Print Email Facebook Twitter Model-reduced gradient-based history matching Title Model-reduced gradient-based history matching Author Kaleta, M.P. Hanea, R.G. Heemink, A.W. Jansen, J.D. Faculty Electrical Engineering, Mathematics and Computer Science Department Delft Institute of Applied Mathematics Date 2010-08-05 Abstract Gradient-based history matching algorithms can be used to adapt the uncertain parameters in a reservoir model using production data. They require, however, the implementation of an adjoint model to compute the gradients, which is usually an enormous programming effort. We propose a new approach to gradient-based history matching which is based on model reduction, where the original (nonlinear and high-order) forward model is replaced by a linear reduced-order forward model and, consequently, the adjoint of the tangent linear approximation of the original forward model is replaced by the adjoint of a linear reduced-order forward model. The reducedorder model is constructed with the aid of the proper orthogonal decomposition method. Due to the linear character of the reduced model, the corresponding adjoint model is easily obtained. The gradient of the objective function is approximated, and the minimization problem is solved in the reduced space; the procedure is iterated with the updated estimate of the parameters if necessary. The proposed approach is adjointfree and can be used with any reservoir simulator. The method was evaluated for a waterflood reservoir with channelized permeability field. A comparison with an adjoint-based history matching procedure shows that the model-reduced approach gives a comparable quality of history matches and predictions. The computational efficiency of the model-reduced approach is lower than of an adjoint-based approach, but higher than of an approach where the gradients are obtained with simple finite differences. Subject data assimilationhistory matchingmodel reductionproper orthogonal decompositionadjoint-free To reference this document use: http://resolver.tudelft.nl/uuid:4f5f5d33-5000-4025-b8bd-e07310fafd98 DOI https://doi.org/10.1007/s10596-010-9203-5 Publisher Springer Verlag ISSN 1573-1499 Source Computational Geosciences, 15 (1), 2011 Part of collection Institutional Repository Document type journal article Rights © 2010 The Author(s). This article is published with open access at Springerlink.com Files PDF kaleta2010.pdf 1.29 MB Close viewer /islandora/object/uuid:4f5f5d33-5000-4025-b8bd-e07310fafd98/datastream/OBJ/view