The Role of Cutoffs in Integrated Reservoir Studies (2)

7/22/2019 The Role of Cutoffs in Integrated Reservoir Studies (2)

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The Role of Cutoffs in IntegratedReservoir Studies

Paul F. Worthington, SPE, Gaffney, Cline & Assocs., and Luca Cosentino, SPE, Eni E&P Div.

Summary

There have been many different approaches to quantifying cutoffs,

with no single method emerging as the definitive basis for delin-eating net pay. Yet each of these approaches yields a differentreservoir model, so it is imperative that cutoffs be fit for purpose(i.e., they are compatible with the reservoir mechanism and with asystematic methodology for the evaluation of hydrocarbons inplace and the estimation of ultimate hydrocarbon recovery). Thesedifferent requirements are accommodated by basing the quantifi-cation of cutoffs on reservoir-specific criteria that govern the stor-age and flow of hydrocarbons. In so doing, particular attention ispaid to the relationships between the identification of cutoffs andkey elements of the contemporary systemic practice of integratedreservoir studies. The outcome is a structured approach to the useof cutoffs in the estimation of ultimate hydrocarbon recovery. Theprincipal benefits of a properly conditioned set of petrophysicalcutoffs are a more exact characterization of the reservoir with abetter synergy between the static and dynamic reservoir models, sothat an energy company can more fully realize the asset value.

Introduction

In a literal sense, cutoffs are simply limiting values. In the contextof integrated reservoir studies, they become limiting values offormation parameters. Their purpose is to eliminate those rockvolumes that do not contribute significantly to the reservoir evalu-ation product. Typically, they have been specified in terms of thephysical character of a reservoir. If used properly, cutoffs allow thebest possible description and characterization of a reservoir as abasis for simulation. Yet, although physical cutoffs have been usedfor more than 50 years, there is still no rationalized procedure foridentifying and applying them. The situation is compounded by thediverse approaches to reservoir evaluation that have been taken

over that period, so that even the role of cutoffs has been unclear.These matters assume an even greater poignancy in contemporaryintegrated reservoir studies, which are systemic rather than parallelor sequential in nature, so that all components of the evaluationprocess are interlinked and, therefore, the execution of any one ofthese tasks has ramifications for the others (Fig. 1). A particularaspect of the systemic approach is the provision for iteration as thereservoir knowledge-base advances. For example, simulation maybe used in development studies to identify the most appropriatereservoir-depletion mechanism, but, once the development planhas been formulated, the dynamic model is retuned and progres-sively updated as development gets under way.

The principal use of cutoffs is to delineate net pay, which canbe described broadly as the summation of those depth intervalsthrough which hydrocarbons are (economically) producible. In thecontext of integrated reservoir studies, net pay has an importantrole to play both directly and through a net-to-gross pay ratio. Netpay demarcates those intervals around a well that are the focus ofthe reservoir study. It defines an effective thickness that is perti-nent to the identification of hydrocarbon flow units, that identifiestarget intervals for well completions and stimulation programs, andthat is needed to estimate permeability through the analysis of

well-test data. The net-to-gross pay ratio is input directly to volu-metric computations of hydrocarbons in place and thence tostatic estimates of ultimate hydrocarbon recovery; it is a keyindicator of hydrocarbon connectivity, and it contributes to theinitializing of a reservoir simulator and thence to dynamic esti-mates of ultimate hydrocarbon recovery.

Unfortunately, there is no universal definition of net pay, nor isthere general agreement on how it should be delineated. For thisreason, net pay has been incorporated within integrated reservoirstudies in many different ways that have not always been fit forpurpose. In particular, there is no generally accepted method forquantifying net-pay cutoffs, without which net pay cannot be de-lineated. In an attempt to redress some of these shortcomings, thispaper is directed at building a systematic foundation for the defi-nition and role of cutoffs in integrated reservoir studies. It tracksthe origins of physical cutoffs from both geoscience and engineer-ing perspectives in both the Western and Eastern hemispheres. Itoutlines what they are and why we need them, describes how they

should be quantified, and proposes a structured method for incor-porating them within integrated reservoir studies for the evaluationof hydrocarbons in place and the estimation of ultimate hydrocar-bon recovery. The starting point is some basic terminology.

Basic Terminology

Definitions.Although there is no universal set of definitions ofthose terms that describe the ability of a rock to store and transmitfluids, there are seven fundamental descriptive terms that are infairly widespread use. They are grounded in the volumetric analy-sis of siliciclastics using core and log data, and they may or maynot be based on a tieback to permeability. They all define thick-nesses or thickness ratios, and they are interrelated (Fig. 2).

Gross rock comprises all rocks within the evaluation interval.Net sand comprises those rocks that might have useful reser-

voir properties. The word sand is a generic oilfield term that his-torically equates tolithologically clean sedimentary rock. Net sandis usually defined as the summation of those intervals for whichthe sand content is greater than or equal to a limiting value. Thiscriterion is usually expressed in terms of a shale volume fractionVsh being less than a limiting value Vshc (the shale cutoff). Theterm shale includes clays and silts (size indicators), clay minerals(compositional indicators, mostly within the clay fraction), andother detritus, usually of a poorly sorted nature. The parameterVshis log-derived; it cannot be measured directly in the laboratory.

Net reservoircomprises those net-sand intervals that do haveuseful reservoir properties. This condition is usually expressed interms of the log-derived fractional porosity being greater than orequal to a limiting value c (the porosity cutoff). Porosity can bemeasured downhole and in the laboratory. It is often tied back tocore permeability so that the net-reservoir criterion effectively be-comes one of a sufficiently porous and permeable rock that iscapable of storing and transmitting hydrocarbons.

Net paycomprises those net-reservoir intervals that do containsignificant hydrocarbons. This requirement has been reduced to thelog-derived, fractional hydrocarbon saturation Sh being greaterthan or equal to a limiting value. This condition is tantamount tostating that the water saturationSw(1Sh) is less than a limitingvalue Swc(the water-saturation cutoff). This second option is morecommonly used. The parameter Swcan be measured downhole andalso in the laboratory if native-state core is available, but reliablecore measurements ofSw remain comparatively rare, even thoughthe technology has been around for several decades. Where netreservoir is tied back to permeability, net pay describes those

Copyright 2005 Society of Petroleum Engineers

This paper (SPE 84387) was first presented at the 2003 SPE Annual Technical Conferenceand Exhibition, Denver, 58 October, and revised for publication. Original manuscript re-ceived for review 5 April 2004. Revised manuscript received 6 May 2005. Paper peerapproved 31 May 2005.

276 August 2005 SPE Reservoir Evaluation & Engineering


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net-reservoir intervals that contain producible hydrocarbons. In aclear link to reserves, the definition of net pay has evolved intothose hydrocarbon-bearing reservoir intervals that can be producedeconomically using a particular recovery method.1 The term net

pay is therefore not merely a descriptor of rock type.Net-to-gross is a generic term that encompasses three defini-

tions, all derived from the above. Generally, it is the ratio of netthickness to gross thickness. Net-to-gross can be based on netsand,net reservoir,or net pay and expressed as net-to-gross sand,net-to-gross reservoir, or net-to-gross pay, respectively. It is im-

portant that the basis for the net criteria be defined. Unfortunately,many investigators merely refer to net-to-gross without givingany explanation.

This set of definitions is not unique. Table 1 indicates thecorrespondence between the more widespread classification that isadopted here and some others that have been proposed elsewhere.25

Adoption of Definitions.The full adoption of these definitionscalls for three coexisting physical cutoffs:Vshc, c,and Swc. Manyinvestigators have adopted the above scheme, usually in one ofseveral different ways. For example, it can be used in true static

or volumetric mode, where the cutoffs are used to evaluate hy-drocarbons in place, possibly with the subsequent application of arecovery factor to estimate ultimate hydrocarbon recovery.6 Alter-natively, it can be used in dynamically conditioned mode,whereby the static cutoffs are tied back to another parameter suchas (relative) permeability, which is sometimes included explicitlyin the definition of net reservoir. In these cases, the cutoffs becomeindicators of flow capability as well as of volumes. They are moreimmediately appropriate to the dynamic estimation of ultimatehydrocarbon recovery through simulation, which also delivers a

recovery factor.7 These two approaches will furnish different val-ues of net pay and have different recovery factors, although theproduct of these two parameters can turn out to be similar. Somehave gone so far as to propose typical values ofVshc, c, and Swcfor clastic reservoirs and then modify these for carbonate reser-voirs (Table 2).8

It is worth noting that the definition of cutoffs is intrinsicallyrelated to the adopted approach to petrophysical evaluation (i.e.,the effective or total porosity model or some variation on these).9

Note that the adjectives effective and total refer, respectively,to the exclusion from or inclusion within the reservoir porosity of

Fig. 1(a) Traditional and (b) contemporary approaches to reservoir studies.

Fig. 2Schematic interrelationship of net parameters with cutoffs applied sequentially.

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any electrochemically bound waters; these terms are used here inthe petrophysical sense rather than the engineering sense, which(in a water-wet system) excludes from the effective pore volumethose formation waters that are subject to capillary retention. Thenet-sand definition is couched in terms of the effective porositymodel, which uses a log-derived value of Vsh. In contrast, thetraditional use of the total porosity model calls only for porosityand water-saturation cutoffs within the above scheme becausethere is no Vsh evaluation within that model, although there aresome hybrid models that use Vsh in a total-porosity setting. This

paper is set within the context of the effective porosity approach topetrophysical evaluation.

Traditional Methodologies

Cutoffs usually have been generated and applied at the petrophysi-cal stage of an evaluation exercise, but, with certain exceptions,their primary impact has been at the reservoir engineering stage.This separation has been exacerbated by the historical practice ofdepartmentalized reservoir evaluation.7 The consequential lack ofuniformity has been compounded by the coexistence of differentsets of definitions (e.g., of net pay vs. net exploitable sand; seeTable 1).

Western Culture.The Western petroleum industry has tradition-ally adopted rules of thumb as cutoffs for the evaluation of net pay

from well logs. The arbitrary nature of those cutoffs has long beenrecognized.10 For the most part, they have been fixed permeabilitycutoffs,kc,nominally 0.1 md for gas reservoirs

1113 and 1.0 md foroil reservoirs.1416 For example, those intervals within a gas col-umn for which permeability k0.1 md are admitted as net pay.These nominal cutoffs are still being used.17,18 Because perme-ability is not measured by well logs, the practice has been to relatecore permeability to porosity and/or some other log-derivable pa-rameter(s). Those log responses and/or interpreted values of res-ervoir parameters that correspond to an adopted permeability cut-off are then used as pseudo-permeability cutoffs. Although therule-of-thumb cutoffs have been founded on experience, they arearbitrary in the sense that they do not take specific account ofreservoir characteristics and the reservoir-depletion mechanism.

The rules of thumb are further degraded by the lack of a speci-

fied procedure for applying them. For example, because conven-

tional core permeability is usually an absolute permeability to gas,

an air permeability of 1.0 md has sometimes been taken as the

limiting permeability for pay in an oil column.9 This implies that

the rule-of-thumb cutoffs are expressed in terms of absolute air

permeability at ambient conditions, but this concept has rarely

been articulated categorically, even though its impact may be con-

siderable. For example, the 1.0 md (air) permeability cutoff might

be appropriate for medium-gravity oils, but it would be meaning-

less in the case of higher-viscosity, heavy oils. A further twist wasprovided by George and Stiles19 and Hall,20 who cited a core

permeability net-pay cutoff of 0.1 md as appropriate to west Texas

Permian carbonate reservoirs that contain low-viscosity oils. How-

ever, although the fluid used to measure the core permeability was

not mentioned, it would appear the 0.1 md value is an air per-

meability rather than an oil permeability . . . .21 The same labo-

ratory air permeability cutoff of 0.1 md has been applied to the

Cambrian sandstones of the Hassi Messaoud field in Algeria; this

field, too, contains low-viscosity oil.22 This discussion demon-

strates that the application of rule-of-thumb cutoffs can be ambiguous.

Examples from the earlier literature indicate a tortuous path in

the evolution of cutoff concepts beyond the rules of thumb for

permeability. Pirson23 presented thecoregraph method of using

three independent cutoffs for permeability, porosity, and water

saturation. It was assumed that unless each limiting value was

satisfied, no hydrocarbons would be produced. Permeability was

promoted as the controlling parameter. In bringing together core

and log analysis, Keener24 described three net-pay cutoffs, for

shale factor, porosity, and water saturation, and then went on to

discuss net pay in a volumetric sense. Yet, in an example from the

Eocene Wilcox Sand in Texas, he did tie back to core permeability

and capillary pressure data. Jeffries25 generated a sonic-log cutoff

that was tied back to arbitrary core porosity and permeability cut-

offs for an oil-bearing Devonian limestone; this information was

used to enhance quantitatively the classical recognition of net pay

using the caliper log and microlog separation.26

In a move toward the modern concept of reserves, Brown and

Salisch27 cited a porosity cutoff below which there was no com-mercial permeability. Walters28 proposed a neutron porosity cut-off to definenet permeable payin a limestone sequence, therebyimplying thatnet pay was a volumetric or static concept. Quintand Grosmangin29 used porosity, water saturation, and permeabil-ity cutoffs in computations of hydrocarbons in place and movableoil; the deliverables were presented as reserves. Ritch andKozik30 applied porosity, water saturation, and self-potential (SP)log cutoffs, the last one being a quasi-shale cutoff, to an overpres-sured gas sand in the Frio Vicksburg Trend, Texas. For net-payclassification, they additionally required a mudcake, noting thatmudcake development occurred in this formation where k0.1md. Interestingly, this observation is in accord with the earlierrules of thumb for a limiting gas-sand permeability. Randolph31

tied porosity back to a critical water saturation in establishing net



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pay on the basis of a single porosity cutoff for the tight gas sandsof the Pinedale Unit, Wyoming. In an excellent paper, MacKen-zie32 recognized productive and nonproductive rock types on thebasis of effective pore-throat size, which he correlated with theratiok/, for the Cretaceous Cardium Sandstone in the Pembina oilfield of south-central Alberta; a cutoff of k/0.05 (with per-meability in md and porosity in percent) was then used to distin-guish net pay.

In a reversal of this trend, McCoy and Burge33 adopted gammaray (shale), porosity, and water-saturation cutoffs for pay iden-tification in the Lower Cretaceous Wabiscaw Sand in the MartenHills Field, Alberta, but without reference to permeability. In aneat shift of logic, Schultz34 adopted a single cutoff for porosity

derived using the density log; this cutoff was used to compute fromporosity and irreducible water saturation a well-by-well net per-meability-foot indicator of producibility.

These examples illustrate the different perceptions of the roleof cutoffs in determining net pay that prevailed prior to 1980, thepoint at which the industry started to benefit from the revolution inthe acquisition, processing, and storage of digital data.

Eastern Culture.There is much less published information avail-able in English concerning the application of cutoffs to determineeffective oil-saturated thickness in the Russian system. Tradi-tionally, there has been a high reliance on rules of thumb, some-times in the form of simple resistivity cutoffs, as noted by Mossand Stocks.35 These same authors cite Itenberg36 as listing criticalvalues of resistivity index to define the hydrocarbon potential in

different geographical regions and as identifying critical watersaturations to distinguish hydrocarbon productive zones for differ-ent formation types (e.g., clean sandstones and shaly carbonates).The analysis of porosity vs. permeability relationships is oftenused to identify a limiting porosity below which a reservoir willnot flow. This limiting porosity is refined on the basis of well tests.It is therefore reservoir- or region-specific.37 Where there are nodata available from the reservoir under study, analogies are drawnwith lithologically equivalent reservoirs in the same region.

Contemporary Methodologies

For present purposes, the contemporary period is designated as 1980onward. It is characterized more by improved data-acquisition tech-nology than by a quantum leap in interpretation philosophy.Table 3summarizes the case histories of cutoff adoption that have been pub-

lished during this period.

36,8,11,12,1618,20,3857

The list is not com-plete because some approaches have gone beyond the procedurallimitations imposed by the design of Table 3. However, severalobservations can be made. First, Table 3 does not indicate a pre-dominant or preferred methodology, although the selection ofsome or all of Vshc, c, kc, and Swc seems to encompass a mostcommon approach. Second, where permeability is not includedexplicitly in Table 3, it is often present implicitly through a tyingback to permeability of one or more of the other parameters andthence their dynamically-conditioned cutoffs. Notwithstandingthis comment, permeability occurs less as an explicit cutoff thanthe other three parameters of this subset. Third, there has been noclear convergence with time toward an industry-preferred group-ing of cutoffs. The nonconvergence is substantiated by the follow-ing specific examples that do not fit into the scheme of Table 3.

At the most basic level, cutoffs have been used for distinguish-ing between sands and shales, especially in laminated sand/shalesequences. This approach has often used resistivity logs, perhapsin conjunction with a minimum admissible layer thickness.3 How-ever, where layer thickness is generally small, the approach hasbenefited from a higher log-data-sampling rate and from thesharper spatial resolution of microresistivity logs or electromag-netic propagation logs.58 More recently, the evaluation of net payin laminated reservoirs has drawn upon microresistivity imagingtools to distinguish between sands and shales in cases where con-ventional log resolution is not sufficiently sharp.46

In an interesting treatment of fractured carbonates, Jiyu59 notedthat a porosity cutoff would satisfactorily distinguish net pay be-cause porosity correlated well with matrix (intergranular) perme-

ability and water saturation, and it was therefore indicative of bothflow and storage properties. A porosity cutoff was established tocorrespond to an arbitrary limiting water saturation of 0.5. How-ever, the height dependence of water saturation led to a porositycutoff that was itself a function of height above free water level.

Berruin and Barlai38 avoided the specification of arbitrary cut-offs by applying pattern-recognition techniques to the evaluationof shaly sands. They gave a movable oil index (MOI) a dynamicmeaning by defining a primary production index (PPI) as the prod-uct of MOI and a function of the ratio k/ normalized to itsmaximum value (k/)maxin the field or in a reservoir subdivision.The PPI was crossplotted with a lithologic factor, itself a geologi-cally conditioned function ofk/. Pattern recognition was appliedto the crossplotted data to identify a productive/nonproductive di-viding line. Although this work used nonstandard parameters, itwas significant in that the reservoir data themselves were used todefine the cutoffs. Thompson et al.49 also used a movable hydro-carbon index as a more realistic pay indicator than the three dis-crete cutoffs, Vshc, c, and Swc.

Kolodzie60 used pore-throat size as a net-pay indicator for theSpindle field, Colorado. The key step was to recognize from earlierwork that the trap on the updip side of Spindle was due to thepore-throat size dropping below 0.5 microns. A modified Winlandequation was established for calculating pore-throat size from log-derived porosity and permeability. A net-pay cutoff of 0.5 micronswas then applied to the log-derived pore-throat-size data. Thisexample was significant because it used the characteristics of thetrapping rock as a basis for setting up a net-pay criterion. This

philosophy has recently been re-emphasized.21

Teti and Krug61 used not only porosity and water-saturationcutoffs but also a bulk-volume-water (Sw) cutoff for oil-bearingcarbonates of the Williston basin in eastern Montana. The deter-mination of net pay additionally used a resistivity-ratio cutoff.Essentially, this involved a comparison of pseudo formation resis-tivity factors in the form ofR1Rt/Rw (where Rtis the formationresistivity of the undisturbed zone and Rw is the resistivity of theformation water) and R2Rxo/Rmf (where Rxo is the formationresistivity of the flushed zone and Rmfis the resistivity of the mudfiltrate). The cutoff was defined in terms of a lower limiting valueofR1/R2. The method is not appropriate to shaly formations.

Vavra et al.1 used mercury injection capillary pressure to iden-tify net reservoir and net pay. The cutoffs were established em-pirically using a global database. Although the cutoffs were not

reservoir-specific, there were limits to their applicability. For ex-ample, the net-reservoir cutoffs may not be appropriate to tightgas sands, whereas the net-pay cutoffs may not apply where thereare special circumstances affecting commerciality (e.g., deep-water reservoirs).

In a paper reminiscent of the rule-of-thumb cutoffs, Bennionet al.62 noted that little or no flow is observed in a tight gasreservoir in which k


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Why Cutoffs Are Needed in IntegratedReservoir Studies

Cutoffs are needed in any reservoir study for which the reservoirsystem includes constituent rocks of weak hydraulic properties thatcannot be excluded at the geological correlation stage. Those rocksform part of the reservoir succession in a geological sense, but theydo not contribute significantly to the evaluation of hydrocarbons inplace or to the estimation of ultimate hydrocarbon recovery. There

are two principal reasons why it is unwise to include those rockswithin the evaluation of hydraulic storage and flow units. Theseconsiderations are set within the context of a petrofacies classifi-cation scheme.63

First, the predictive algorithms for porosity, permeability, andhydrocarbon saturation that form part of the reservoir evaluationexercise must be established using data measured for the rocks thatdetermine reservoir character. The inclusion of nonreservoir rocks



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at the outset usually distorts the predictive algorithms and therebylessens their accuracy and weakens their precision if these samealgorithms are then adopted throughout. This means that for prac-tical purposes, the numerical relationships between the pertinentparameters have to be established twice. Initially, they are ana-lyzed for the identification of cutoffs when all data have to beconsidered; this exercise is essentially concerned with the quanti-fication of trends. Then, when the cutoffs have been accepted, theyare re-established for all intervals that satisfy the cutoffs; this

exercise is undertaken for purposes of predictive applications.Fig. 4shows an example of a linear fit to a bilogarithmic porosityvs. permeability data distribution before and after the applicationof a net-reservoir cutoff. These core data have not been sorted intopetrofacies units, and they typically show a dispersion of approxi-

mately plus/minus one order of magnitude. The inclusion of datafor which k


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Intended Deliverable. The need for fit-for-purpose cutoffs wasidentified by Snyder,2 who noted that the intended use of the netpay often determines how net pay is picked. He saw net pay asbeing determined by porosity and/or permeability cutoff values,thereby implying that the approach could be static or dynamic innature. This duality was also flagged by Berruin and Barlai,38 whosaw a twofold approach based on static reserves, where perme-ability had not been taken into account in establishing the cutoffs,and dynamic reserves, where it had. The use of an MOI merelydefined static reserves, as suggested by the descriptive termnet oilsand, although Berruin and Barlai did call their final deliverablenet pay. In general, cutoffs should be dynamically conditioned.

Reservoir Connectivity.Here, the cutoffs are intended to definea net-to-gross ratio that is a measure of the continuity of a reser-voir. The well data are samples of the connectivity. They are alsocontrol points because if connectivity is inferred from a net-to-gross ratio, the latter can be measured only at a well. In terms ofour adopted definitions, we require net-reservoir thickness as theinput parameter to a net-to-gross ratio. This indicates the fractionof gross rock that is sufficiently clean and porous to be a potentialhydrocarbon reservoir. IfVshcand chave been tied back to (rela-tive) permeability, there is the added assurance that continuousnet-reservoir rock will allow the reservoir fluids to flow. Thisassurance is one of the strongest arguments against independent,static definitions ofVshc,c,and Swc. It can be visualized througha 3D geocellular model in which the distribution of good cellsis highlighted.7

Volumetric Analysis.This method might be directed at a hy-

drocarbons-in-place figure, as an end in itself, or it might be tar-geted at the estimation of ultimate hydrocarbon recovery, in whichcase a recovery factor will be applied.

In the context of estimating hydrocarbons in place, there hasbeen some debate about whether cutoffs are needed at all. If oneseeks a gross number, and nothing more, the argument for nocutoffs can be accepted for volumetric calculations (but not inestablishing reservoir-specific interpretative algorithms, which aredegraded by the inclusion of nonreservoir rock). Having said that,it is difficult, if not impossible, to conceive of a situation in whichan estimate of hydrocarbons in place would be made without anyintention of using it. To this end, we take the view that accessiblehydrocarbons are contained in reservoirrock, which is character-ized by a supracritical capability for the storage and transmissionof fluids. Therefore, if an estimate of hydrocarbons in place is to

have any pragmatic meaning, it has to relate to host rocks that areof reservoir quality. This philosophy is key to the generation ofestimates of hydrocarbons in place using dynamically conditionedcutoff parameters (i.e., scalar quantities that are tied back to somefunction of permeability).

Of course, as noted earlier, some investigators have determinedindependent static cutoffs for the parameters Vsh,,and Swwith-out reference to permeability. In contrast, there have been othercases in which scalar cutoffs have been tied back to a (sometimesarbitrary) permeability cutoff even where the volumetrics are to besubjected to a recovery factor. In this respect, it is essential to notethat recovery factor is intertwined with net pay. The latter is athickness and the greater the admitted thickness (i.e., the less strin-gent the cutoffs), the lower the recovery factor will be. The inde-pendent generation of net-pay thickness and recovery factor is,therefore, not appropriate. Moreover, the interrelationship of netpay and recovery factor does not preclude volumetric cutoffs frombeing defined dynamically (i.e., with reference to permeability).It is recommended that the dynamically conditioned approach bethe standard.

Dynamic Reservoir Model.The intended deliverable is the es-timation of ultimate hydrocarbon recovery. Cutoffs should be dy-namic in nature. They are needed because there is no point inaccounting for in-place hydrocarbons that will not form some partof the recovery process. Hydrocarbon volumes that do not con-tribute to the energy balance (e.g., do not experience pressuredecline) during the course of the recovery process should not becounted in the initial in-place volumes upon which the efficiencyof the recovery process (i.e., the recovery factor) is based.

Cutoffs should be tied back to a hydraulic parameter, which

might be absolute permeability; equivalent circular pore diameter,

(k/)0.5; mobility, k/, where is fluid viscosity; capillary pres-sure; residual water saturation; or extrapolated endpoint relative

permeability; depending on the reservoir-depletion mechanism.

Here, there is a stronger case for the synergic application of static

cutoffs that are all tied back to the same (petrofacies-specific)

limiting value of the same hydraulic parameter.7 Note, however,

that this approach is applicable only over a predefined hydrocar-

bon leg. The great advantage of synergic cutoffs is that the entire

process of determining net pay has a dynamic foundation. The

recovery factor delivered by the simulator will be conditioned by

the input net-to-gross pay.

Flow Regime. Most of the published case histories of the appli-

cation of cutoffs relate to reservoirs within which intergranular

(sometimes called matrix) flow predominates. In fractured res-

ervoirs, a different approach is called for. At the limit, where the

intergranular flow is negligible and the fractures form a network of

regional conduits, some kind of fracture indicator is needed with a

limiting value above which flow is commercially exploitable.

More generally, the fractures are fed by an intergranular rock that

can also allow flow into a well; here, the relative importance of the

two flow mechanisms will determine whether to use a fracture

indicator, intergranular cutoffs, or some combination of these. It is

important to distinguish between fractures that act as conduits

throughout the volume drained by a well and those that are drill-

ing-induced and, therefore, irregular extensions of the boreholewall. Both contribute to well productivity, but to different degrees.

An example of cutoffs for commercial hydrocarbon recovery in a

naturally fractured reservoir was provided by Schafer.64 Where

fracture stimulation is applied, the cutoffs need to take account of

this as part of the recovery mechanism.

Reservoir Recovery Mechanism and Stage of Depletion.Dy-

namic cutoffs are necessarily founded on Darcys law. In addition

to the effective thickness of the flowing interval, the key factors

influencing producibility are mobility, fluid pressure gradient, wet-

tability, viscous/capillary forces ratio, and wellbore skin factor.

These factors are impacted by the reservoir recovery mechanism

and the stage of depletion. Sensible cutoffs are needed so that the

efficiency of the recovery mechanism can be assessed. Cutoffs are

therefore established in the light of an assumed recovery mecha-nism. The following comments develop this point.As noted earlier, contemporary reservoir studies are both inte-

grated and iterative in nature. Where the optimum recovery mecha-nism has not been established, cutoffs will have a markedly itera-tive role in integrated reservoir studies because they will be reap-plied through various scenarios. However, in many cases, therecovery mechanism actually will be known or can be assumed.Where a field has a significant production history, the availablepressure and production data are used to infer reservoir drives but,even here, the opportunities to use material-balance and perhapsdecline-curve analyses retain a dependence on cutoffs becauserecovery efficiency still has to be assessed. In development stud-ies, reservoir behavior has to be understood reasonably well be-cause it forms the basis for a development plan (e.g., a decision onwhether or not to implement waterflooding). Here, a drive mecha-nism is assumed on the basis of rock and fluid properties, analogreservoirs in the area, and regional information concerning aquiferstrength and permeability. This assumption allows the prevalentreservoir mechanism to be inferred (e.g., diffusion or convection).It is a prerequisite for generating the economics of a proposeddevelopment project.

Most fundamentally, George and Stiles19 drew a distinctionbetween continuous net payand floodable net pay. They observedthat all net pay is not necessarily floodable, even if it is laterallycontinuous. These observations were developed by Cobb andMarek,21 who noted that lower-permeability rocks that contributedto production during primary depletion might not be injectableduring waterflooding and thence become nonpay.



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Primary Depletion.To accommodate both oil and gas reser-voirs within the same framework, it is proposed that cutoffs shouldbe tied to a limiting value of mobility. The viscosity of a gas is atleast an order of magnitude less than that of a light oil, and themagnitude of this disparity probably accounts for the differencebetween the traditional permeability cutoff values of 0.1 md forgas and 1.0 md for oil. The need to tie viscosity to temperature andpressure emphasizes that permeability must also be at reservoirconditions, which will change as the reservoir is produced. In thisrespect, cutoffs assume a time dependence, primarily through theclosure of pore throats. The limiting mobility is determinedthrough the analysis of data that pertain to a given petrofacies unitand a given fluid type.

Waterflood Depletion. The key permeability parameter is hy-drocarbon permeability at irreducible water saturation. To makefull use of the conventional core database, an additional linkagebetween absolute and relative permeability is needed. If reservoir-fluid pressure is maintained, the complication of pressure-inducedreductions in permeability is avoided. However, there is the op-posite problem of thermal fracturing of the reservoir along theflood front; this will have some impact on the sweep mechanism.Analytical waterflooding calculations for the establishment of apermeability cutoff have been outlined by Cobb and Marek.21

Factors Relating to the Specification of Cutoffs

Scale Effects. A most important requirement is that core perme-ability be used in a manner that does not introduce any transgres-sions of scale. Because cutoffs often relate to log responses, thecore data need to be reconstructed at a scale that is compatible withthe spatial resolution of logging tools before being correlated withlog-derived parameters in order to tie the net-pay cutoffs to areference permeability value. This exercise should be undertakenseparately for each petrophysical rock type and by using a consis-tent approach to petrophysical evaluation. In this way, data scatteris reduced, and the resulting cutoffs are therefore more definitive.

This objective has been partially achieved by defining a limit-ing value of a reference parameter at the core scale and thenrelating the reference parameter to a log-derived cutoff parameterto establish a crude cross-scale correspondence between the lim-iting value and the cutoff value. The implication here is that thealgorithm accommodates scale differences. This procedure can beimproved by investigating relationships between core-derived pa-rameters at a pseudo-log scale, where the latter is attained through

the application of (weighted) running means to regularly spacedconventional core data.65 Alternatively, the combined use of coredata and micro-imaging logs, the latter as a pseudo-measure ofporosity and thence perhaps permeability, has allowed the con-

struction of variograms to guide the weighting of core-plug data

adjacent to each log-sampling level. This weighting has allowed

the core data to be reconstructed at the (axial) log scale.66

It is important to note that because cutoffs are usually derived

empirically from an inspection of data, they are intrinsically con-

ditioned by the scale of measurement of those data. Cutoffs should

only be applied to data that relate to that same scale. This funda-

mental law of scale applies to the whole of engineering geoscience.

It is commonly abused. An illustration of the effects of ignoring

scale in the establishment of cutoffs is shown in Fig. 5.

Minimum Net-Pay Thickness.Net pay is conditioned by the spa-

tial resolution of well logs because the cutoffs ultimately will beapplied to log data. The conventional log-sampling interval is 0.15

m, so each log data point notionally relates to a sublayer of 0.15 m

thickness. Resolution describes the minimum layer thickness for

which a log will record a correct parametric value for that layer

after appropriate environmental corrections. This is nominally

about 0.60 m, but it does vary from log to log, with downhole

conditions, and with the type of log-data processing that has beenapplied. Below this limit, the log merely detects a layer, and all thedata points are apparent values. Partly for this reason, there hasoften been a minimum thickness for a net-pay interval to be ad-missible. This thickness has ranged from 0.25 m to 1.0 m, butsometimes it has been greater. A further reason for this spatial limitis that an overcomplex reservoir model is difficult to use, espe-cially at the simulation stage.

Rock Typing.Where a reservoir is heterogeneous, a subdivisionof the geological succession might be needed. Traditionally, thissubdivision has been based on facies (associations), so that a fa-cies-by-facies set of cutoffs is established.67 More recently, it hasbeen proposed that a reservoir should be partitioned in a mannerthat is fit for purpose.68 The geological architecture is retained forvolumetric computations. However, the establishment of cutoffs,which is essentially a petrophysical and engineering exercise,should be undertaken on the basis of physical criteria. Because thedetermination of cutoffs uses relationships between physical prop-erties, a reservoir should be subdivided separately into petrophysi-cal units that are distinguished not by their data envelopes ofphysical properties but by the quantitative forms of the predictivealgorithms that are needed to evaluate them.63 Each of these petro-

facies units can have an exclusive set of different cutoffs. Here, it

might be possible to use a single reference value of mobility or ofa (relative) permeability term as a limiting value for the wholereservoir system. However, there might still be significantly dif-ferent (petrofacies-specific) relationships between the reference

Fig. 5Bilogarithmic crossplots of porosity vs. permeability for a sandstone reservoir (a) at the core scale and (b) at the simulatorgrid-cell scale, showing the different porosity cutoffs

cthat correspond to a fixed (air) permeability cutoff of 1.0 md (adapted

from Worthington65).



9/15

parameter and the cutoff parameters to be used in log analysis.

These relationships can be described through discrete crossplots

of, for example, mobility or (relative) permeability vs.Vsh,,andSwfor each petrofacies. Therefore, the resulting values ofVshc, c,and Swc will be distinct for each petrofacies unit (Fig. 6).

The situation is different where the petrofacies are markedly

distinct texturally and/or differ from the standpoint of the stress

response of the reference parameter(s). This means that at condi-

tions of effective reservoir stress, the rock types can be addition-

ally distinguished by the ranges of values of the pertinent param-

eters. Here, it might not be possible to identify a single limiting

value of mobility or of a (relative) permeability term that is ap-

propriate to all petrofacies. In effect, there will be different startingpoints for developing the cutoffs to be used in log analysis. Once

again, the resulting values ofVshc, c,and Swcwill be different foreach rock type.

It is worth reiterating that once the cutoffs have been identified

and applied, the interpretative algorithms should be re-established

for each petrofacies unit so that they relate solely to the admitted

net intervals. Where a reservoir comprises a single petrophysical

rock type, there still may be a need for different cutoffs in different

parts of the reservoir (e.g., because of the different mobilities

associated with a gas cap and an oil rim). The same is true for a

reservoir that has a large structural closure and for which the

hydrocarbon properties vary significantly with depth.

Relationship of Permeability to Other Parameters. The perme-

ability that is most appropriate to a reservoir situation is unlikelyto be the absolute gas permeability. Yet this is what is usuallyavailable from conventional core analysis. The analysis of a mo-bility or a (relative) permeability cutoff must be guided by thenature of the data and the intended application. However, in all

cases the aim is to identify a crossover point from inadmissible to

admissible levels of producibility that can be expressed in terms of

a cutoff value for a permeability or mobility parameter. That per-

meability parameter should be appropriate to the task in hand. It

might be relative permeability to gas or oil at conditions of irre-

ducible water saturation, perhaps expressed in units of mobility.

These data are usually far more limited than conventional gas-

permeability measurements. When a (relative) permeability cutoff

has been determined, it must then be related to absolute perme-

ability for wider application. This philosophy is in accord with the

key well concept of calibrating interpretative methods at well-

studied localities.

Once a (relative) permeability or mobility cutoff has been iden-tified, it can be related to Vshc, c, and perhaps Swc. The cutoffstherefore share three characteristics. First, through this process,

they are dynamically conditioned. This is the primary justification

for this approach. Second, they are synergistic rather than sequen-

tial. Although the values ofVshc, c, and Swc notionally relate tothe net-sand, net-reservoir, and net-pay classifications, respec-

tively, they no longer have the nested impact of Fig. 2. Indeed, by

tying each of them back to the same limiting (relative) permeabil-

ity or mobility(Fig. 7),we introduce a strongly overlapping effect,

so that the third cutoff, whichever that may be, has comparatively

little additional impact when it is applied over the hydrocarbon leg

(Fig. 8). A similar observation was made by Pirson,23 who in-cluded a permeability cutoff, although his three cutoff parametersappeared to have been established independently. Third, the cut-

offs are rendered log-derivable. This means that a log-derivedparameter has to be correlated with core permeability, and thisrequirement has rock-type and scale implications (see above). Al-though Vsh, , and Sw can all be tied back in this way, the rela-tionship of porosity to permeability is the most critical.69

Fig. 6Porosity vs. permeability relationships for four rock types, showing the different porosity cutoffs c

that correspond toa fixed permeability cutoff of 0.1 md. The permeability cutoff is presumed to be tied to a reference parameter cutoff (adaptedfrom Cosentino7).



10/15

Implications for Integrated Reservoir Studies

The foregoing constitutes a defensible foundation for quantifyingnet-pay cutoffs. Because this foundation has been placed withinthe context of integrated reservoir studies, the geological setting,interstitial fluids, and field database are all pertinent to the way inwhich cutoffs are selected.

Formulation of Cutoff Criteria. Although there are still differ-ences of perception between geologists and engineers concerningthe role of net pay, it is becoming increasingly accepted that this

term and its defining cutoffs must have a dynamic significance. Inother words, cutoffs are mostly used to delineate those net-payintervals through which hydrocarbons will flow and hence . . . beproduced, and they are therefore a function of the permeabilitydistribution.70 Some have introduced the further requirement thatnet-pay cutoffs should delineate intervals of commercial produc-ibility.1,10,21 The difficulty here is how to make this expandeddefinition workable at the reservoir evaluation stage. Whatever theprecise definition of net pay, the cutoff exercise reduces to one ofquantifying a limiting permeability term that can be expressed interms of an absolute air permeability as measured by conventionalcore analysis. In this way, log-derivable cutoffs can be tied backto a (scale-compatible) core-derived permeability that is moreabundant than any permeability deliverable from special coreanalysis. The underlying problem, which has long been recog-

nized, is that it isdifficult to select with assurance a permeability

cutoff value.23

Fig. 9provides a schematic description of the role of cutoffs in

integrated reservoir studies. By adopting a structured procedure

that is fit-for-purpose, the arbitrary nature of rules of thumb is

avoided. Although described in terms of a set of tasks, the enact-

ment of these procedures has to be undertaken systemically within

the overall field study. Fig. 9 is intended to form a basis for the

pragmatic application of cutoffs in integrated reservoir studies, an

exercise that is to be the subject of a follow-up paper.

In Fig. 9, the definition of the reference mobility or the refer-ence relative permeability at irreducible water saturation Swirris byfar the most critical step in the whole procedure. A stepwise ap-proach has been suggested, so that the process will be consistent.The following notes supplement Fig. 9.

Identification of Data Sources.These include all the data thatcan provide information about the hydrocarbon presence and mo-bility or multiphase fluid flow [e.g., laboratory measurements oncores (conventional and special), raw log data and log-analysisdeliverables such as NMR movable hydrocarbon index, dynamicdata (DST and well-test results, production data), etc.]. The entireprocess of cutoff selection should be driven by the available datarather than by imported concepts.

Data Integration. The integration of diverse data is impactedby variations in saturation, pressure, and temperature. This is es-

Fig. 8Schematic similarity of net reservoir and net pay, where dynamically conditioned cutoffs are applied synergically to thehydrocarbon leg.

Fig. 7Schematic generation of synergic cutoffs c, V

shc, and S

wc for primary reservoir depletion, where mobility and water

saturation are log-normally distributed (adapted from Cosentino7).



11/15

pecially important in the case of viscosity. Cutoff selection isspecific to a reservoir, to its depletion mechanism, and to the stageof depletion.

Correlation With Petrophysical Parameters.Once the refer-ence mobility or endpoint relative permeability value has been

selected, it should be correlated with standard rock parametersdelivered by the petrophysical evaluation. This process should beperformed independently for each petrofacies. Cutoff selectionuses all the data, including those that obviously are going to beclassified as nonreservoir.

Fig. 9Flow chart describing the role of cutoffs in integrated reservoir studies.



12/15

Sensitivity Studies.Volumetric computations should be per-formed using different sets of (dynamically conditioned) cutoffs inorder to understand the impact on the final results. One example ofthis sensitivity analysis is illustrated in Fig. 10.

Reconciliation of Different Reservoir Subdivisions. In deter-ministic field studies, where a correlative reservoir architecture hasbeen defined stratigraphically, the interpreted reservoir propertiesfor each petrofacies unit are recombined into stratigraphic zonaldata at each grid node for purposes of computing volumetrics.Net-reservoir cutoffs are applied before mapping; the saturation-height function is generated using net-reservoir data. Becausethese cutoffs are petrofacies-specific, they have to be applied be-

fore recombination. In geostatistical field studies, where each cellis assigned a petrofacies classification as part of the populatingexercise, the volumetric computation is a direct summation of thecontributions of the individual cells, for each of which a hydro-carbon saturation has been calculated. Depending on cell thicknessand the scale at which the net-reservoir cutoffs are established, thenet-reservoir cutoffs can be applied to point data or to cellularaverages of, for example, porosity. However, given that the satu-ration-height function has to be applied at the cellular scale, theadoption of this scale for the establishment of all cutoffs would beconsistent. Of course, an integrated reservoir study can draw uponboth deterministic and geostatistical approaches. By tying back thecutoffs to dynamic parameters so that the cutoffs determine wheth-er or not hydrocarbons will flow, the volumetrics will relate toproducible hydrocarbons. If this tieback is not done, the volumetric

computation delivers strictly static hydrocarbons in place ratherthan dynamically conditioned or producible hydrocarbons in place.In the latter case, the recovery factor can be significantly higher.The dynamic conditioning forms a much sounder basis for thesubsequent identification of flow units.

Relationship Between Cutoffs and the Results of Simula-tion.From a theoretical standpoint, cutoffs are not strictly neces-sary in a 3D numerical simulation study. In fact, each petrofacies(or petrophysical rock type) in the geological model could becharacterized with specific capillary pressure and relative perme-ability functions in the simulator, and these functions unequivo-cally determine the ability of the fluid to flow under all possiblecircumstances. In reality, however, the identification and the ap-plication of cutoffs at the geological modeling stage is beneficial to

the dynamic modeling because it avoids time-consuming flowcomputations between cells with very poor characteristics. Indeed,

it is well known that the numerical performance of the simulatorimproves significantly when low-volume cells of poor reservoircharacter are eliminated. Thus, from a practical standpoint, theapplication of net-pay cutoffs as described above does reinforcethe synergy between the static and the dynamic models. This state-ment is substantiated by the incorporation of net-to-gross reservoirwithin preliminary sensitivity studies, which can provide usefulprojections of the volume of reservoir that is connected for differ-ent cutoff scenarios.

One further noteworthy issue is how to accommodate tightgas-bearing intervals that do not satisfy net-reservoir criteria asapplied at wells, but which contribute to production through cross-flow away from the wellbore as pressure differentials arise be-

tween permeable and tight beds. These contributions take the formof enhancements to recovery as critical depletion levels are at-tained. If no cutoffs are applied to the dynamic model, simulationat a sufficiently fine grid scale may result in a recovery factor inexcess of 100% for the more permeable intervals. If cutoffs areapplied, some late-onset gas will be excluded. A decision to applycutoffs at a particular scale will be governed by projections ofdifferential pressure decline and flow response. This dichotomyreinforces the need for a depletion scenario before decisions can bemade on how and where cutoffs are to be applied. It also re-emphasizes the iterative nature of integrated reservoir studies. Yetagain, this example links to the commercial nature of cutoffs. If,for example, gas prices were low, the reservoir might have to beabandoned before depleting the tight gas intervals. If, on the otherhand, gas prices were high, additional compression would be cost-

effective, and this would allow the reservoir to be produced to alower pressure, which would, in turn, lead to a higher gas recoveryfrom the tight intervals.

Conclusions

There is no generally accepted method for the identification ofpetrophysical cutoffs and, thence, net pay. Yet, it has been dem-onstrated that without the systematic quantification of cutoffs,there can be a highly significant degradation of those petrophysicalalgorithms that are a primary vehicle for evaluating reservoir prop-erties. Moreover, examples confirm that different approaches todefining cutoffs yield different reservoir models, so it is imperativethat cutoffs be fit for purpose [i.e., they are compatible (1) with theapproach taken for the evaluation of hydrocarbons in place or forthe estimation of ultimate hydrocarbon recovery and (2) with the

intended reservoir-depletion mechanism]. A structured methodol-ogy has been developed to accommodate these different require-

Fig. 10Illustration of the sensitivity of original oil in place to the porosity cutoff, which can be dynamically conditioned.



13/15

ments by basing cutoff definitions on reservoir-specific criteriathat take account of the storage and flow of hydrocarbons. Thismethodology draws upon physical rock typing, a proper reconcili-ation of petrophysical partitioning where this does not correspondto the geological architecture, upscaling of algorithms to the simu-lator scale, and the relationship between cutoffs and the results ofnumerical simulation.

Key benefits of a properly conditioned set of petrophysicalcutoffs include a more exact characterization of a reservoir and,thence, a better synergy with the dynamic reservoir model, mani-fested through a more efficient attainment of a functional historymatch. Thus, the model more successfully predicts the behavior ofthe reservoir, thereby providing an energy company with the op-

portunity to optimize the value of the asset.

Nomenclature

k permeability, md

Rmf mud-filtrate resistivity, m

Rt formation resistivity, m

Rw formation-water resistivity, m

Rxo flushed-zone resistivity, m

R1 pseudo formation resistivity factor (undisturbed zone)

R2 pseudo formation resistivity factor (flushed zone)

Sh hydrocarbon saturation

Sw water saturation

Swirr irreducible water saturation

Vsh shale volume fraction

porosity

viscosity, cp

Subscripts

c parametric cutoff

Acknowledgments

The authors are obliged to Ian Beck for his helpful review ofthe manuscript.

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15/15

70. Fosvold, L. et al.: Volumes Before and After Exploration Drilling:

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SI Metric Conversion Factors

cp 1.0* E03 Pas

ft 3.048* E01 m

*Conversion factor is exact.

Paul F. Worthington is a senior technical manager withGaffney, Cline & Assocs. and a visiting professor in petroleumgeoscience and engineering at Imperial College, U. of Lon-don. His principal interests are integrated reservoir studies forthe estimation of reserves, for equity determination, and forreservoir management. Worthington holds doctorates in engi-

neering geophysics and applied geology and has publishedmore than 80 technical papers in the field of engineering geo-science. He is a past president of the Soc. of Petrophysicistsand Well Log Analysts (SPWLA) and has twice served as a Dis-tinguished Lecturer for SPE and as Chair of the SPE FormationEvaluation Committee. Worthington is Editor of Petrophysicsand a Deputy Editor of Petroleum Geoscience. He is a char-tered geologist and a chartered engineer in the United King-dom. Luca Cosentino is currently Manager of the ReservoirModeling & Characterization Dept. of Eni, Milan, Italy. Previ-ously, he was in charge of the Reservoir Studies Dept. at Eniheadquarters, Milan, and before that was a project managerwith Beicip-Franlab. His main interests are related to the devel-opment and deployment of new technologies for geological

modeling and reservoir simulation. He has published more than20 technical papers in the areas of reservoir characterizationand simulation, geostatistics, and fractured reservoirs, as wellas a book on integrated reservoir studies, published by EditionsTechnip, Paris. He has served on the Steering and ProgramCommittees of several SPE, European Assn. of Geoscientistsand Engineers (EAGE), and American Assn. of Petroleum Ge-ologists (AAPG) Annual Meetings, and he has also served as aTechnical Editor for SPE.

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Documents

The Role of Cutoffs in Integrated Reservoir Studies (2)