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Abstract

Ma, Y. Zee, Ernie Gomez, Barbara Luneau, Previous HitFabianNext Hit Iwere, Terry J. Young, and Dennis L. Cox, 2011, Integrated reservoir modeling of a Pinedale tight-gas reservoir in the Greater Green River Basin, Wyoming, in Y. Z. Ma and P. R. La Pointe, eds., Uncertainty analysis and reservoir modeling: AAPG Memoir 96, p. 89106.

DOI:10.1306/13301409M963458

Copyright copy2011 by The American Association of Petroleum Geologists.

Integrated Reservoir Modeling of a Pinedale Tight-gas Reservoir in the Greater Green River Basin, Wyoming

Y. Zee Ma,1 Ernie Gomez,2 Terry J. Young,3 Dennis L. Cox,4 Barbara Luneau,5 Previous HitFabianTop Iwere6

1Schlumberger, Greenwood Village, Colorado, U.S.A.
2Schlumberger, Greenwood Village, Colorado, U.S.A.
3BP America, Houston, Texas, U.S.A.
4BP America, Houston, Texas, U.S.A.
5Schlumberger, Greenwood Village, Colorado, U.S.A.
6Schlumberger, Greenwood Village, Colorado, U.S.A.

ACKNOWLEDGMENTS

We thank BP America and Schlumberger, Ltd., for permission to publish this work and the reviewers for their useful suggestions.

ABSTRACT

The Pinedale anticline is a large natural gas field in the Greater Green River Basin of Wyoming, located north of the giant Jonah field. Gas production is from overpressured fluvial channel sandstones of the Upper Cretaceous Mesaverde and Lance formations and the lower Tertiary “unnamed Tertiary” formation. To date, most studies have focused on the regional geology and potential hydrocarbon economics. This chapter discusses an integrated approach for reservoir modeling to reduce uncertainty in this tight-gas field development.

In this study, fluvial facies were defined using wireline logs. Object-based modeling was used to integrate well-log facies, object dimension, channel sinuosity, and orientation in building the three-dimensional facies model. The facies model was then used to guide petrophysical property modeling. Dependencies between rock properties were modeled using a geostatistical method. The final model honors the fluvial depositional characteristics and dependencies between the rock properties and was used for better uncertainty management in reservoir simulation and performance forecasting.

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