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Abstract


 
Chapter from: CA 3: Stochastic Modeling and Geostatistics 
Edited by 
Jeffrey M. Yarus and Richard L. Chambers

Authors:
William M. Bashore, Udo G. Araktingi, Marjorie Levy and William J. Schweller

Methodology and Concepts

Published 1994 as part of Computer Applications 3
Copyright © 1994 The American Association of Petroleum Geologists.  All Rights Reserved.
 

Chapter 14

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Importance of a Geological Framework and Seismic Data Integration for
Reservoir Modeling and Subsequent
Fluid-Flow Predictions

William M. Bashore
Udo G. Araktingi
Reservoir Characterization Research and Consulting, Inc.
Fullerton, California, U.S.A.
Marjorie Levy
William J. Schweller
Chevron Petroleum Technology Company
La Habra, California, U.S.A.



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ABSTRACT

Fluid-flow simulation results are used extensively as reservoir performance predictions upon which to base economics for reservoir management decisions. The generation of numerical models for simulation purposes may be easily facilitated by computer-aided algorithms, regardless of the quality of data or input parameters. This study contrasts two different geological interpretation styles: lithostratigraphic and chronostratigraphic. Specifically, comparisons are made as to properly integrating seismic-based information and to potentially erroneous conclusions deduced from simulator predictions if the simulation models are built without a sound geological framework. Models derived from the two different correlation strategies using only well logs are compared. Seismic inversions are included within the chronostratigraphic framework as a third model type. Multiple realizations of each model type are input to a fluid-flow simulator. Selecting the appropriate simulation results is closely tied to the reservoir management objective in question. Histograms of breakthrough times indicate little difference between the well-only models of either correlation strategy, whereas water displacement patterns are significantly different. Models that have been conditioned by the seismic pseudologs show substantially different results for both breakthrough and displacement distributions, and the spread or uncertainty in breakthrough estimates is greatly reduced compared to the well-only model results.
 
 

 

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