Local parameterization techniques, such as the gradual deformation method and the perturbation method, have already proved to be efficient for the integration of production data in a history matching process, considering regions of the reservoir associated to wells and defined according to physical or geometrical criteria. The aim of this study is to apply local parameterization techniques for the integration of 4D seismic data, using a new definition of regions based on the error on the seismic data. Each time seismic data are available, streamlines arriving in the parts of the reservoir with the highest error on these data are computed. The aim is to identify “influence areas” which should contribute to the behavior in the badly matched regions. The successive partitions can be used sequentially. Several methods are also proposed to combine them in a single partition. We intend in this study to improve the matching of the saturation distribution in the reservoir obtained at different times from seismic data interpretation. Considering for instance a constant porosity, an increase (decrease) of the permeability in the influence areas associated to a delay (advance) of the saturation front may improve the match. This can be achieved by modifying locally the mean of the permeability, using for instance a non-stationary mean to simulate the realization. We also propose to modify linear volume averages of the simulated petrophysical properties distributions, in one or several regions, using a kriging based methodology. Using this methodology, history matching processes of production and saturation data have been performed, optimizing local averages of the permeability and porosity realizations in the influence areas. The results show a strong improvement of the saturation match. They are also compared to the ones obtained with local gradual deformation based optimizations considering the same partitions of the reservoir.


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