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AAPG Bulletin

Abstract

AAPG Bulletin, V. 88, No. 7 (July 2004), P. 905-921.

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

Multiple-point simulation integrating wells, three-dimensional seismic data, and geology

Yuhong Liu,1 Andrew Harding,2 William Abriel,3 Sebastien Strebelle4

1ExxonMobil Upstream Research Company, P.O. Box 2189, Houston, Texas 77252-2189; email: [email protected]
2ChevronTexaco Energy Technology Company, San Ramon, California; email: [email protected]
3ChevronTexaco Overseas Petroleum Company, San Ramon, California; email: [email protected]
4ChevronTexaco Energy Technology Company, San Ramon, California; email: [email protected]

AUTHORS

Yuhong Liu holds a Ph.D. in geological and environmental science from Stanford University (2003). She worked at the University of Petroleum, China, as an assistant professor and a lecturer from 1995 to 1999, working on industry projects related to petroleum geology and reservoir characterization. She joined ExxonMobil in 2003 and now works on geological modeling and geostatistics as a research geologist.

Andrew Harding holds an M.A. degree in physics from Trinity College, Cambridge, in Great Britain. He has worked in the oil industry since 1975, the last 23 years with ChevronTexaco. He presently is a consultant in reservoir modeling in San Ramon, California, and works on projects from around the world. Andrew is a chartered geologist of the Geological Society of London.

William Abriel (Bill) received his B.S. and M.S. degrees in geophysics (1978) from Pennsylvania State University. Joining Chevron Oil Company from 1978 to the present, he has been involved in many interesting projects in both operations and seismic research offshore and onshore in North and South America, Europe, Asia, Australia, and Africa. Bill is a member of the Society of Exploration Geophysicists (SEG), European Association of Exploration Geophysicists, and AAPG and the 2004 SEG Spring distinguished lecturer.

Sebastien Strebelle earned his Ph.D. at Stanford University in geological and environmental sciences in 2000. His research focuses on reservoir geomodeling and geostatistics. He is currently employed as a research geoscientist with ChevronTexaco.

ACKNOWLEDGMENTS

The authors thank ChevronTexaco Energy Technology Company, ChevronTexaco Overseas Petroleum Company, and affiliates for the permission to publish these results. The help provided by Rusty Gilbert, Karen Payrazyan, and the staff of ChevronTexaco Company is gratefully acknowledged. The authors also thank Andre Journel of Stanford University for reviewing this work.

ABSTRACT

There are two significant challenges in building a reservoir model integrating all available information. One challenge is that wells and seismic data measure the reservoir at different scales of resolution. The other challenge lies in how to account for conceptual geological knowledge with resolution at multiple scales.

In this paper, we present a case study of integrating Previous HitwellNext Hit data, seismic data, and conceptual geologic models. The Previous HitwellNext Hit and seismic data are of good quality, but conventional Previous HitwellNext Hit-seismic data calibration indicates that the seismic data are unable to fully differentiate sand from shale. The reason for this poor Previous HitwellNext Hit-seismic data calibration is that Previous HitwellNext Hit Previous HitlogNext Hit and seismic data measure the reservoir at different scales. Previous HitWellNext Hit logs are able to differentiate sand from shale, whereas seismic data are better at detecting larger scale depositional geometries.

A new workflow is presented to deal with this problem. First, principal component Previous HitanalysisNext Hit clustering is used to identify characteristic patterns of certain depositional facies, from which sandy and shaly channels are interpreted. Next, multiple-point geostatistical simulation is performed to build a depositional-facies model, which integrates both hard and soft data but also incorporates realistic depositional-facies geometries provided by our geological knowledge of this reservoir. Finally, different lithofacies (sand and shale) indicators and corresponding petrophysical properties are simulated honoring the limited Previous HitwellTop data.

The results show that not only are the geological features better reproduced, but also is the uncertainty about the reservoir significantly reduced because of a better integration of corresponding three-dimensional seismic data.

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