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42109-AC9
Efficient Quantification of Uncertainties Associated with Reservoir Performance Simulations

Dongxiao Zhang, University of Oklahoma

In this study, we are attempting to develop efficient and accurate solutions to the stochastic problem with a novel stochastic decomposition method. During this year, we developed a probabilistic collocation method for efficiently and accurately solving stochastic flow problems with random coefficients and compared the method with various stochastic methods, and demonstrated it with problems of single and multi-phase flow in random porous media. During this year, we have also extended the KLME approach developed in previous years to nonstationary (statistically in homogeneous) random fields and combined KLME with the Kalman filtering scheme for efficient dynamic data assimilation with continuously available production data. The research led to three peer review publications in 2007. We are further developing and demonstrating the stochastic decomposition approach for large-scale multiphase flow in random porous media.

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