid systems,but it only applies if the porous rock types havesimilar pore size distributions or pore geometry. Inthese types of rocks, the pore size and permeabilityincrease as the grain size increases. J versus Sw,plotted for two samples in gas and many samples inoil bearing reservoirs are presented in Figure-7. Eachcurve in this figure represents a sample and higherporosity-permeability samples plot towards left.Right most curves represent the rock properties closeto the low resistivity reservoirs and have been usedto derive the following water saturations and Jfunction relationship in gas and oil reservoirs:

Gas, Sw =0.6415-0.2521X+0.0316X2 –0.035X3

Oil, Sw=0.5852-0.2487X +0.023X2 -0.007X3

Where X=LOG J

Depth wise J values have been computed as J = (Pc

/cos K where Capillary pressure Pc isderived from pressure gradient measurement i.e. Pc =(w-o)gh where g is gravity constant, h is oilcolumn height above free water level,w, o are thedensities of water and oil respectively. Core derivedpermeability-porosity relationship,

K = 0.001067 Exp (52.827) has been used forpermeability estimation using log porosity. Capillarypressure of different fluids for various depths fromOWC and GOC are estimated by using averagepressure gradients obtained from MDT data as 0.12,0.25 and 0.433 psi/ft respectively in Gas, oil andwater zones.

Pc_oil = Hoil (0.433 – 0.25)Pc_gas=Hgas(0.433–0.12)Where, Hoil = Height of oil column from OWC(feet)Hgas= Height of gas column from GOC (feet)

Processing resultsProcessing results with new approach using variableArchie’s exponent of bound water volume asindicated in third track (Figure-8) has resulted inrealistic water saturations very close to thecorresponding values predicted independently from Jfunction height method.

Figure 8: Validation of water saturation estimation using newapproach with J function height method.

Small deviations are related to the facies variationsfrom core samples used for the derivation of watersaturation and J function relationship viz. relativelycleaner portions are showing lower Sw and portionswith relatively higher shaliness are exhibiting higherSw values as expected. Sw values estimated throughnew approach are in close agreements with Jfunction height method against relatively cleanreservoirs having pore geometry of the formationssimilar to the core samples. Deviations of 5-10% in

GAS

OIL



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Sw can be attributed to the variation in grainsize/shaliness as conventional core samples areavailable only in relatively clean reservoirs.

ConclusionsCore measurements of LRP of Mesozoic reservoirsindicate that kaolinite commonly occurs in the poresystem as discrete particles in the form of large flakybooklets which do not attach securely to sand grainsurfaces. Authigenic dispersed kaolinite clays aresituated within the pore system and, by virtue oftheir immense surface area relative to the detritalframework grains, have an impact on the chemicalsensitivity and petrophysical properties of thesandstone which is greatly out of proportion to theirvolumetric contribution.A rock fabric with a continuously connected systemof small pores in addition to larger pores connectedby proportionally large pore throats can result in lowresistivity pay. In these types of bimodal poresystems the capillary properties of the continuoussystems of smaller pores results in a connected poresub-system which is largely or completely watersaturated and has high capillary bound (irreducible)water. There is little that can be done to account forthis additional component of conductivity usingconventional Archie’s approach where resistivity isdirectly related to water filled porosity of the rocks.

In such case, anomalous reduction of resistivity inhas to be identified and classified based on reductionin formation factor ratio i.e. F/F*. The ratio F/F*suggests that the behavior of the rocks is severelynon-Archie. The SEM and thin section studiessuggest that the rock fabric is dominated by micropores, has a high capillarity and high irreduciblewater saturation. As kaolinite is electrically inert, thewhole rock can be considered as clean sandstonedominated by micro pores with a high capillarity andhigh irreducible water saturation and which obeysthe Archie law where bound water exponent isallowed to take its own level to match the formationresistivity factors derived from resistivity and NMRdata.The technique is very robust and can be extended forthe evaluation of other fields of the world exhibitinganomalous low resistivity related to pore geometryand their interconnectivity where applicability ofshaly sand equations breaks down.

AcknowledgmentsAuthors are thankful to the management of RelianceIndustries for giving the permission to present andpublish the paper.

ReferencesArchie, G. E., (1942). The Electrical Resistivity Log

as an Aid in Determining Some ReservoirCharacteristics, Trans., AIME, 146: 54–62

Dolly, E.D., and Mullarkey, J.C., eds., 1996,Hydrocarbon production from low contrast, lowresistivity reservoirs Rocky Mountains and Mid-Continent regions; log examples of subtle pays:Rocky Mountains Association of Geologists,Denver, Colorado, 290 p.

Gumilar, B., Adriansyah, R., Thomas, A.R., andDarmawan, B., 1996, An analysis of low-contrastpay in Telisa sands [sic] packages in centralSumatra, paper IPA96-2.2-123, in 25th annualconvention proceedings, v. 2: IndonesianPetroleum Association, Jakarta, p. 175-187

Hassoun, T.H., Zainalebedin, K., and Minh, C.C.,1997, Hydrocarbon detection in low-contrastresistivity pay zones, capillary pressure and ROSdetermination with NMR logging in SaudiArabia, SPE-37770, in 10th SPE Middle East oilshow conference proceedings, v. 2: Society ofPetroleum Engineers, p. 127-143.

Leverett, M. C., 1941, Capillary behavior in poroussolids: Transactions of the American Institute ofmining and Metallurgical Engineers, v. 142, p.152–169.

Turner, J.R., 1997, Recognition of low resistivity,high permeability reservoir beds in the TravisPeak and Cotton Valley of east Texas: Gulf CoastAssociation of Geological Societies Transactions,v. 47, p. 585-593.

Waxman, M. H., Smits, L. J. M., (1968), ElectricalConductivities in Oil-Bearing Shaly Sands,Paper 1863-A, SPE June, 107–122.

Worthington, P.F. and Pallatt, N., 1990, Effect ofvariable saturation exponent upon the evaluationof hydrocarbon saturation, Paper SPE 20538presented at the SPE 65th Annual TechnicalConference and Exhibition, New Orleans, Sept23-26, 1990

Worthington, P. F. and Johnson, P. W., 1991,Quantitative evaluation of hydrocarbonsaturation in shaly freshwater reservoirs: TheLog Analyst, v. 32, no. 4, p. 358-370.

Worthington, P. F., 2006, Quality Assurance of theEvaluation of Hydrocarbon Saturation fromResistivity Data, SPE-103075, SPE AnnualTechnical Conference and Exhibition held inSan Antonio, Texas, U.S.A., 24–27 September2006


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