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Abstract

AAPG Bulletin, V. 88, No. 7 (July 2004), P. 885-904.

Copyright copy2004. The American Association of Petroleum Geologists. All rights reserved.

Fault-seal analysis using a stochastic multifault approach

William R. James,1 Lee H. Fairchild,2 Gretchen P. Nakayama,3 Susan J. Hippler,4 Peter J. Vrolijk5

1ExxonMobil Upstream Research Co., P.O. Box 2189, Houston, Texas
24614 Baldwin Creek Dr., Mt. Hood, Oregon; email: [email protected]
3deceased
4ExxonMobil Exploration Company, 233 Benmar, Houston, Texas; email: [email protected]
5ExxonMobil Upstream Research Co., P.O. Box 2189, Houston, Texas; email: [email protected]

AUTHORS

Bill James earned his B.S. degree in geology from Earlham College and a Ph.D. from Northwestern University in 1968. He moved on to careers at the Corps of Engineers and the U.S. Geological Survey before starting at Exxon Production Research (now ExxonMobil Upstream Research) in 1979. He worked there, specializing in statistical applications in geology, assessment, and seal analysis, until his recent retirement.

Lee Fairchild has a B.A. degree in geology from the University of California, Berkeley, and an M.S. degree and a Ph.D. from the University of Washington. He joined Exxon Production Research (now ExxonMobil Upstream Research) in 1985, working on structural geology and fault-seal analysis. In 1999, he moved to Starpath Exploration as a geophysicist, prospecting in south Texas. In 2001, he began an independent consulting business.

Gretchen Nakayama earned her B.S. and M.S. degrees from the State University of New York, Rochester, and her Ph.D. in geology from the University of California, Davis, in 1990. She started her career at Exxon Production Research (now ExxonMobil Upstream Research) immediately, specializing in fault-seal analysis. We are saddened by our recent loss of Gretchen to cancer.

Susan Hippler has a B.A. degree in geology from Augustana College and a Ph.D. from the University of Leeds (1989). She then joined Exxon Production Research (now ExxonMobil Upstream Research) as an expert in fault-zone characterization and fault-zone migration. She transferred to ExxonMobil Exploration Co. in 1996, specializing in applications of integrated trap analysis to exploration, development, and production problems.

Peter Vrolijk earned his B.S. and M.S. degrees from the Massachusetts Institute of Technology and his Ph.D. in geology from the University of California, Santa Cruz, in 1982. In 1989, he joined Exxon Production Research (now ExxonMobil Upstream Research), doing research on a wide range of topics, including most recently fault-seal analysis and fault transmissibility.

ACKNOWLEDGMENTS

The authors thank ExxonMobil, its Malaysian affiliate ExxonMobil Exploration and Production Malaysia Inc., Petronas, Sable Offshore Energy Inc. and its partners Shell, Imperial Oil Ltd., and ExxonMobil Canada for permission to publish this paper. We thank Eric Schmidtke, Mohd. Tahir Ismail, and Stan Malkiewicz for obtaining permission. David Reynolds and David Phelps provided material for the paper. Brooks Clark, Steve Davis, and Rod Meyers helped formulate the goals and subject matter of the manuscript. Yao Chang and Brooks Clark were instrumental in software development. Reviews by Eric Schmidtke, Emery Goodman, Tom Hauge, Dave Reynolds, Tom Bultman, George Ramsayer and AAPG reviewers Laurel Alexander, Terrilyn Olson, Graham Yielding, and John Lorenz improved this manuscript; their time and dedication are greatly appreciated. The authors are indebted to our many colleagues at ExxonMobil who have greatly improved stochastic multifault analysis through their discussions and application of the technique.

Please direct inquiries regarding reprints or further information to Peter Vrolijk.

ABSTRACT

We have developed a stochastic multifault method for analysis of the impact of stratigraphic uncertainty on cross-fault leakage at sand-sand juxtapositions. This method assumes that all sand-sand juxtapositions leak across the fault. Stratigraphic uncertainty is modeled by stochastic variation of stratigraphic stacking. Structural uncertainty is addressed through variation of the input. Our objectives were to quantitatively predict the impact of uncertainties in stratigraphic and structural input and to simulate the complex system of structural spills and juxtaposition leak points that control hydrocarbon contact levels in traps with stacked reservoir systems and many faults.

Three examples demonstrate how this stochastic multifault method has helped us evaluate uncertainty and understand complex leak fill-and-spill controls. The Ling Gu prospect demonstrates that widespread cross-fault leakage on two crestal faults with throw changes that exceed seal thickness causes only a single hydrocarbon column to accumulate in multiple-stacked reservoirs. This column is controlled by a juxtaposition leak point on a third, deeper fault. We have learned from examples like Ling Gu that the relative size of throw change and seal thickness is a fundamental control on the probability of cross-fault juxtapositions. An example at prospect A demonstrates the sensitivity of hydrocarbon entrapment to small faults in a sand-prone interval with thin seals. The prospect A analysis shows that if seals are thin, faults or channel incisions below seismic resolution can leak hydrocarbons out of stacked reservoirs that are interpreted as unfaulted on seismic data. This introduced significant predrill uncertainty and risk. Guntong field demonstrates that a thin sand in a juxtaposed seal interval can introduce large uncertainty in the prediction of hydrocarbon columns.

These examples and many other analyses using the method demonstrate how small changes in stratigraphic and structural input to a fault-seal analysis can introduce significant uncertainty in the predicted range of hydrocarbon volumes. Such uncertainties need to be directly and systematically accounted for in a fault-seal analysis.

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