The use of gradient-based optimization methods in automatic history matching requires that the reservoir simulator provides the necessary derivative information in the most efficient way. The implementation of these techniques in existing complex simulators is a difficult task, however. This paper describes the implementation of the forward and adjoint methods for derivative calculation in a full-featured adaptive implicit black-oil simulator. To show how the derivative calculation methods can be used even outside the framework of standard optimization algorithms, a new algorithm for automatic history matching, based on the truncated singular value decomposition, is proposed. Application to simple synthetic cases shows promising results.

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