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Updating geological facies models using the Ensemble Kalman filter

机译:使用Ensemble Kalman滤波器更新地质相模型

摘要

The invention relates to a method for history matching a facies geostatistical model using the ensemble Kalman filter (EnKF) technique. The EnKF is not normally appropriate for discontinuous facies models such as multiple point simulation (MPS). In the method of the invention, an ensemble of realizations are generated and then uniform vectors on which those realizations are based are transformed to Gaussian vectors before applying the EnKF to the Gaussian vectors directly. The updated Gaussian vectors are then transformed back to uniform vectors which are used to update the realizations. The uniform vectors may be vectors on which the realizations are based directly; alternatively each realization may be based on a plurality of uniform vectors linearly combined with combination coefficients. In this case each realization is associated with a uniform vector made up from the combination coefficients, and the combination coefficient vector is then transformed to Gaussian and updated using EnKF.
机译:本发明涉及一种用于使用集成卡尔曼滤波器(EnKF)技术来匹配相地统计模型的历史的方法。 EnKF通常不适用于不连续相模型,例如多点模拟(MPS)。在本发明的方法中,生成一组实现,然后在将EnKF直接应用于高斯矢量之前,将这些实现所基于的统一矢量转换为高斯矢量。然后将更新的高斯矢量转换回统一矢量,该矢量用于更新实现。统一矢量可以是直接基于其实现的矢量。可替代地,每个实现可以基于与组合系数线性组合的多个均匀矢量。在这种情况下,每个实现都与由组合系数组成的统一矢量相关联,然后将组合系数矢量转换为高斯并使用EnKF更新。

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