An integrated, quantitative AUTHORS approach to assessing · 508 An Integrated,Quantitative...

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-versity’s 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 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 andmagnitude 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.

AAPG Bulletin, v. 87, no. 3 (March 2003), pp. 507–524 507

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 standard

risking procedures,� allows data from different scales and pertaining to all fault-seal

failure mechanisms to be integrated,� facilitates rapid comparison of known sealing/leaking fault bound

traps 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 theApollo prospect in theAustralian 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 collisionbetween

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 effective

stresses 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 plot

of 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 at

various 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 is

summarized 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 Petroleum’s 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 ¼ f1 � ½ð1 � aÞð1 � bÞg � ð1 � cÞ ð1Þ

where a, b, and c are the probabilities of deformation

process 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 value

of 1 indicates the fault is definitely reactivated. The

three factors influencing fault sealing are assumed to be


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


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 4–6). 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 aspect

of 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). Critical

parameters 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 ¼ ½1 � ðX

nw=nÞ � 100 ð2Þ

The juxtaposition uncertainty illustrated in Figure

4 is expressed as

U ¼ ½1 � fð0:9 þ 0:6 þ 0:9Þ=3g � 100 ¼ 20% ð3Þ

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-southwest–trending 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



Figure3.Fault-seal

risk

web

andseal

probability

condition

(see

text

fordetails).

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


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

Proven; definitely true 98–100%

Virtually certain; convinced 90–98%

Highly probable; strongly believe; highly likely 75–90%

Likely; probably true; about twice as likely to be true as untrue; chances are good 60–75%

Chances are about even, or slightly better than even or slightly less than even 40–60%

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

two or three times more likely to be untrue than true 20–40%

Possible but very doubtful; only a slight chance; very unlikely indeed; very improbable 2–20%

Proven untrue; impossible 0–2%

*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


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 as

a 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 is

about 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


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


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.


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.


Figure10.Faultrock

type

predictionforApollo

prospect.N

otethedevelopm

entof

disaggregationzonesdueto

sand-sanddeform

ationprocessesat

loweffectivestress.These

zonesaremodeled

toform

leak

windows(see

textfordetails).Shalegougeratio

data

arepresentedforcomparison.

FW=footwall;HW

=hangingwall.


Figure11.Apollo

faultreactivationprediction.

Figure

left,

structural

perm

eabilitypoles-to-plane

stereonet.High-risk

faultsections

strike

between070and160anddipgreater

than

60j.

Figure

right,mapping

ofreactivationrisk

onto

faulttrace(see

textfordetails).


Figure12.A

pollo

fault-sealrisk

web,riskprofiles,andintegrated

prospectfault-sealrisk

statem

entsfor10-and100-ftoilcolum

ns.N

otetheincreasedfault-zone

processesseal

breach

risk

associated

with

thelarger

oilcolumn.

the individual components of fault sealing [a = 0.3 (10-ft

column) 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, the

Apollo 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


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 Sibson’s (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-

vationmust 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 (O’Brien 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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