Porous Media Group
MSc project

History matching with reduced parameterization and fast streamline-based sensitivities, 2012

Fethia Ibrahim

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Advisors: Inga Berre, Tor Harald Sandve

Short description of project:

The main goal of history matching is to construct updated models capable of predicting the future performance of the reservoir more accurately. History matching method requires a solution of inverse problem to minimize the objective function. We applied regularization by parameterization for solving an ill-posed problem. Stepwise estimation strategy of parameterization structure is used to sequentially find new parameterization structure. Generalized travel time inversion (GTTI) is used in this thesis because it preserves the quasi-linear properties of travel time inversion while using the overall production data. Also we used Levenberg-Marquard optimization method. 

Link to thesis at BORA-UiB: Link