This work describes the combination of adjoint methods for derivative calculation with a trust-region Quasi-Newton optimization algorithm for solving history matching problems. The techniques employed allowed for the resolution of problems with a larger number of parameters, when compared to other approaches, based on derivative free optimization or the forward method for derivative calculation. Applications to both synthetic and real cases will be shown. A substantial improvement of the match was obtained in all examples. Problems with more than 250 parameters were solved efficiently. The ability to handle problems with a large number of parameters is exploited to discuss the possibility of accessing the uncertainty in the history matching process through exausting the space of possible models.
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