1887

Abstract

Summary

In this work we propose a new history matching methodology that couples within the same framework the benefits of using geostatistical sequential simulation and the principles of ensemble Kalman filters, denominated as history matching based on ensemble updating. The main idea is to use simultaneously the relationship between petrophysical properties and the dynamical results in this process, to update the static properties at each iteration and to define the areas of influence of each well. This relation is established through the experimental non-stationary covariances, simply computed in the several forms of the Ensemble Kalman Filters (EnKF) for history matching of hydrocarbon reservoirs. The proposed iterative history matching procedure was applied to a 2D synthetic reservoir, built to mimic a classical 5-spot configuration with 4 producers located near the corners of the model and an injector well in the center of the grid. In order to assess the performance of the proposed approach, comparison tests were carried out in order to distinguish the advantages of the two main enhancements proposed: the use of areas of influence and the ensemble updating.

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/content/papers/10.3997/2214-4609.201600606
2016-05-30
2024-03-29
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