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Abstract

We focus on minimizing the number of reservoir simulation runs and conserving geological realism of the solutions when solving the history matching problem. Geological a priori information is taken into account by means of multiple point statistics borrowed from training images (conceptual geological models). Then production data and prior information are integrated into a single differentiable objective function, minimizer of which has a high posterior value. Solving the proposed optimization problem for an ensemble of different starting models, we obtain a set of solutions honoring both data and prior information.

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/content/papers/10.3997/2214-4609.20132053
2013-11-17
2021-11-27
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http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.20132053
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