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Wang, F. P., and F. J. Lucia, 2012, Reservoir modeling and simulation of the Fullerton Clear Fork reservoir, Andrews County, Texas, in S. C. Ruppel, ed., Anatomy of a giant carbonate reservoir: Fullerton Clear Fork (Lower Permian) field, Permian Basin, Texas: Studies in Geology 63, p. 111143.

DOI:10.1306/13341541St633527

Copyright copy2012 by The American Association of Petroleum Geologists.

Reservoir Modeling and Simulation of the Fullerton Clear Fork Reservoir, Andrews County, Texas

Fred P. Wang,1 F. Jerry Lucia2

1Bureau of Economic Geology, The University of Texas at Austin, Austin, Texas, U.S.A.
2Bureau of Economic Geology, The University of Texas at Austin, Austin, Texas, U.S.A.

ACKNOWLEDGMENTS

We thank Julia Gale, James Jennings, and Stephen C. Ruppel for providing extensive critical review comments that greatly improved the content and quality of the manuscript. Terry Anthony and David Smith, from ExxonMobil Corporation, openly shared their knowledge of field operations and data and offered valuable feedback on modeling results. Lana Dieterich edited the manuscript. The illustrations were prepared with the assistance of the graphics group at the Bureau of Economic Geology (BEG). The support of this research by the Landmark Graphics Corporation via the Landmark University Grant Program is acknowledged. The publication is authorized by the director of BEG.

ABSTRACT

Simulation studies and three-dimensional (3-D) reservoir modeling were conducted as part of an integrated geologic, petrophysical, and geophysical effort to better define the distribution of remaining oil and the opportunities for a more effective recovery of remaining hydrocarbons. Two 3-D reservoir models—a 2000-ac window model and a fieldwide model—were built using a cycle-based geologic framework and rock-fabric–dependent petrophysical properties. A comprehensive sensitivity study on volumetrics was conducted using the fieldwide model, and reservoir simulation was performed in a 1600-ac area in the window model.

Original oil in place (OOIP) is a complex function of log-data quality, mapping parameters, vertical resolution of the 3-D grid, oil-water contact, and cutoff values in porosity, permeability, and water saturation. The high vertical-resolution 3-D model calculates higher OOIP than the 36-layer cycle-based model by 8 to 30%, depending on the cutoff criteria. Because permeability is a function of porosity and rock fabric, the permeability cutoff is equivalent to rock-fabric-dependent porosity or water saturation cutoffs and is less sensitive to grid vertical resolution than porosity and water saturation cutoffs.

The simulation study was divided into two phases: sensitivity analysis and history matching. The sensitivity study was used to evaluate and rank the importance of reservoir parameters affecting production performance. During simulation, oil relative permeability for primary recovery has a strong effect on recovery from waterflooding. Because fractures and breccias are common in testing and core data, negative skin factors (or effective wellbore radii) were used to simulate near-wellbore fractures, and permeability values in the lower Wichita were modified to simulate karst-related breccias. Through history matching, optimal fluid and rock properties were determined.

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