18
AUTHORS Richard M. Jones Woodside Energy, 1 Adelaide Terrace, Perth, Western Australia, 6000, Australia; [email protected] Richard joined Woodside in September 2000 and is currently working in the Trap and Pres- sure Team, New Ventures. He graduated with a joint B.Sc. degree (with honors) in geology and economics from Keele University (1992) and a Ph.D. from Keele University (1996). He has worked extensively in the area of fault and top seal evaluation and has been involved with seals research programs in Europe, the United States, and Australia. Current interests include structural modeling, seal evaluation, wellbore stability, and Liverpool FC. Richard is a member of AAPG, PESA, and PESGB. Richard R. Hillis National Centre for Petroleum Geology and Geophysics, Australian Petroleum Cooperative Research Centre, Uni- versity of Adelaide, South Australia 5005, Australia; [email protected] Richard holds the State of South Australia Chair in Petroleum Reservoir Properties/Petrophysics at the National Centre for Petroleum Geology and Geophysics (NCPGG), Adelaide University. He graduated with a B.Sc. degree (with honors) from Imperial College (London, 1985), and a Ph.D. from the University of Edinburgh (1989). After seven years at Adelaide Uni- versity’s Department of Geology and Geophys- ics, Richard joined the NCPGG in 1999. His main research interests are in petroleum geo- mechanics and sedimentary basin tectonics. He has published approximately 50 papers and has consulted to many Australian and inter- national oil companies in these topics. Richard is a member of AAPG, American Geophysical Union, Australian Society of Exploration Geo- physicists, European Association of Geoscien- tists and Engineers, Geological Society of America, Geological Society (London), Petro- leum Exploration Society of Australia, Society of Exploration Geophysicists, and Society of Petroleum Engineers. An integrated, quantitative approach to assessing fault-seal risk Richard M. Jones and Richard R. Hillis ABSTRACT Fault sealing is one of the key factors controlling hydrocarbon accu- mulations and trap volumetrics and can be a significant influence on reservoir performance during production. Fault seal is, therefore, a major exploration and production uncertainty. We introduce a sys- tematic framework in which the geologic risk of faults trapping hy- drocarbons may be assessed. A fault may seal if deformation processes have created a mem- brane seal, or if it juxtaposes sealing rocks against reservoir rocks, and the fault has not been reactivated subsequent to hydrocarbons charging the trap. It follows from this statement that the integrated probability of fault seal can be expressed as {1 [(1 a)(1 b)]} (1 c), where a, b, and c are the probabilities of deformation process sealing, juxtaposition sealing, and of the fault being reacti- vated subsequent to charge, respectively. This relationship provides an assessment of fault-seal risk that integrates results from the crit- ical parameters of fault-seal analysis that can be incorporated into standard exploration procedures for estimating the probability for geologic success. The integrated probability of fault seal for each prospect can be visualized using the fault-seal risk web, which allows rapid comparison of success and failure cases through construction of prospect risk web profiles. The impact of uncertainty (U ) and the value of information (VOI) for each aspect of fault sealing on the overall fault-seal risk may be determined via the construction of data webs and the rela- tion U = [1 {( P nw)/ n}] 100, where nw is the value given to each data web parameter and n is the number of data web com- ponents. For example, the data web components required to assess fault reactivation risk are the orientation and magnitude of the in-situ principal stresses, pore pressure, fault architecture, and the geo- mechanical properties of the fault. Risking of the Apollo prospect, Dampier subbasin, North West shelf, Australia is presented as a worked example. Fault-seal risking for the Apollo prospect has been conducted on 10- and 100-ft oil Copyright #2003. The American Association of Petroleum Geologists. All rights reserved. Manuscript received July 31, 2002; provisional acceptance August 27, 2002; revised manuscript received October 8, 2002; final acceptance October 10, 2002. DOI:10.1306/10100201135 AAPG Bulletin, v. 87, no. 3 (March 2003), pp. 507 – 524 507

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  • AUTHORS

    Richard M. Jones Woodside Energy,1 Adelaide Terrace, Perth, Western Australia,6000, Australia;[email protected]

    Richard joined Woodside in September 2000and is currently working in the Trap and Pres-sure Team, New Ventures. He graduated witha joint B.Sc. degree (with honors) in geologyand economics from Keele University (1992)and a Ph.D. from Keele University (1996). Hehas worked extensively in the area of fault andtop seal evaluation and has been involved withseals research programs in Europe, the UnitedStates, and Australia. Current interests includestructural modeling, seal evaluation, wellborestability, and Liverpool FC. Richard is a memberof AAPG, PESA, and PESGB.

    Richard R. Hillis National Centre forPetroleum Geology and Geophysics, AustralianPetroleum Cooperative Research Centre, Uni-versity of Adelaide, South Australia 5005,Australia; [email protected]

    Richard holds the State of South Australia Chairin Petroleum Reservoir Properties/Petrophysicsat the National Centre for Petroleum Geologyand Geophysics (NCPGG), Adelaide University.He graduated with a B.Sc. degree (with honors)from Imperial College (London, 1985), anda Ph.D. from the University of Edinburgh(1989). After seven years at Adelaide Uni-versitys Department of Geology and Geophys-ics, Richard joined the NCPGG in 1999. Hismain research interests are in petroleum geo-mechanics and sedimentary basin tectonics.He has published approximately 50 papers andhas consulted to many Australian and inter-national oil companies in these topics. Richardis a member of AAPG, American GeophysicalUnion, Australian Society of Exploration Geo-physicists, European Association of Geoscien-tists and Engineers, Geological Society ofAmerica, Geological Society (London), Petro-leum Exploration Society of Australia, Societyof Exploration Geophysicists, and Society ofPetroleum Engineers.

    An integrated, quantitativeapproach to assessingfault-seal riskRichard M. Jones and Richard R. Hillis

    ABSTRACT

    Fault sealing is one of the key factors controlling hydrocarbon accu-

    mulations and trap volumetrics and can be a significant influence on

    reservoir performance during production. Fault seal is, therefore, a

    major exploration and production uncertainty. We introduce a sys-

    tematic framework in which the geologic risk of faults trapping hy-

    drocarbons may be assessed.

    A fault may seal if deformation processes have created a mem-

    brane seal, or if it juxtaposes sealing rocks against reservoir rocks,

    and the fault has not been reactivated subsequent to hydrocarbons

    charging the trap. It follows from this statement that the integrated

    probability of fault seal can be expressed as {1 [(1 a)(1 b)]}(1 c), where a, b, and c are the probabilities of deformationprocess sealing, juxtaposition sealing, and of the fault being reacti-

    vated subsequent to charge, respectively. This relationship provides

    an assessment of fault-seal risk that integrates results from the crit-

    ical parameters of fault-seal analysis that can be incorporated into

    standard exploration procedures for estimating the probability for

    geologic success. The integrated probability of fault seal for each

    prospect can be visualized using the fault-seal risk web, which allows

    rapid comparison of success and failure cases through construction of

    prospect risk web profiles.

    The impact of uncertainty (U ) and the value of information(VOI) for each aspect of fault sealing on the overall fault-seal risk

    may be determined via the construction of data webs and the rela-

    tion U = [1 {(P

    nw) / n}] 100, where nw is the value givento each data web parameter and n is the number of data web com-ponents. For example, the data web components required to assess

    fault reactivation risk are the orientation and magnitude of the in-situ

    principal stresses, pore pressure, fault architecture, and the geo-

    mechanical properties of the fault.

    Risking of the Apollo prospect, Dampier subbasin, North West

    shelf, Australia is presented as a worked example. Fault-seal risking

    for the Apollo prospect has been conducted on 10- and 100-ft oil

    Copyright #2003. The American Association of Petroleum Geologists. All rights reserved.

    Manuscript received July 31, 2002; provisional acceptance August 27, 2002; revised manuscript receivedOctober 8, 2002; final acceptance October 10, 2002.

    DOI:10.1306/10100201135

    AAPG Bulletin, v. 87, no. 3 (March 2003), pp. 507524 507

  • 508 An Integrated, Quantitative Approach to Assessing Fault-Seal Risk

    columns to allow integration with volumetric probabilistic state-

    ments. The critical parameter for fault-seal risking at the Apollo

    prospect is the ability of disaggregation zone faults (low shale gouge

    ratio fault gouge) to support increasingly large hydrocarbon col-

    umns. Evaluation of the individual components for Apollo fault

    sealing indicates a = 0.3 (10-ft column) and a = 0.1 (100-ft column),b = 0.2, and c = 0.1. The overall probability of the Apollo trap-bounding fault sealing a 10-ft oil column is 0.4 or 40% (seal con-

    dition moderately unlikely). The likelihood that the fault seals oil

    columns greater than 100 ft is 0.3 (seal condition unlikely). Data web

    error margins for the Apollo prospect are 20% (juxtaposition un-

    certainty), 26% (fault-rock process uncertainty), and 27% (fault re-

    activation uncertainty). Recalculating each parameter by its un-

    certainty, for a 10-ft oil column, the upper value of integrated fault-

    seal risk is 0.5 (seal condition intermediate), and the lower value is

    0.3 (seal condition unlikely). The upper value of integrated fault-

    seal risk for a 100-ft oil column is 0.3 (seal condition unlikely), and

    the lower value is 0.2 (seal condition very unlikely). The variation in

    the Apollo final risk calculation reflects the lack of prospect-specific

    data. The greatest VOI benefit for Apollo fault-seal prospectivity is

    sedimentary architecture data.

    INTRODUCTION

    Hydrocarbon exploration and production strategies all involve an

    element of risk. As with any investment strategy, the goal of the

    venture capitalist is to minimize this risk. Geologic risk minimiza-

    tion should begin with a focused evaluation of the chance of success.

    That is determining the likelihood that all elements of the pe-

    troleum system required for economically viable volumes of hy-

    drocarbons to be developed and trapped have been satisfied. In

    an economic environment where prospects are now considered

    and drilled in a global context, it is essential that all prospects be

    ranked via comparable risking criteria. The presence of a sealed

    trap is one of the key factors in the evaluation of geologic risk for

    exploration prospects (Rose, 1992; Otis and Schneidermann, 1997;

    Watson, 1998). This paper presents a framework for quantifying

    the risk associated with the development of an intact seal for fault-

    bound prospects. This procedure

    enables geologic fault-seal risk to be incorporated into standardrisking procedures,

    allows data from different scales and pertaining to all fault-sealfailure mechanisms to be integrated,

    facilitates rapid comparison of known sealing/leaking fault boundtraps to identify key field or basin-scale trap integrity controls, and

    allows value of information (VOI) for critical data to be assessed.

    Previous techniques for risking the likelihood of fault sealing

    have tended to focus on one particular aspect of sealing such as

    ACKNOWLEDGEMENTS

    The authors are extremely grateful to colleaguesat the National Centre for Petroleum Geologyand Geophysics, Adelaide, Woodside Energy,and Shell for manuscript discussions. RussellDavies, Rob Knipe, Gavin Lewis, Frank Krieger,and James MacKay are thanked for providingconstructive and focused reviews that improvedearlier versions of the manuscript. The fault-sealrisk web as presented herein has evolved froma risk-web concept presented by former col-leagues of the first author at Rock DeformationResearch, University of Leeds. The integratedfault-seal risking procedure detailed in this paperforms part of the proprietary APCRC SealsConsortium. The consortium members Wood-side Energy, BHP Billiton, JNOC, Origin Energy,ChevronTexaco, Exxon-Mobil, Globex Energy,Santos, Anadarko Petroleum Corporation, andOMV are thanked for their permission topublish.

  • cross-fault reservoir-seal juxtaposition or membrane

    seals created by deformation, shale gouge ratio (SGR)

    or fault reactivation. There is no doubt that techniques

    such as SGR mapping (Yielding et al., 1997) have proved

    critical in reducing exploration and production fault-seal

    uncertainty. However, to fully risk fault sealing, an as-

    sessment of all possible mechanisms of seal failure (Fig-

    ure 1) should be undertaken and the results integrated

    into an overall fault-seal risk.

    This paper presents a methodology for combining

    the risks associated with juxtaposition seals, fault-rock

    membrane seals, and fault reactivation into a single in-

    tegrated, overall fault-seal risk. The fault-seal risk web

    as presented herein has evolved from a risk web concept

    presented by Knipe et al. (1995). Furthermore, because

    reactivation is a critical risk in the Australian context,

    and because assessing the risk of fault-seal breach caused

    by reactivation has received less attention than the other

    mechanisms, we summarize our methodology for assess-

    ing the risk of reactivation-related fault-seal breach.

    The risks associated with juxtaposition sealing, fault-

    rock membrane sealing, and fault reactivation are each

    assessed for the Apollo prospect in the Australian North

    West shelf. This case study is used to demonstrate how

    these risks are combined into an integrated, overall

    fault-seal risk that considers uncertainty and assists in

    determining data value of information.

    MECHANISMS OF FAULT SEALING

    Faults may seal if they juxtapose reservoir rocks against

    sealing rocks (Allan, 1989; Freeman et al., 1990; Yielding

    et al., 1997) or if the faulting process has generated a

    membrane seal, for example, by cataclasis (Antonellini

    and Aydin, 1994), cementation/diagenesis, framework

    grain-claymixing (Knipe,1992), or clay smearing (Bouvier

    et al., 1989; Gibson, 1994). It is not necessary for both

    juxtaposition and deformation process seals to be de-

    veloped in order for a fault to be sealing. If throw on the

    fault juxtaposes sealing rocks against reservoir rocks, no

    deformation process seal is required. Conversely, faults

    can seal where there is sand-sand juxtaposition and cata-

    clastic processes have reduced framework grain pore-

    throat apertures such that the fault zone itself acts

    as a membrane seal. For further details on cross-fault

    reservoir-seal juxtaposition seals or membrane seals

    created by deformation, the reader is referred to other

    papers in this issue and the references herein.

    Abundant evidence that active faults and fractures

    provide high-permeability conduits for fluid flow dur-

    ing deformation exists (e.g., Sibson, 1994; Barton et al.,

    1995). Juxtaposition or deformation process seals may

    be breached if the fault is reactivated subsequent to

    hydrocarbons charging the trap. Seal breach caused by

    fault reactivation has been recognized as a critical risk in

    the Australian context. For example, in the Timor Sea

    region, Neogene reactivation related to collision between

    the Australian and Southeast Asian plates has breached

    many Jurassic or older paleotraps (Shuster et al., 1998).

    Jones et al. (2000) has also presented microstructural

    evidence for in-situ related fault reactivation in the

    Otway basin, South Australia. In considering a pop-

    ulation of faults and fractures, those that are critically

    stressed (subject to a state of stress conducive to re-

    activation) are prone to act as conduits for fluid flow

    (Barton et al., 1995).

    Assessing the Risk of Reactivation-Related Fault-SealBreach

    Fault sealing caused by juxtaposition and deformation

    processes has received considerable attention, and tech-

    niques for the analysis of such (e.g., Allan diagrams, jux-

    taposition diagrams and shale smear algorithms) are

    widely applied. However, the risk of seal breach caused

    by reactivation, although recognized (e.g., Nybakken,

    1991; Grauls and Baleix, 1994), has received some-

    what less attention. Our methodology for assessing the

    risk of seal breach caused by fault reactivation was de-

    veloped in response to the recognition that reactivation

    is a critical risk in the Australian context.

    We combine knowledge of the in-situ stress field

    with that of fault geometry to assess the likelihood of

    reactivation of mapped faults and associated seal breach

    in the in-situ stress field. Other techniques have sim-

    ilarly used information on in-situ stress and fault geom-

    etry to investigate dynamic fault-sealing properties

    (e.g., Morris et al., 1996; Ferrill et al., 1999; Wiprut and

    Zoback, 2000; Finkbeiner et al., 2001). However, all

    of these techniques assume cohesionless frictional fail-

    ure of the fault rock. Dewhurst and Jones (2002) have

    demonstrated that preexisting faults may not be cohe-

    sionless. Thus, knowledge of the fault-rock failure en-

    velope should be incorporated into predictions of fault

    reactivation.

    In-situ stress is determined from wellbore geome-

    chanical data such as borehole breakouts as described,

    for example, by Bell (1996). Fault orientations (dip and

    dip direction) are determined from seismic interpreta-

    tion, based on the offset between reflector terminations

    Jones and Hillis 509

  • at a fault. Knowledge of the fault-rock failure envelope

    can be determined from laboratory testing of intact fault

    rocks (see Dewhurst and Jones, 2002). Given the above

    information, there are three critical stages to assessing re-

    activation risk.

    1. A three-dimensional (3-D) Mohr diagram represent-

    ing the state-of-stress and failure envelope for the

    fault is constructed. The risk of reactivation of a plane

    of any orientation can be expressed by the increase in

    pore pressure (P) required to reduce the effectivestresses such that failure occurs on that plane, i.e.,

    horizontal distance on a 3-D Mohr diagram between

    a plane and the failure envelope.

    2. The reactivation risk (P) is plotted on a polar plotof normals to all planes.

    3. Fault geometry is transposed onto the reactivation

    risk plot and the reactivation risk is determined for

    the fault. The P value should be determined atvarious points along the fault, especially where signif-

    icant changes in orientation and/or dip are observed

    as risk of seal breach can vary significantly along a single

    plane.

    In addition to permitting the use of realistic fault-

    rock failure envelopes derived from laboratory tests, this

    methodology allows the likelihood of reactivation by

    all modes of failure to be assessed in a single calculation,

    as opposed to the separate slip and dilation tendency

    analyses of Ferrill et al. (1999). The P technique issummarized in Figure 2 and described in greater detail

    in Mildren et al. (2002).

    QUANTIFYING THE RISK OF FAULT-SEALBREACH

    The fundamental tenet of our approach follows from

    the above discussion in that a fault may seal by mem-

    brane seal if deformation processes have created an ef-

    fective seal, or if displacement juxtaposes sealing rocks

    against reservoir rocks, and the fault has not been re-

    activated subsequent to hydrocarbons charging the

    trap.

    Expressed alternatively, a fault is sealing if both

    cross- and up-fault flow are inhibited. Juxtaposition or

    deformation process seals inhibit the former, and the

    latter occurs if the fault is reactivated. This approach

    forms the basis of BHP Petroleums logic tree for as-

    sessing fault seal (Watson, 1998); however, the above

    has not been previously converted into a quantitative

    relationship describing integrated fault-seal risk.

    It can be demonstrated that the integrated prob-

    ability of a fault sealing (FS) can be expressed as

    FS f1 1 a1 bg 1 c 1

    where a, b, and c are the probabilities of deformationprocess sealing, juxtaposition sealing, and of the fault

    being reactivated subsequent to the trap being charged

    with hydrocarbons, respectively. A value of zero is as-

    signed where there is no chance of a parameter providing

    a seal, and one is assigned where a parameter definitely

    provides a seal. For reactivation parameter c, a valueof 1 indicates the fault is definitely reactivated. The

    three factors influencing fault sealing are assumed to be

    510 An Integrated, Quantitative Approach to Assessing Fault-Seal Risk

    Figure 1. Classification and critical risk factors of hydrocarbon seals.

  • independent (the probability of independent events

    occurring is the product of their individual probabil-

    ities). To combine the probabilities of juxtaposition

    and deformation process sealing, the probability of

    neither providing a seal should be considered. The

    probability of neither juxtaposition nor deformation

    process sealing being developed is (1 a)(1 b).The probability of juxtaposition and/or deformation

    processes providing a seal is the complement of this,

    i.e., {1 [(1 a)(1 b)]}. The product of the

    Jones and Hillis 511

    Figure 2. Summary work flow of risking faultreactivation and seal breach through nucleationof structural permeability networks.

  • probability of juxtaposition and/or deformation pro-

    cesses providing a seal and the probability that

    reactivation has not led to the seal being breached

    gives the overall probability of a fault sealing (FS),

    i.e., {1 [(1 a)(1 b)]} (1 c).The fault-seal risk web (FSRWeb) illustrates the

    multiparameter approach required for integrated fault-

    seal risking and presents an example of probability

    and seal condition (Figure 3). The seal condition scale

    is analogous to industry standard probability scales,

    yet with the recognition that a seal condition value

    of 0.5 does not reflect an equivocal probability of

    sealing. Under this scheme, a risk value of 0.5 is in-

    terpreted to reflect an intermediate chance of sealing

    hydrocarbons. The Sherman-Kent scale may be used

    for eliciting and quantifying confidence judgements

    (Table 1).

    The construction of the fault-seal risk profile allows

    a rapid visual assessment of the prospect risks and their

    relative importance. Comparison of adjacent known

    sealing/leaking traps and their fault-seal risk profile

    may aid identification of key regional fault-seal issues.

    INCORPORATING UNCERTAINTY

    A key factor in any risking procedure is the influence of

    uncertainty. Indeed, the more uncertainty that attends

    a given prospect, the more a systematic expression of

    subjective probability is needed (Rose, 1992). Each

    component of fault-seal risk, as expressed by equation

    1, has a component of uncertainty. This uncertainty

    reflects a less than complete data set and technical

    limitations of geologic data (e.g., seismic resolution).

    Juxtaposition, deformation processes, and reactivation

    fault-seal uncertainties are calculated via construction

    of data webs (Figures 46). Each data web provides a

    framework for evaluating the uncertainty for each

    aspect of fault-seal risk and its associated impact on

    overall fault-seal risk.

    The uncertainty (U ) associated with each aspectof fault-seal risk is calculated by the summation of the

    data web values given to each critical parameter (nw),divided by the total number of parameters (n). Criticalparameters to be included in each data web were chosen

    with reference to key publications (e.g., Allan, 1989;

    Knipe, 1992; Yielding et al., 1997, Hillis, 1998). U ex-pressed as a percentage can be written as

    U 1 X

    nw=n 100 2

    The juxtaposition uncertainty illustrated in Figure

    4 is expressed as

    U 1 f0:9 0:6 0:9=3g 100 20% 3

    This value, in conjunction with deformation process

    and reactivation aspects, may be used to identify the

    upper and lower integrated fault-seal risk values by

    positively and negatively factoring each parameter of

    equation 1 by their respective uncertainty value. These

    data can be used to assess VOI and determine whether

    it is economically viable to generate additional data to

    reduce prospect uncertainty. Traps that are risked as

    marginal (borderline geologic success), yet having a

    high uncertainty may be worth additional investment,

    especially when calculated returns are believed to be

    high. The VOI for the Apollo prospect is discussed in

    the following worked example.

    A WORKING EXAMPLE: APOLLO PROSPECT,NORTH WEST SHELF, AUSTRALIA

    Geologic Setting

    The Apollo prospect is a rollover structure on the down-

    thrown side of the northeast-southwesttrending Egret

    fault system, Dampier basin, permit WA-10-R, North

    West shelf, Australia (Figure 7). The reservoir target is

    the Tithonian synrift Angel Formation having the Ber-

    riasian Forestier Claystone forming the cap seal (Figure

    8). The main risk for Apollo prospectivity is fault seal-

    ing caused by the presence of large potential leak win-

    dows generated by sand-sand juxtaposition. A detailed

    review of the fault-seal workflow and interpretation are

    beyond the scope of this publication. Therefore, only a

    technical summary of prospect fault-seal evaluation

    is given so as to illustrate application of the risking

    methodology.

    Juxtaposition Analysis

    Seismic mapping suggests Egret fault displacement

    maintains Angel sand-sand communication through-

    out the Apollo prospect. Construction of detailed Allan

    diagrams confirms Angel sand-sand juxtaposition over

    closure (see Figure 9). Juxtaposition fault sealing is

    therefore assigned a high-risk seal condition of 0.2 (seal

    condition very unlikely). In this example, no distinc-

    tion in juxtaposition seal risk is made between 10- and

    100-ft oil columns as mercury injection capillary pressure

    512 An Integrated, Quantitative Approach to Assessing Fault-Seal Risk

  • Jones and Hillis 513

    Figu

    re3

    .Fa

    ult-

    seal

    risk

    web

    and

    seal

    prob

    abili

    tyco

    nditi

    on(s

    eete

    xtfo

    rde

    tails

    ).

  • data from offset wells indicates the membrane seal

    capacity of equivalent nonreservoir strata is capable of

    supporting greater buoyancy pressures than both col-

    umns would exert. In this example, maintaining a con-

    stant juxtaposition parameter value between 10- and

    100-ft column scenarios simply reflects the risk that

    such a seal mechanism exists. The Apollo juxtaposition

    data web is illustrated in Figure 4. Three-dimensional

    seismic over the prospect has allowed fault-zone archi-

    tecture to be accurately mapped; hence, a confidence

    514 An Integrated, Quantitative Approach to Assessing Fault-Seal Risk

    Table 1. Sherman-Kent Scale for Eliciting and Quantifying Confidence Judgements*

    Proven; definitely true 98100%

    Virtually certain; convinced 9098%

    Highly probable; strongly believe; highly likely 7590%

    Likely; probably true; about twice as likely to be true as untrue; chances are good 6075%

    Chances are about even, or slightly better than even or slightly less than even 4060%

    Could be true but more probably not; unlikely; chances are fairly poor;

    two or three times more likely to be untrue than true 2040%

    Possible but very doubtful; only a slight chance; very unlikely indeed; very improbable 220%

    Proven untrue; impossible 02%

    *Meyer and Brooker, 1991; Watson, 1998.

    Figure 4. Juxtaposition data web. Exam-ples of the position on each parameterspine with respect to data quality andquantity are given. In the example illus-trated, the combined juxtaposition uncer-tainty is 20% with the greatest uncertaintyrelated to sedimentary architecture (seetext for details).

  • value of 0.9 is ascribed to this parameter on the data

    web spine. Sedimentary architecture is less certain with

    recognized facies variability across the basin and gamma

    log-defined strata from adjacent wells. A data web con-

    fidence value of 0.6 is ascribed to sedimentary architec-

    ture reflecting a lack of prospect-specific data. Principal

    fault throw magnitude is ascribed a data web confidence

    value of 0.9 reflecting 3-D seismic mapping of the fault

    zone. Integrated uncertainty with respect to a juxtapo-

    sition seal mechanism is calculated as 20% (equation 2

    and Figure 4).

    Fault-Rock Process Analysis

    Prediction of fault-rock processes using Juxtaposition

    software (Knipe, 1992) focused on the likelihood of

    sealing through sand-sand deformation given the like-

    lihood of reservoir-reservoir juxtaposition. Both grain

    boundary (dissagregation zones) and cataclastic pro-

    cesses occur through clean (< 15% clay content) sand

    deformation yet under distinct effective stress mag-

    nitudes (Fisher and Knipe, 1998). Timing of faulting

    relative to burial history is, therefore, a crucial element

    to consider when evaluating membrane seal formation.

    Structural reconstruction of the prospect indicates depth

    of burial at the time of faulting to be less than 2 km

    at relatively low vertical effective stress and early in

    the reservoir burial history. Faulting of clean Angel

    Formation sands is modeled to generate disaggregation

    zones (Figure 10a) that, without diagenetic enhance-

    ment, will act as leak windows and allow cross-fault

    communication. Shale gouge ratio values correspond-

    ing to reservoir-reservoir deformation range from ap-

    proximately 14 to 16 reflecting faulting of relatively

    clean/low GR sands (Figure 10b). Microstructural and

    petrophysical analysis of core scale faults from an ad-

    jacent field confirms the presence of disaggregation

    zone faults in the Angel Formation strata. No post-

    deformation diagenetic processes were observed in

    these faults, suggesting that diagenetic enhancement

    of Apollo disaggregation zone seal capacity is unlikely.

    Mercury injection capillary pressure evaluation of these

    faults indicates an oil seal capacity of less than 1 ft.

    Hydrocarbon trapping greater than the 10-ft oil column

    through fault-rock process sealing was subsequently

    risked as 0.3 (seal condition unlikely). The potential for

    Jones and Hillis 515

    Figure 5. Fault rock process data webfor the Apollo prospect. Integrated un-certainty associated with fault rock pro-cess sealing is 26% (see text for details).

  • the trap-bounding fault baffling an oil column greater

    than 100 ft is risked as 0.1 (seal condition extremely un-

    likely). The fault-rock processes seal uncertainty is cal-

    culated as 26% (Figure 5).

    Fault-Seal Reactivation Analysis

    As discussed above, reactivation of faults nucleates

    networks of structural permeability that can result in

    across- and up-fault hydrocarbon migration. P ex-presses the likelihood of seal failure (see Figure 2). A

    high P value represents a relatively low-risk fault asa significant pore pressure increase is required to in-

    duce failure. Structural permeability modeling of the

    Apollo prospect fault shows the majority of the fault

    within closure to be low-reactivation risk having Pof approximately 38 MPa. However, a high-risk (P< 5 MPa) fault section is identified related to a change

    in fault strike (see Figure 11). This high-risk, low Pregion is coincident with the southern margin of clo-

    sure for the Egret field on the footwall side of the

    Apollo structure. Egret is underfilled, and, as charge is

    not believed to be limited, it is feasible that structural

    permeability networks may be responsible for con-

    trolling the volume of hydrocarbons in the footwall

    trap. Given that P for the Apollo prospect fault isabout 38 MPa, a seal condition of 0.1 (extremely un-

    likely that the fault is reactivated) is used for risking

    the likelihood of seal breach. The fault reactivation

    uncertainty is calculated as 27% (Figure 6).

    INTEGRATED FAULT-SEAL RISKING OF THEAPOLLO PROSPECT

    Quantitative fault-seal risking was conducted on the

    likelihood of supporting 10- and 100-ft oil columns

    to allow integration with prospectivity and probabi-

    listic volumetric statements. The critical structural risk

    parameter for Apollo is the ability of disaggregation zone

    faults (low SGR fault gouge) to support increasingly large

    hydrocarbon columns. Given the above assessments of

    516 An Integrated, Quantitative Approach to Assessing Fault-Seal Risk

    Figure 6. Reactivation data web for theApollo prospect. Integrated uncertaintyassociated with the likelihood that thefault seal is unreactivated is 27% (seetext for details).

  • Jones and Hillis 517

    Figure 7. Three-dimensional two-way traveltime image of Apollo (hanging wall) and Egret (footwall) prospects. Fault plane istransparent to allow visualization of both footwall and hanging-wall prospects. Figure insert: location of North West shelf, petroleumprovince, and Dampier subbasin.

  • 518 An Integrated, Quantitative Approach to Assessing Fault-Seal Risk

    Figure 8. Generalized Triassic/Jurassic stratigraphy of Dampier subbasin.

    Figure 9. Allan diagram ofApollo fault. Note the presenceof large areas of sand-sandjuxtaposition in prospect clo-sure.

  • Jones and Hillis 519

    Figu

    re1

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  • 520 An Integrated, Quantitative Approach to Assessing Fault-Seal Risk

    Figu

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  • Jones and Hillis 521

    Figu

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  • the individual components of fault sealing [a = 0.3 (10-ftcolumn) and a = 0.1 (100-ft column); b = 0.2; c = 0.1]and utilizing equation 1, the probability that the Apollo

    trap-bounding fault seals a 10-ft oil column is 0.4 (seal

    condition moderately unlikely), see Figure 12. The like-

    lihood that the fault seals oil columns greater than 100 ft

    is 0.3 (seal condition unlikely).

    Data web errors for the Apollo prospect are 20%

    (juxtaposition uncertainty), 26% (fault-rock process

    uncertainty), and 27% (fault reactivation). Recalculat-

    ing each parameter by its uncertainty, the upper

    (positive) value of integrated fault-seal risk for a 10-ft

    oil column is 0.5 (seal condition intermediate) The

    lower integrated risk value for a 10-ft oil column is 0.3

    (seal condition unlikely). The upper value of integrated

    fault-seal risk for a 100-ft oil column is 0.3 (seal con-

    dition unlikely). The lower integrated risk value for a

    100-ft oil column is 0.2 (seal condition very unlikely).

    The variation in the final Apollo risk calculation re-

    flects the lack of prospect-specific data and the critical

    importance of accurately determining the probability of

    fault-seal failure through reactivation. Data employed

    in the final integrated fault-seal risk calculations are

    summarized in Table 2.

    These data indicate the greatest uncertainty and,

    therefore, most influencing parameters on Apollo fault-

    seal prospectivity are sedimentary architecture/clay con-

    tent and fault failure envelope. Given that the average

    fault P within closure is approximately 38 MPa, theApollo fault is unlikely to be reactivated under present-

    day in-situ stress conditions (hence, c = 0.1). Therefore,there appears little business driver or technical justi-

    fication to collect further information on the failure

    envelope of the fault. Following this rationale, the

    greatest VOI for Apollo is in obtaining additional data

    on the sedimentary architecture and clay content var-

    iability. Value of information analysis is increasingly

    being used as a discriminator to justify data acquisition.

    Value of information can be thought of as value of a

    project executed with certain information minus value

    of that project executed without that information.

    Hence, VOI components include benefit of informa-

    tion and cost of acquiring information. The cost of ac-

    quiring the analysis is relatively simple to ascertain in

    that most data have a monetary value attached. The

    degree of uncertainty and time range in project net

    present value (NPV) influence the VOI benefit. For

    example, early in project development, the range in

    potential NPV may be large as many factors such as

    field compartmentalization and migration pathway may

    carry significant uncertainty. At this stage in project ap-

    praisal, key data would carry a high VOI as it is likely

    to significantly influence the decision-making process.

    As projects mature, the impact of additional data on

    reducing the NPV range is likely to have relatively minor

    impact as overall project uncertainty will have been

    reduced and time to revenue will be shorter. Hence,

    data will carry a relatively reduced VOI benefit. The

    cost of acquiring additional data needs to be evaluated

    with reference to impact on overall prospectivity. Given

    the impact of sedimentary architecture and clay content

    data on Apollo fault-seal prospectivity range and poten-

    tial time to revenue, VOI benefit in this case is likely to

    outweigh the cost of acquisition or reduce uncertainty

    range through modeling. VOI justification of this state-

    ment is that additional data may sufficiently reduce

    522 An Integrated, Quantitative Approach to Assessing Fault-Seal Risk

    Table 2. Apollo Fault Risking and Seal Parameter Uncertainty*

    Apollo Risking Parameters

    Risk Web Values Juxtaposition Fault-rock Processes Reactivation

    10-ft oil column 0.2 0.3 0.1

    100-ft oil column 0.2 0.1 0.1

    Data Web Components and

    Confidence Parameters Fault-zone architecture: 0.9 Depth of burial: 0.9 Stress regime: 0.7

    Sedimentary architecture: 0.6 Sedimentary architecture: 0.6 Failure envelope: 0.6

    Fault throw: 0.9 Fault throw: 0.9 Fault architecture: 0.9

    Hydrocarbon column height: 0.8

    Stratigraphic clay content: 0.6

    Data Web Uncertainty 20% 26% 27%

    *See text for details.

  • stratigraphic uncertainty to the extent that a drill-or-

    not-to-drill decision can be made. In the negative case,

    a decision to divert well costs could be made, thus sav-

    ing considerable dollar value. Whether to always re-

    duce key uncertainties as identified by the fault-seal

    risking process should be made in conjunction with VOI

    studies.

    DISCUSSION

    If a fault is considered to be definitely reactivated sub-

    sequent to hydrocarbon charge, the integrated fault-

    seal risk determined using the methodology herein is

    zero, i.e., no chance of fault seal. We believe that the

    assumption that fault reactivation postcharge leads to

    seal breaching, and loss of hydrocarbons from the trap

    provides a reasonable and practical basis for the as-

    sessment of fault-seal exploration risk. However, the

    reactivation risk is a critical parameter that must be

    assessed with caution.

    We follow Sibsons (1992) fault-valve model that

    proposes that fault rupture leads to the creation of

    fracture permeability and fluid discharge. Only during

    fault movement, or at stresses close to criticality, does

    the fault act as a conduit for fluid flow. Hence, reacti-

    vation must occur postcharge for the seal to be breached.

    The fault may again seal after reactivation. For example,

    fluid flow along the fault may promote cementation, or

    fault movement may assist the development of deforma-

    tion process seals, and the fault may again seal hydro-

    carbons once quiescent, if the reservoir is recharged.

    Further reactivation would again cause the fault to leak,

    hence, the process may be cyclic (Sibson, 1992; 1994).

    Increasing pore pressure while the fault is quiescent

    may play a critical role in initiating the next phase of

    reactivation.

    The assumption that fault reactivation postcharge

    leads to seal breach is valid in the Australian context

    where numerous fault traps, the bounding faults of

    which have been reactivated, are associated with re-

    sidual columns witnessed by geochemical analysis of

    fluid inclusions in the reservoir (e.g., Lisk et al., 1998).

    The reactivated trap-bounding faults are commonly

    associated with anomalous hydrocarbon-related diage-

    netic zones and in some cases present-day seepage of

    hydrocarbons into the water column (OBrien and

    Woods, 1995). These faults have clearly been reacti-

    vated postcharge and acted as conduits for the escape

    of hydrocarbons. In other basins, reactivation may be

    relatively minor and may not always lead to loss of an

    entire accumulation. The risk posed by reactivation can

    therefore be thought of as area specific and should be

    calibrated by the type of observations that confirms its

    significance in the Australian context. Furthermore,

    the P methodology for assessing the risk of reactiva-tion and associated seal breach uses knowledge of the

    current in-situ stress field and is only appropriate if re-

    activation is occurring at the present day, or in a stress

    field similar to that of the present day. If reactivation

    occurred under a paleostress regime, then reactivation-

    related risk should be assessed with reference to that

    paleostress regime.

    The location of high-risk reactivation points rela-

    tive to trap geometry/spill point also needs to be con-

    sidered when producing a final integrated fault-seal

    risk statement. It is feasible that reactivation may occur

    downdip of the crest of the structure and may not breach

    the entire accumulation. Hence, one may wish to gen-

    erate a series of risk statements that link to volumetric

    statements that consider several scenarios, i.e., reac-

    tivation at the crest of the trap and/or reactivation of a

    section of the fault downdip from the crest but above

    the trap spill point. Regardless of the approach taken,

    it is critical that other members of the team are fully

    aware of the exploration/production implications as-

    sociated with the reactivation risk.

    CONCLUSIONS

    A quantitative assessment of fault-seal risk that in-

    tegrates parameters from different aspects of fault-seal

    analysis in a consistent framework may be determined

    if the risks associated with juxtaposition sealing, de-

    formation process sealing, and reactivation are known.

    The impact of uncertainty and VOI for each aspect of

    fault sealing may be determined via the construction

    of data webs and modification of equation 1. The fault-

    seal risk web profile provides a powerful tool for vi-

    sualizing each parameter probability of fault sealing and

    allows rapid comparison with proven success/failure

    prospect cases.

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