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WELL INTERFERENCE MODELING WITH EXTENDED KALMAN FILTER
Abstract
The paper investigates the problem of determining the interinfluence of production and injection wells on a single development target. To solve this problem, we develop a stochastic reservoir model, which is a variant of extended Kalman filter. The model is some simplification of the hydrodynamic model. Its purpose is to estimate interwell permeability through production history. We discuss different variants of the model, which vary basing on availability of certain input data. On the baseline, the model can only depend on production and injection data. Information on the geological structure of wells, data on hydrodynamic studies of wells, data on geological and technical measures taken can also be added to the model. The calculation algorithm for the probabilistic characteristics of the model based on the ensemble Kalman filter is derived. The parameter estimation of the model is performed by applying the EM algorithm. We also develop the maximization step of this algorithm. Production forecast methods, variants for the coefficients of influence, and estimation methods for the amount of reserves in the reservoir are given for the trained model. The resulting interinfluence coefficients mainly depend on the interwell permeability. Methods for optimizing the operation of injection wells to improve oil production are also discussed. The result of application of the proposed method on the data of a real field is shown and discussed. The method proposed in the paper is compared to other methods solving the same problem.
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References6
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