m exponent

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WWW.GeoNeurale.Com January 2012 © 2012 Robert E Ballay, LLC The essence of carbonate  petrophysics is (often) pore sys tem  heterogeneity , as compared to clay  conductivity i ssues for clas tics •The foundation of the Lucia  petrophysical classification is the concept that pore-size distri bution  controls permeabil ity and  saturation •The focus of this classification is  on petrophysical properties and  not genesis  Petrophysical class ifications focu s on contemporary rock fabrics that include  depositional and diagenetic textures •To determine the relationships between rock fabric and petrophysical parameters, one must  define and classify por e space as it exists today in terms of petrophysical  properties Addition of vuggy pore space alters the manner in which the pore space is connected Courtesy of Jerry Lucia Figure 1 a: Rock Types 1 and 2 correspond to intergranular grainstone •Limestone and dolostone b: Rock Type 3 is sucrosic dolostone with intercrystalline porosity c: Rock Types 4 and 5 correspond to  moldic limestone and dolostone d: Rock Type 6 is mudstones and chalks e: Rock Type 7 is the combination of  matrix and moldic / vuggy  porosity , ie vuggy  packstone / wackestone f : Rock Type 8 is fracture / fissure  porosity Cementation Exponents in ME Carbonat e Reservoirs. J W Focke and D Munn, SPE Formation Evaluat ion, June 1987  Illustrative, generic thin sections Porosity is black Figure 2 The “m” Exponent in Carbonate Petrophysics R E (Gene) Ballay, PhD www.GeoNeurale.com In 1952  Archie stated  “In discussing the petrophysics of  limestones,  it is necessary to first classify them in a manner to portray as much as possible the essential pore characteristics  of  a reservoir.  The application of   petrophysical  relationships in limestones can be much more difficult  than  for  sandstones because of  the heterogeneity . This is due mainly to the variation of   pore size distribution.” The attribute within  Archie’s equation which represents the  pore system tortuosity  is the “m”  exponent . Complications  in carbonate formation evaluation can arise due to mixed mineralogy’s  (which affects the estimation of  total porosity) and wettability (Sweeny & Jennings)/surface  roughness  (Diederix) which drive the “n” exponent,  but  from one  perspective the “m”  exponent  can be said  to often represent  the essence of  carbonate  petrophysics. As compared to clastic petrophysics,  which is typically compromised  by clay conductivity  issues,  carbonate petrophysics  issues will in many cases revolve around proper characterization of  the  pore system, which reflects both depositional  and  diagenetic   properties. Jerry Lucia advises us to focus on petrophysical  properties,  not genesis, and we thus realize that  petrophysical   zones may  be genuinely  different  than geological   zones: Figure 1. While there are several  carbonate classification systems in the public domain (Lucia, Lønøy, etc), Focke and  Munn’s work  is  particularly  complete in that  it  illustrates each of  the  following: Figure 2.  Pore geometry per thin sections.   Laboratory “m” measurements  correlated with thin section descriptions.   Wireline methodology  for determining  “m” in the wellbore,  across 

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  • WWW.GeoNeurale.Com January2012 2012RobertEBallay,LLC

    The essence of carbonate petrophysics is (often) pore system heterogeneity, as compared to clay conductivity issues for clastics

    The foundation of the Lucia petrophysical classification is the concept that pore-size distribution controls permeability and saturation

    The focus of this classification is on petrophysical properties and not genesis Petrophysical classifications focus on contemporary rock fabrics that include depositional and diagenetic textures

    To determine the relationships between rock fabric and petrophysical parameters, one must define and classify pore space as it exists today in terms of petrophysical properties

    Addition of vuggy pore space alters the manner in which the pore space is connected

    Courtesy of Jerry Lucia

    Figure 1

    a : Rock Types 1 and 2 correspond to intergranular grainstone

    Limestone and dolostoneb : Rock Type 3 is sucrosic dolostone with intercrystalline porosityc : Rock Types 4 and 5 correspond to moldic limestone and dolostoned : Rock Type 6 is mudstones and chalkse : Rock Type 7 is the combination of matrix and moldic / vuggy porosity, ie vuggy packstone / wackestone f : Rock Type 8 is fracture / fissure porosity

    Cementation Exponents in ME Carbonate Reservoirs. J W Focke and D Munn, SPE Formation Evaluation, June 1987

    Illustrative, generic thin sections

    Porosity is black

    Figure 2

    ThemExponentinCarbonatePetrophysicsRE(Gene)Ballay,PhDwww.GeoNeurale.com

    In1952ArchiestatedIndiscussingthepetrophysicsoflimestones,itisnecessarytofirstclassifytheminamannertoportrayasmuchaspossibletheessentialporecharacteristicsofareservoir.Theapplicationofpetrophysicalrelationshipsinlimestonescanbemuchmoredifficultthanforsandstonesbecauseoftheheterogeneity.Thisisduemainlytothevariationofporesizedistribution.

    TheattributewithinArchiesequationwhichrepresentstheporesystemtortuosityisthemexponent.Complicationsincarbonateformationevaluationcanariseduetomixedmineralogys(whichaffectstheestimationoftotalporosity)andwettability(Sweeny&Jennings)/surfaceroughness(Diederix)whichdrivethenexponent,butfromoneperspectivethemexponentcanbesaidtooftenrepresenttheessenceofcarbonatepetrophysics.

    Ascomparedtoclasticpetrophysics,whichistypicallycompromisedbyclayconductivityissues,carbonatepetrophysicsissueswillinmanycasesrevolvearoundpropercharacterizationoftheporesystem,whichreflectsbothdepositionalanddiageneticproperties.JerryLuciaadvisesustofocusonpetrophysicalproperties,notgenesis,andwethusrealizethatpetrophysicalzonesmaybegenuinelydifferentthangeologicalzones:Figure1.

    Whilethereareseveralcarbonateclassificationsystemsinthepublicdomain(Lucia,Lny,etc),FockeandMunnsworkisparticularlycompleteinthatitillustrateseachofthefollowing:Figure2.

    Poregeometryperthinsections.

    Laboratorymmeasurementscorrelatedwiththinsectiondescriptions.

    Wirelinemethodologyfordeterminingminthewellbore,across

  • WWW.GeoNeurale.Com January2012 2012RobertEBallay,LLC

    Interparticle vs moldic porosity and Sw

    J W Focke and D Munn: Cementation Exponents in Middle Eastern Carbonate Reservoirs, SPE Formation Evaluation 2 (1987) : 155-167See Also A M Borai: A New Correlation for the Cementation Factor in Low-Porosity Carbonates, SPE Formation Evaluation 2 (1987): 495-499Schlumberger Technical Review, Volume 36 Number 3

    Saturation Variations

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    0.60

    0.80

    1.00

    1.5 1.7 1.9 2.1 2.3 2.5

    Saturation Exponent

    Wat

    er S

    atur

    atio

    n

    Boxing in the uncertainty for specific criteria

    = 0.2, Rw@FT = 0.1 ohm-m, R = 50 ohm-m At each value of 'n', a range (1.5 - 4.0) of 'm' values are displayed in steps of 0.25

    m = 3.50

    m = 3.00

    m = 2.50

    m = 2.00

    m = 1.75

    Pore Geometry Effects on Sw

    Figure 3

    Dots, ambient pressureOpen circles, reservoir pressure

    1.9 < n < 2.1

    Middle East Carbonate Sw calculated with both constant and variable exponent

    Variable (high m) exponent evaluation consistent with water test in lower zone

    Schlumberger Technical ReviewSeeking the Saturation Solution M. Watfa: Middle East Well Evaluation Review No. 3 (1987)

    Where m ~ 2.0 2.5, calculations and test agree

    Across the water test m approaches 3.5

    Failure to recognize this yields Sw(Actual) ~ Sw(m=2) / 0.25 orSw(Actual) ~ 4 * Sw(m=2)

    Sw calculates good but Test is water!!

    Figure 4

    boththewaterlegandhydrocarboncolumn.

    Comparisonofwirelinedeterminedmandlabdeterminedm.FockeandMunnfindthatthedifferencebetweenaninterparticleandvuggyporesystemcanbeaslargeasanmof~2versusanmof~4,correspondingtoanSwuncertaintyof~20%versus~75%:Figure3.

    Theconsequencescanbedevastating:anintervalofhighresistivity(apparentlypay)maybenothingmorethanrelativelytortuous,waterfilledporesystem.

    Oneapproachtothisuncertaintyistocombine

    anonArchietool(suchasthedielectric)withaconventional(shallowreading,sincethedielectricisalsoshallow)resistivitymeasurement,andwiththismultiplicityofmeasurementsdeducewhatthefootbyfootmisinthewellbore:Figure4.

    Anotheroptionmightbetopartitiontheporesystemwithmoderntools(Gomaaetal,Ramamoorthy,etal,etc)andtothenindependentlyestimatethecorrespondingfootbyfootmwithsomekindofelectricalcircuitmodel(Aguilera,Wang&Lucia,etc).

    Anattractionofamathematicalrepresentationofthemexponentisthatwhatifcalculationscanbedone,toascertainthe

  • WWW.GeoNeurale.Com January2012 2012RobertEBallay,LLC

    Comparison of Empirical Models for Calculating the Vuggy Porosity and Cementation Exponent of Carbonates from Log Responses. Fred P. Wang and F. Jerry Lucia

    In the graphic at right, cementation exponents calculated by the Archie equation (thick black line - mres ) are compared with those from SPI/Nugent, Nurmi /Asquith, Lucia, modified Myers, and Dual Porosity.

    Cementation Exponent Models vs Wireline mm(Dual Porosity) ~ m(Archie)

    Figure 5

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    0 0.1 0.2 0.3 0.4

    RelativeUncertainty

    Porosity

    RelativeContribution ToSwUncertainty

    a

    Rw

    Phi

    m

    n

    Rt

    Below: Illustrative (Chen & Fang) Best Estimate of each parameter, with corresponding individual uncertainty, and associated relative uncertainty on Sw(Archie).

    Right: Relative impact on Sw(Archie) uncertainty of m & n, across a range of porosity values, for a fixed Phi uncertainty.

    Attribute Uncertainties Specified IndividuallyLight Green Cells require User SpecificationLight Blue Cells are calculated results

    Individual Best Relative UncertaintyAttribute Uncertainty Estimate On Sw(Archie)a 0.0% 1.00 0.0000Rw 4.4% 0.02 0.0019Phi 15.0% 0.20 0.0900m 10.0% 2.00 0.1036n 5.0% 2.00 0.0480Rt 1.0% 40.00 0.0001Sw 11%Sw^n 1%Sw^n=0.367 is an inflection point

    After C. Chen and J. H. Fang. Sensitivity Analysis of the Parameters in Archies Water Saturation Equation. The Log Analyst. Sept Oct 1986

    Identifying the Biggest Bang for the Buck, in Improved Sw Estimation

    Figure 6

    rangeofestimatescorrespondingtoarangeofinputuncertainties(uncertaintyin,forexample,theporositypartition).

    Regardlessofwhatapproachisusedtoestimatethewellborem,duediligencerequiresthatateveryopportunitytheresultbecomparedagainsttheinferredArchieestimateinthewaterleg[whereSw=1andm=log(Rw/Ro)/Log(Phi)]:Figure5.

    Weshouldfurthermorenotlosesightofthefactthattheremaybeintervals,particularlyinthevicinityofthetransitionzone,acrosswhichtheArchiecalculationissimplynotvalid(Griffithsetal).

    WheretoFocusAlthoughthemexponentmay(logically)bethefirstissuethatcomestomindincarbonateevaluation,itdoesnotalwaysdominatetheuncertaintyinSwestimates.Therearetwobasicwaysofidentifyingwherethefocusshouldbe:Figure6.

    TakethevariouspartialderivativesofArchiesequation,andcomparemagnitudesforlocallyspecificvaluesanduncertainties.

    MonteCarlosimulation.

    Thetwooptionscomplementoneanotherinthatthederivativesareeasytocodeintoaspreadsheetor

  • WWW.GeoNeurale.Com January2012 2012RobertEBallay,LLC

    0.00

    0.10

    0.20

    0.30

    0.40

    0.50

    0 0.1 0.2 0.3 0.4

    RelativeUncertainty

    Porosity

    RelativeContribution ToSwUncertainty

    a

    Rw

    Phi

    m

    n

    Rt

    At 20 pu, formation evaluation should focus on improved porosity and m estimates, with n of relatively less importance.

    If porosity rises to 30 pu, however, improved porosity estimates become more important with m and n having similar, and less, impact.

    As porosity drops to 10 pu, it is the pore connectivity (m) that begins to dominate the accuracy.

    The Porosity Dependence

    The relative importance of m and n depend not only upon their specific uncertainty, but also upon the porosity of the interval in question; there is a link

    Figure 7

    After C. Chen and J. H. Fang. Sensitivity Analysis of the Parameters in Archies Water Saturation Equation. The Log Analyst. Sept Oct 1986

    0.00

    0.10

    0.20

    0.30

    0.40

    0.50

    0 0.1 0.2 0.3 0.4

    RelativeUncertainty

    Porosity

    RelativeContribution ToSwUncertainty

    a

    Rw

    Phi

    m

    n

    Rt

    Light Green Cells require User SpecificationLight Blue Cells are calculated results

    Individual Best Relative UnAttribute Uncertainty Estimate On Sw(Archa 0.0% 1.00 0.0000Rw 4.4% 0.02 0.0019Phi 15.0% 0.20 0.0900m 10.0% 2.00 0.1036n 5.0% 2.00 0.0480Rt 1.0% 40.00 0.0001Sw 11%Sw^n 1%0.367 is a logarithmic inflection point

    0.00

    0.10

    0.20

    0.30

    0.40

    0.50

    0 0.1 0.2 0.3 0.4

    RelativeUncertainty

    Porosity

    RelativeContribution ToSwUncertainty

    a

    Rw

    Phi

    m

    n

    RtLight Green Cells require User SpecificationLight Blue Cells are calculated results

    Individual Best Relative UnAttribute Uncertainty Estimate On Sw(Archa 0.0% 1.00 0.0000Rw 4.4% 0.20 0.0019Phi 15.0% 0.20 0.0900m 10.0% 2.00 0.1036n 5.0% 2.00 0.0108Rt 1.0% 40.00 0.0001Sw 35%Sw^n 13%0.367 is a logarithmic inflection point

    If the water were fresher, say Rw = 0.2 instead of 0.02, n diminishes in importance as compared to both the amount of porosity, and its connectivity (m).

    After C. Chen and J. H. Fang. Sensitivity Analysis of the Parameters in Archies Water Saturation Equation. The Log Analyst. Sept Oct 1986

    The Rw Dependence

    The Rw Dependence

    Figure 8

    petrophysicals/wpackage(forfootbyfootdisplay),whiletheMonteCarlogivesinsightintotheupanddownsides(with95%confidence,theuncertaintywillbelessthanhighlowcalculations).

    UsingChenandFangsparameterstoillustratethedifferentialapproach(Figure6)wenotethatasporosityvaries,therelativeimportanceofmandnalsovaries.Thatis,theimportanceofasingleattribute,mforexample,islinkedtothemagnitudeofother

    attributes.

    Inthecaseathand,a20puformationevaluationshouldfocusonimprovedporosityandmestimates,withnofrelativelylessimportance.Asporositydropsto10pu,theporeconnectivity(m)beginstodominatetheaccuracy:Figure7.

    Thementalimagethatemergesisthatasporositydecreases,itsconnectivity(orefficiency)becomesincreasinglyimportant.

    Weretheformationwaterresistivitytochange,itsquitepossiblethatthefocusshouldalsochange:Figure8.

    Insummary,eachsituationshouldbeevaluatedwithitslocallyspecificparametersanduncertainties,andourfocus(andbudget)appliedaccordingly.

  • WWW.GeoNeurale.Com January2012 2012RobertEBallay,LLC

    Generalized slope-intercept straight line equationy = m * x + b

    Log(FF) = - m * Log( ) + bAt = 100 % , Log ( ) = Log(1) = 0

    Leaving Log(FF) = Log(1) = 0 b = 0 to give Log(FF) = - m * Log( )

    At = 10 % , FF = 100Log(100) = 2.0 = - m * Log (0.1) = m

    to give m = 2.0

    1

    Schlumberger Technical Review, Volume 36 Number 3G E Archie: The Electrical Resistivity Log as an Aid in Determining Some Reservoir Characteristics. Petroleum Transactions of the AIME 146 (1942): 54-62.

    The Key to working with the Log-Log displays is to think in terms of decades and take logarithms

    when working with numerical values

    Figure 9

    mandCarbonatePoreSystemsArchiemeasuredtheporosity,permeabilityandresistivityofbrinesaturatedcarbonateandnonshalysandsamples,acrossarangeofbrinesalinities,toobservealinearrelationbetweenRo(brinesaturatedsampleresistivity)andRw(brineresistivity).

    ThisresistivityratioisknownastheFormationFactor,where

    FF=R(sample)/R(brine)=1/mArchiecommentedthatmwasabout1.3inunconsolidatedrockandincreasedasthecementationincreased.Atypicalformationstartingpointvalueformis2.0.

    ItwasHubertGuyodwhogaveusthetermcementationexponent,andwhoincidentally,alsosuggestedtheoriginalnameoftheSPWLAJournal(TheLogAnalyst).

    Themexponenttypicallyinvolvesaloglogdisplayofthebasicdata,andassuchislessintuitivethanasimplelineardisplay.Semilogandloglogdisplaysarecommoninmanypetrophysicalendeavors(phiperm,etc),however,anditsusefultobeabletodrawourownlinethroughthedataanddeducethecorrespondingexponent.TheKeytoworkingwiththe

    LogLogdisplaysistothinkintermsofdecadesandtakelogarithmswhenworkingwithnumericalvalues.

    SketchingourlinethroughArchies1942dataanddrawingupontheslopeinterceptformulationofalinearrelation,revealsthatm~2.0isindeedareasonablestartingpointwiththatdataset:Figure9.

    WhileitwasMrGuyodwhogaveustheterminology

    cementationexponent,itappearsthatwederivethemnomenclaturefromthemathematiciansslopeinterceptrepresentationofastraightline,whereintheslopeisdenotedbym:y=m*x+b.

    Lookingaheadjustabit,totheResistivityIndex(incontrasttotheFormationFactor),itwouldfurtherseemthatournnomenclaturemayhavearisenalphabetically,sincenfollowsm.

    Interestinglyfromahistoricalperspective,thiskindofrelationshiphadbeenpostulatedearlierbySundberg,butwithoutthesupportingdata.

  • WWW.GeoNeurale.Com January2012 2012RobertEBallay,LLC

    Archies 1947 Data - Sandstone and Limestone

    G E Archie: Electrical Resistivity as an Aid in Core Analysis Interpretation, AAPG Bulletin 31 (1947): 350-366Schlumberger Technical Review, Volume 36 Number 3

    Suggested to Archie that permeability (molecular fluid flow) and resistivity (ionic movement) were different

    Formation Factor (Rformation / Rbrine )

    Figure 10 Conceptually,giventhatbothrepresentaflow,onemightexpectastrongerrelationshipbetweenresistivityandpermeability,ascomparedtoresistivityandporosity.Archieaddressedthisbyplottinghismeasurementsbothways:Figure10.

    Perhapssurprisingly,thevariousFormationFactormeasurementsconvergemuchbetterwhendisplayedagainstporosity,thanagainst

    permeability,promptingArchietosuggestthatmolecularfluidflow(permeability)andionicmotion(current)weredifferent.ThosewhohaveworkedbothIG/IXandchalksystemsarealreadyawareofthis,havingnoticedthatthemforthetwoverydifferentpermeabilitiescanbothbeabout2.

    Verweretalhaveperformedadigitalimageanalysisofthinsectionsrepresentingcarbonateplugsuponwhichresistivitymeasurementsweremade.Threeattributeswererecognizedasplayinganimportantrole.

    Perimeteroverarea:twodimensionalequivalenttotheporesurface/porevolumeratio.

    Dominantporesize:theupperboundaryofporesizeswithwhich50%oftheporosityonthethinsectioniscomposed.

    Microporosity:calculatedasthedifferencebetweentheobservedmacroporosityinDIAandthemeasuredporosityfromtheplugsample.

    Theirmeasurements,nicelyillustratedwithaccompanyingthinsections,demonstratethatinadditiontoourintuitiveexpectations,

    sampleswithhighresistivitycanhavehighpermeability, sampleswithlowpermeabilitycanhavea(relatively)lowmexponent.

    AsArchiepointedoutin1952,carbonateporesystemsmaybequitevariable,causinganm=2calculationtobenonrepresentative.WyllieandGregoryboundedthemexponentforarangeofbeadpacksconsistingofunconsolidatedandcementedspheres,viachemicalflushes,andfoundtherelationbetweenformationfactorandporositycouldinvolveanadditionalparameter,C,whichdifferedfromunity.

  • WWW.GeoNeurale.Com January2012 2012RobertEBallay,LLC

    Wyllie and Gregory constructed bead packs with varying degrees of cementation

    The baseline represents a formation of unconsolidated spheres

    This data prompted them to propose the relation

    FF = C / mC was a formation dependent constant

    m ~ 1 for unconsolidated spheres

    m ~ 4 for cemented bead pack

    M R Wyllie and A R Gregory: Formation Factors of Unconsolidated Porous Media: Influence of Particle Shape and Effect of Cementation, Petroleum Trans of the AIME (1953): 103-110. Schlumberger Technical Review, Volume 36 Number 3

    Figure 11Archie commented that m was about 1.3 in unconsolidated sand and became higher as cementation increased

    Cementation Exponents in Middle Eastern Carbonate Reservoir. J W Focke and D Munn, SPE Form Evaluation, June 1987

    Geological descriptions of hundreds of samples reveal a systematic relation between Rock Type and Archies m exponent

    Rock with a more tortuous and/or poorly interconnected porosity (moldic) display well-defined trends of increasing m with increasing porosity

    The additional moldic porosity is less effective at electrical conduction

    In some rock m is found to rise from 2 @ 5 pu, to 5.4 @ 35 pu

    m variations, within a specific Rock Type, can be reduced by segregating the samples of a specific Rock Type into Permeability Classes

    Figure 12

    Rock Type 4, the moldic limestone grainstone, represents a diagenetic inversion whereby the original porosity (between the grains) was filled with cement, and the original grains were dissolved to form the current porosity

    Symbols refer to different wells

    FF=R(sample)/R(brine)=C/mCisformationdependent,andtherangeofmexponentswasfoundtobem~1for

    unconsolidatedbeadsm~4forcementedbeads:Figure11.

    FockeandMunnthenconductedadetailedstudyofmmeasurementsonactualcarbonatesamples,supportedwiththinsectiondescriptionstofindsystematicrelationsbetweentheporositytypeandm.

    Whiletheintergranular/intercrystallineporesystemhadm~2(solongas>5pu),consistentwithArchies

    earlierlabwork,vuggyporesystemscouldexhibitanmthatreached5:Figure12.

    TheirRockType4,representingadiageneticinversioninwhichOriginalPorosityRockandOriginalRockPorosityisanexampleofwhereanincreaseinporositycorrespondstoanincreaseinvuggyporositycontent.Becausethevuggyporosityislessefficientatelectricalconduction,themexponent(counterintuitively)risesasporosityincreases:Figure13.

  • WWW.GeoNeurale.Com January2012 2012RobertEBallay,LLC

    Rock Type 4, the moldic limestone grainstone, represents a diagenetic inversion whereby the original porosity (between the grains) was filled with cement, and the original grains were dissolved to form the current porosity

    Perm Class 1: Perm < 0.1 md

    Perm Class 2: 0.1 md < Perm < 1 md

    Perm Class 3: 1.0 md < Perm < 100 md

    Perm Class 4: 100 md < Perm

    Moldic Rock

    1

    2

    3

    4

    5

    0 5 10 15 20 25 30 35Porosity

    Cem

    ent E

    xpon

    ent

    RT4/PC1RT4/PC2RT4/PC3RT4/PC4

    m vs PorosityRock Type 4: Classes 1, 2, 3, 4

    Figure 13

    Cementation Exponents in Middle Eastern Carbonate Reservoir. J W Focke and D Munn, SPE Form Evaluation, June 1987

    Fracture porosity has an effect opposite to vuggy porosityProvides a conductive conduit => lowers m

    m can be estimated with Charts

    R Aguilera: Analysis of Naturally Fractured Reservoirs from Sonic and Resistivity Logs, SPE 4398, Journal of Petroleum Technology 26 (1974)R Aguilera: Analysis of Naturally Fractured Reservoirs from Conventional Well Logs, SPE 5342, Journal of Petroleum Technology 28 (1976)Schlumberger Technical Review, Volume 36 Number 3

    Illustrative calculation

    is the fraction of porosity that is fracture

    Phi(Total) ~ 20 pu ~ 50 %m ~ 1.35

    Figure 14

    Althoughextreme,diageneticinversionisreportedinotherstudies,forexampleEberlietal,whoillustrateitwiththinsectionsanddescribetheprocessastheoriginalgrainsaredissolvedtoproduceporesastheoriginalporespaceisfilledwithcementtoformtherock

    FockeandMunnnextnoticedthatthecorrelationbetweenmandporositycouldbe

    improvedbybreakingthatRockTypeintopermeabilityclasses,eachofwhichcorrespondedtodiageneticallyinvertedrock,butwithdifferentpermeabilities.Weshallreturntothedifferentmvstrendsassociatedwiththedifferentpermeabilityclasses,withinthecontextofadigitalmexponentmodel,shortly.

    Fractureporosityhasaneffectoppositetovuggyporosity,conceptuallyformingakindofshortcircuit,whichisrepresentedmathematicallybyadecreaseinvalue:Figure14.

  • WWW.GeoNeurale.Com January2012 2012RobertEBallay,LLC

    The Dual Porosity Cementation Exponent model follows from a simple two component (intergranular and vuggy porosity) electrical model

    1/R(equivalent) = 1/R1 + 1/R2 = C0 = C1 + C2

    Each component satisfies Archies relation between resistivity and formation factor

    Resistivity = Rw * FF Conductivity = Cw / FFFormation Factor is related to porosity as FF = a / m

    The two component parallel circuit equation is then

    C0 = Cw [1/FF1 + 1/FF2]

    C0 = Cw [(1)m(1) / a(1) + (2)m(2) / a(2)]Now take a(1) as 1.0, m(2) as 1 and allow a(2) to vary from 1 to infinity [av(2) represents the tortuosity of the vuggy partition]

    intergranular vuggy

    Figure 15

    Comparison of Empirical Models for Calculating the Vuggy Porosity and Cementation Exponent of Carbonates from Log Responses. Fred P. Wang and F. Jerry Lucia

    Type I formula: Assuming that mv is 1 and that av varies from 1 to infinity, we can write the parallel circuit equation as below

    The deduction of the net effective m from the conductivity equation follows from(relative to the simple Archie relation)

    Ro = Rw / ( m) => Co = Cw * ( m) Take logarithm of Co - Cw equation

    log(Co) = log(Cw) + m log()Following exhibit

    Details following

    exhibit

    Figure 16

    Comparison of Empirical Models for Calculating the Vuggy Porosity and Cementation Exponent of Carbonates from Log Responses. Fred P. Wang and F. Jerry Lucia

    DigitalmExponentModelWithintheLuciasystem,vuggyporosityiseverythingthatisnotinterparticle,andincludesbothtouchingvugs(fractures,etc)andseparatevugs(moldic,intraparticle,etc).Whiletherearechartsavailabletoestimatem,asafunctionofvuggyporositycontent,forthevariousscenarios,itwouldbeadvantageoustohaveadigitalmodel.

    Thereareseveraldigitalmodelsavailable,andhereweuseWang&Luciaforillustrativepurposes,because:

    Itisbaseduponasimplecircuitmodelthatiseasytofollowforthosenotparticularlycomfortablewithelectricalcircuittheory,

    Itallowsforbothtouchingandseparatevugs,andeverythinginbetween, WangandLuciaincludedindependentQCchecksontheviabilityoftheirmodel,

    WangandLuciarepresentvuggyrockasatwocomponent,parallelcircuit:Figure15.

    Eachcomponent(independently)satisfiesArchiesequation,andtheythensimplifytheresultingnetconductivityexpressionbysettingthemofthevuggyfractiontobe1andrepresentingthetortuosityofthevugs(betheytouching,separateorsomethinginbetween)withaparameterav:Figure16.

  • WWW.GeoNeurale.Com January2012 2012RobertEBallay,LLC

    Type I formula: Assuming that mv is 1 and that av varies from 1 to infinity, we can write the parallel circuit equation as below (details in exhibits following)

    The deduction of m from the conductivity equation follows from (relative to the simple Archie relation)

    Ro = Rw / ( m) => Co = Cw * ( m) log(Co) = log(Cw) + m log()

    m log() = log(Co) - log(Cw) = log(Co / Cw) = log [ ]

    m = log(Co / Cw) / log() = log [ ] / log()

    Figure 17

    Comparison of Empirical Models for Calculating the Vuggy Porosity and Cementation Exponent of Carbonates from Log Responses. Fred P. Wang and F. Jerry Lucia

    This indicates that equation 30 can be used to model reservoirs with separate vugs, touching vugs, and fractures using appropriate values of av.

    av represents the connectivity, or lack thereof, of the vuggy portion of the pore system

    Figure 18

    Thisleavesthemwithanexpressionforthenetcementationexponentasafunctionofthetotalporosity,theporositypartition,theexponentoftheinterparticlefraction(mip)andtheconnectivityofthevuggyfraction(av):Figure17.

    Withthisdigitalmodelinhand,duediligencerequiresthatitbetested,withonesuchtestbeingacomparisonofthecalculatedmtothatinferredfrom

    Archiesequationinthewaterleg,Figure5,wheretheyfindthatanappropriatechoiceofavresultsinamatch.

    Whilethereisatendencytothinkofnonfracturevugsasseparate,withoutcontributiontopermeability,aliteraturesearchwillrevealinstancesofthepermeabilityactuallyincreasing,withthepresenceofvuggycontent.Thisbehaviorbringsforwardtheimportanceofparameterav,whichisavailabletorepresentsuchasituation.

    WangandLuciaalsotestedtheirmodelinsuchasituation,drawinguponMeyersdata,wheretheyagainfoundthatalocallyappropriatechoiceofavbroughtmeasurementsandestimatesintoagreement:Figure18.

    Theattractionofadigitalmodelisthatitallowswhatifcalculations.Suppose,forexample,avisualexaminationofcoreindicatesthatabout1puofvuggyporosityispresent,dispersedamongstthematrixporosity.Ifthatvuggyporosityisnotwellconnected(ieav>>1)andthetotalporosityis~5puor

  • WWW.GeoNeurale.Com January2012 2012RobertEBallay,LLC

    So long as ~ 5 pu and greater, only at av ~ 1 does a small (v ~ 1 pu) cause the Cementation Exponent to differ from mip = 2.0

    Dual-porosity Model / What If Characterizations

    0

    1

    2

    3

    4

    0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35

    Cem

    ent E

    xpon

    ent

    Total Porosity [ Phi(v)=0.01 ]

    Dual Porosity / Type 1

    av=1

    av=10

    av=100

    av=1000

    ip + v = 2 pu

    0

    1

    2

    3

    4

    0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35

    Cem

    ent E

    xpon

    ent

    Total Porosity [ Phi(v)=0.05 ]

    Dual Porosity / Type 1

    av=1

    av=10

    av=100

    av=1000

    ip + v = 6 puSo long as ~ 10 pu (or more) and the vugs are not present as fractures (or connected vugs), an m of ~ 2.5 would be a reasonable starting point.

    Figure 19

    Monte Carlo Dual-porosity Model What If Characterizations

    The Monte Carlo method relies on repeated random sampling to model results

    Advantages of Monte Carlo include

    any type of distribution can be used to characterize the uncertainty distribution of any parameter

    normal, log normal, etc

    insight is gained into the upside and downside

    0

    100

    200

    300

    400

    500

    600

    1.00 1.20 1.40 1.60 1.80 2.00 2.20 2.40 2.60 2.80 3.00

    Frequency

    DualPorosity"m"

    MonteCarloDistribution

    "m"DualPhi

    0

    1

    2

    3

    4

    0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35

    Cement Exponent

    Total Porosity [ Phi(v)=0.05 ]

    Dual Porosity / Type 1

    av=1

    av=10

    av=100

    av=1000

    Figure 20

    more,thedualporositymodelwouldindicatethataneffectivemofabout2isareasonablestartingpoint:Figure19.

    If,however,that1puispresentintheformofwellconnectedvugs(fractures),thenav~1andtheeffectivembecomesmuchmoresensitivetotheporositypartitionandconnectivity.

    Nextconsideranintervalwithabout5puofvuggyporosity(Figure19,again),withamatrixcementationexponentof2.Solongasthetotalporosityis10puorgreater,areasonableinitial

    valueoftheeffectivemwouldbeabout2.5,solongasthevuggyportionisnotwellconnected.

    Buildinguponthisconcept,werealizethatifitispossibletopartitionporosity,footbyfootinthewellbore,thenonemayalsocalculatemfootbyfootandusethatexponentvaluetothenestimateSw.Insuchasituation,itwouldbeadvisabletoseekoutawaterintervalatthefirstopportunityandcomparetheresultingSw(whichishopefullycloseto100%)withthatdeducedfromaninversionofArchie(asWang&Luciadid,inFigure5),forvalidationpurposes.

    IfthecalculateddualporosityexponentisafairrepresentationoftheinvertedArchiem,thentheevaluationofvuggyintervalshingesupontheaccuracyoftheporositypartition,whichmayinfactbeahurdle.Limitationsthatwillariseare,

    theimagelogwillbecompromisedifthevugsizeislessthanthebuttonresolution,about35mm,

    incarbonatestheNMRT2willlosetheporesizerelationatporebodysizesofabout50100um.

  • WWW.GeoNeurale.Com January2012 2012RobertEBallay,LLC

    Matrix has a relatively uniform amount of interparticle porosity (the background), with variable amounts of vuggy porosity, with different degrees of connectivity

    mip = 2.0, ip & av constant across range of v

    Moldic Rock

    1

    2

    3

    4

    5

    0 5 10 15 20 25 30 35Porosity

    Cem

    ent E

    xpon

    ent

    RT4/PC1RT4/PC2RT4/PC3RT4/PC4

    Focke & Munns DataRock Type 4, Perm Classes 1 => 4, a moldic limestone grainstone: representing a diagenetic inversion whereby the original porosity (between the grains) was filled with cement, and the original grains were dissolved to form the current porosity

    Dual Porosity / Type 1

    1

    2

    3

    4

    5

    0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35

    Total Porosity [ Phi(ip)=0.01 ]

    Cem

    ent E

    xpon

    ent

    av=1

    av=10

    av=100

    av=1000

    ip + v = 2 pu

    The Dual Porosity Model has captured the essential trends of the independent Focke & Munn data.

    The Dual Porosity Model vs Lab Data

    Figure 21 Thereisyetanotheradvantageofexpressingthevuggyporesystemexponentinmathematicalform:itbecomespossibletoperformaMonteCarlosimulation:Figure20.

    Nowweareabletoaccountforuncertaintyinthevariousinputs(theporositypartition,asanexample),andcharacterizetheBestEstimateintermsofprobabilities.Thatis,ratherthangowithahigh/lowestimate,onecanidentify(for

    example)95%oftheMCdistribution.Inmanycaseswewillfindthat,ifwecanaccepttwostandarddeviationsofuncertainty(95%),thelikelyhigh/lowvaluesarenotsoextremeasthepossiblehigh/low.Thisisbecause,ingeneral,itisunlikelythatallthehigh(orlow)inputvalueswilloccursimultaneously.

    Theprecedingillustrationsrepresentafixedvuggyportioninthepresenceofmoreorlessmatrixporosity.Itisalsopossiblethatmostoftheporosityisintheformofvugs,withsomesmallamountof(background)matrixporosity:Figure21.

    Thatis,insteadofaconstant1pu(or5pu)ofvuggyporosity,asthetotalporositygoesupanddown(Figure19),onemighthaveasmallamountofinterparticleporosity,withmoreorlessvugspresent.Thedualporositymodelexponenttrendsarenowverydifferent,becausethebulkoftheporosityisnotefficient.

    Solongasthevugsarenotconnected,Figure21revealsatrendofincreasingm,withincreasingporosity.Asavvariesfromslightlyconnected(av~10)toseparate(av~1000),thedifferenttrendsseparate,andexhibitapatternverysimilartowhatFockeandMunnfoundexperimentally.

    FockeandMunnsRockType4(diageneticallyinverted),withdifferentpermeabilityclasses,canberepresentedwiththedualporositymodel.Atasimplelevel,theavvaluescorrespondtothechokingoffoftheporethroats,whichbothreducespermeabilityandincreasesm.

    Itisimportanttorealizethat,conceptually,someporesystemsmaynotsatisfytheparallelcircuitassumptionandthatadditionallyinsomereservoirstheporesystemisatripleporositysystem,notdual.Insuchasituation,thisparallelcircuitdualporositymodelisnotgoingtobesufficient.

  • WWW.GeoNeurale.Com January2012 2012RobertEBallay,LLC

    Cementation Exponents in Middle Eastern Carbonate ReservoirsJ W Focke and D Munn, SPE Formation Evaluation, June 1987

    m(EPT) & m(core), foot by foot, with the two m estimates compared in crossplot in later graphic

    Immobile oil in black, movable oil shaded, both as a fraction of porosity, calculated with Schlumbergers Global package

    MoldicIG / IX

    Upper Interval

    m from logs, foot-by-foot,

    compared to core

    Figure 22

    mfromnonArchieTechniquesIftheporesystemcanbepartitioned,amathematicalmodelofthemexponentwillallowonetothenevaluatethehydrocarboncolumnwithvariablem.Analternativeapproachistoincludeanadditionaltoolinthesuite,whichwhencombinedwitharesistivitymeasurement,allowsonetodeducethelocalm,andtothenusethatmintheinterpretationofthedeepresistivity.

    FockeandMunncombinedthedielectriclogwithanRxomeasurementinjustthisway,to

    calculatemfootbyfootinthehydrocarboncolumn, comparethewellboremestimateswithlabm.

    Althoughtheconceptisstraightforward,FockeandMunnwerecarefultopointoutkeyissuesthatmustbekeptinmind.

    TheevaluationrequiresthatthedielectricbepairedwithroutineporosityandRxotools,whichhaveagreaterdepthofinvestigationandlessverticalresolution.Theyarethenreflectinga

    largervolumeofreservoirthanisthedielectric.

    Rxomayalsobereflectingamixofmudfiltrateandformationbrine.Ifso,aneffectivevalueRmfeshouldbeused.

    Archiessaturationexponentisassumedtobe2.0andcarbonatescanassumenonwaterwetvalueswithn>2.0.

    Intheirillustrativewell,twoporesystemsarerecognized,moldicandIG/IX:Figure22.

    Asexpected,themoldicporosityexhibitsanincreasedm,andreaches~3.5inplaces,asseenwithbothlabdataandthedielectricbasedestimate.

  • WWW.GeoNeurale.Com January2012 2012RobertEBallay,LLC

    Wireline m(EPT) vs Laboratory m(core) are in general agreement

    m and from corem from logs vs from logsCementation Exponents in Middle Eastern Carbonate Reservoirs J W Focke & D Munn, SPE Form Evaluation, June 1987

    Figure 23

    Similar Trends

    Labandwirelinecanalsobecomparedviacrossplot.Recognizingthedifferentvolumesofinvestigation,andattemptingtocompensate,FockeandMunncrossplotmversusporosityforcore,andforlog:Figure23.

    Inthemoldicintervals,thetworesultsdisplayanalmostidenticaltrendofincreasingmas(moldic)porosityincreases.

    RasmusandKenyonprovideyetanother

    illustrationofthecontributionthatadielectriclogcanmakeinthepresenceofoomoldicporosity.

    InthetimesinceFockeandRasmus,significantadvanceshavebeenmadeindielectricmeasurements,andtheynowoffermoresophisticatedoptions(ZappingRocks.RomuloCarmona,etal.OilfieldReview.Spring2011.).

    SummaryIn1952Archiepointedoutthecomplicationsthatarisewithcarbonateporesystems,whichcanresultintortuouswaterfilledporesystemshavingaresistivitysimilartoaninterparticleporesystemthatishydrocarboncharged.Inonesensethen,andrecognizingthatothercomplicationscanbepresent,thecementationexponent(whichrepresentstheporesystemtortuosity)representstheessenceofcarbonatepetrophysics.

    WyllieandGregoryboundedthemwithlaboratorybeadpackstudies,findingthatinapackofunconsolidatedbeadsm~1,whilem~4inachemicallycementedpack.FockeandMunninterpretedhundredsofcarbonateformationfactormeasurements,withinthecontextofthinsectiondescriptions,tofindasystematicrelationbetweenRockTypeandm.

    Inthecaseofmoldicporosity,FockeandMunnfoundthatmsystematicallyincreasesastotalporosityincreases:theadditionalporosityissimplynoteffectiveintheelectricalconductionsense.

  • WWW.GeoNeurale.Com January2012 2012RobertEBallay,LLC

    Petrophysical Characterization of Permian Shallow-Water Dolostone. M H Holtz, R. P. Major. SPE 75214, 2002http://www.beg.utexas.edu/mainweb/presentations/2002_presentations/holtz_spe0402ab.pdf

    Pore geometries control the interrelationship of petrophysical properties. The three most important pore-geometry characteristics are

    amount and types of pores or shapeinterconnectedness of pores (tortuosity)size of interconnecting pore throats

    Various m exponents as a function of vuggy porosity ratioNote the Myers trend is relatively flat: the vugs in this data set exhibit touching behavior.

    As the separate vug fraction increases, so too

    does the Archie m

    Figure 23

    Ingeneral,thepresenceofvuggyporositycorrespondstoanincreaseinm,withthemagnitudeofthatincreasedifferingfromonedatasettothenext:Figure23.

    Therearebothchartsandmathematicalmodelsthatallowonetoestimatemforvariousporositypartitions.Theadvantageofthemathematicalmodelisthattheyeasilyallowbothfootbyfoot

    estimatesandMonteCarlosimulation.

    Chartsandmodelsshouldalwaysbetested,atthefirstopportunity,bycomparingthemestimatetothatdeducedbyinvertingArchiesequationinthewaterlegofarepresentativewell.InthecaseoftheDualPorositymodelusedforillustrationsherein,thatcomparisonisreasonable.TheDualPorositymmodelisalsofoundtomatchtheindependentlabmeasurementsofMeyers,andtocapturethepatternsreportedbyFockeandMunn.

    AwellborealternativetommodelsistoaddanonArchietooltothetoolsuite,whichallowsaneffectivemtobededuced.Thatmisthenusedtointerpretthedeepresistivitymeasurement.

    Regardlessoftheapproachused,weshouldbearinmindthatparticularlyinthevicinityofthetransitionzone,thereservoirmayfailtosatisfythebasicArchiecriteria.

    AcknowledgementMohamedWatfasArchiesLaw:ElectricalConductioninClean,WaterbearingRockisanimportantsinglepointhistoricaloverviewsource.FockeandMunnsCementationExponentsinMiddleEastCarbonateReservoirsliterallysetthestandardforasystematicinvestigationoftheissue,backin1987.TothesemustreadarticlesIhaveaddedmorerecentmaterial,andmypersonalthoughts/techniques.

    ThisoneisformyMother,whoisalwaysthere,throughthickandthin.

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  • WWW.GeoNeurale.Com January2012 2012RobertEBallay,LLC

    AlGhamdi,AliandBoChen,HamidBehmanesh,FarhadQanbari&RobertoAguilera.AnImprovedTriplePorosityModelforEvaluationofNaturallyFracturedReservoirs.TrinidadandTobagoEnergyResourcesConference.June2010.

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    Ballay,Gene.StatisticsArePliable.February2010.www.GeoNeurale.com.

    Ballay,Gene.TheBiggestBangfortheBuck.April2011.www.GeoNeurale.com

    Carmona,Romuloetal.ZappingRocks.OilfieldReview.Spring2011

    Chen,CandJ.H.Fang.SensitivityAnalysisoftheParametersinArchiesWaterSaturationEquation.TheLogAnalyst.SeptOct1986

    Diederix,K.M.AnomalousRelationshipsBetweenResistivityIndexandWaterSaturationsintheRotliegendSandstone(TheNetherlands),TransactionsoftheSPWLA23rdAnnualLoggingSymposium,CorpusChristi,Texas,July69,1982,PaperX

    Eberli,GregorP.andGregorTBaechle,FlavioSAnselmetti&MichalLIncze.Factorscontrollingelasticpropertiesincarbonatesedimentsandrocks.THELEADINGEDGEJULY2003

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    Hartmann,DanandEdwardBeaumont.PredictingReservoirSystemQualityandPerformance.www.searchanddiscovery.net/documents/beaumont/index.htm

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    Lucia,Jerry.Petrophysicalparametersestimatedfromvisualdescriptionofcarbonaterocks:afieldclassificationofcarbonateporespace.JournalofPetroleumTechnology.March,v.35,p.626637.1983.

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  • WWW.GeoNeurale.Com January2012 2012RobertEBallay,LLC

    Chattanooga shale

    Mississippian limestoneR. E. (Gene) Ballays 35 years in petrophysics include research and operations assignments in Houston (Shell Research), Texas; Anchorage (ARCO), Alaska; Dallas (Arco Research), Texas; Jakarta (Huffco), Indonesia; Bakersfield (ARCO), California; and Dhahran, Saudi Arabia. His carbonate experience ranges from individual Niagaran reefs in Michigan to the Lisburne in Alaska to Ghawar, Saudi Arabia (the largest oilfield in the world).

    He holds a PhD in Theoretical Physics with double minors in Electrical Engineering & Mathematics, has taught physics in two universities, mentored Nationals in Indonesia and Saudi Arabia, published numerous technical articles and been designated co-inventor on both American and European patents. At retirement from the Saudi Arabian Oil Company he was the senior technical petrophysicist in the Reservoir Description Division and had represented petrophysics in three multi-discipline teams bringing on-line three (one clastic, two carbonate) multi-billion barrel increments. Subsequent to retirement from Saudi Aramco he established Robert E Ballay LLC, which provides physics - petrophysics training & consulting.He served in the U.S. Army as a Microwave Repairman and in the U.S. Navy as an Electronics Technician; he is a USPA Parachutist, a PADI Nitrox certified Dive Master and a Life Member of Disabled American Veterans.

    Watfa,M.etal.ArchiesLaw:ElectricalConductioninClean,WaterbearingRock.TechnicalReview,Volume36Number3

    Watfa,M.SeekingtheSaturationSolution.MiddleEastWellEvaluationReviewNo.3(1987)

    Wyllie,M.R.andARGregory:FormationFactorsofUnconsolidatedPorousMedia:InfluenceofParticleShapeandEffectofCementation,PetroleumTransoftheAIME(1953):103110.

    Biography