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The AAPG/Datapages Combined Publications Database

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Xu, W., K. Wrolstad, D. Kramer, P. Dooley, K. Domingue, and D. T. Vo, 2006, Brazos A-105 D-sand reservoir modeling by integration of seismic elastic inversion results with geostatistical techniques, in T. C. Coburn, J. M. Yarus, and R. L. Chambers, eds., Stochastic modeling and geostatistics: Principles, methods, and case studies, volume II: AAPG Computer Applications in Geology 5, p. 269-278.


Copyright copy2006 by The American Association of Petroleum Geologists.

Brazos A-105 D-Sand Reservoir Modeling by Integration of Seismic Elastic Inversion Results with Geostatistical Techniques

W. Xu,1 K. Wrolstad,2 D. Kramer,3 P. Dooley,4 K. Domingue,5 D. T. Vo6

1Unocal Thailand, Ltd. Bangkok, Thailand
2Unocal Exploration and Production Technology Sugar Land, Texas, U.S.A.
3International Reservoir Technologies, Inc. Lakewood, Colorado, U.S.A.
4Unocal Thailand, Ltd. Bangkok, Thailand
5Nexen Petroleum U.S.A. Inc. Dallas, Texas, U.S.A.
6Unocal Thailand, Ltd. Bangkok, Thailand


The authors are grateful for management and partner support for this integrated project. Special thanks go to Dave Bacchus (Unocal EampPT) for the petrophysical analyses performed in conjunction with this work. The Brazos A-105 Partnership comprises Spirit Energy 76 (Unocal), The Northwestern Mutual Life Insurance Company, and Mariner Energy. We also thank Petter Abrahamsen and another reviewer for their comments, which improved the submitted manuscript.


An integrated reservoir modeling study of the Bigenerina humblei (Big Hum) Miocene D-sand at Brazos A-105 field, offshore Texas, was conducted to predict the lateral extent of the reservoir, to build a porosity model for use in flow simulation and reserve evaluation, and to assess the uncertainty of the reserve estimation. Several geostatistical techniques for integrating well-log porosity with quantitative average porosity derived from a forward elastic model-based inversion method for three-dimensional seismic data were applied in this reservoir modeling study. Elastic modeling was necessary to predict the correct porosity-amplitude relationship for this reservoir because it is a class 2 type amplitude-vs.-offset reflection. The results of the study showed that if a reservoir is seismically resolved and properly imaged, elastic model-based inversion of the type employed can be used in conjunction with geostatistical methods to obtain a more complete reservoir description. These techniques were determined to have direct application to reservoir-flow modeling and hydrocarbon reserve volume estimation.

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