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DRUMHELLER, RICHARD E., and STEPHEN R. CARNEY, Anadarko Algeria Corporation, London, U.K.;ALAN J. SCOTT, A.J. Scott and Associates, Boulder, CO, and JEFFREY M. YARUS Smedvig Technologies, Houston,TX

Abstract: Reservoir Characterization of Fluvial Sandstones, Berkine Basin, Algeria: Contrasting Stochastic Modeling Techniques


The reservoir characterization of the Trias argilo-greseux inferieur (TAGI) fluvial sandstones in the Berkine Basin,Algeria has been assisted systematically with stochastic modeling methods since discovery and initial delineation of several oil fields over the past two years. The technical tools available for this purpose vary widely and have evolved dramatically during this time. 3D seismic data, delineation and development well information, interference well testing, initial production data, and field analog studies of selected outcrops contributed to this series of models.

Contrasting methodology for the construction of geologic models result in quite different reservoir descriptions which feed the reservoir simulation process.This in turn affects all decisions and investments concerning management of the reservoir.The selection and testing of the proper technological tools is therefore a critical step in the modeling process. All current methods have some inherent imperfections, so we are faced with the challenge of effectively adapting and utilizing available technology for best results.

While it might be expected that object-based modeling techniques should be more appropriate, the truncated gaussian methods for performing stochastic modeling are apparently performing very well for use with the TAGI fluvial systems. The newly available 'Plurigaussian' modeling technique allows the use of additional variograms within the same model which are allocated to certain facies within the reservoir, thus eliminating several time-consuming steps in the process.

AAPG Search and Discovery Article #[email protected] International Conference and Exhibition, Birmingham, England