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首页> 外文期刊>Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of >Orthogonal Matching Pursuit for Enhanced Recovery of Sparse Geological Structures With the Ensemble Kalman Filter
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Orthogonal Matching Pursuit for Enhanced Recovery of Sparse Geological Structures With the Ensemble Kalman Filter

机译：正交匹配追踪，通过集成卡尔曼滤波增强稀疏地质结构的恢复

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摘要

Estimating the locations and the structures of subsurface channels holds significant importance for forecasting the subsurface flow and reservoir productivity. These channels exhibit high permeability and are easily contrasted from the low-permeability rock formations in their surroundings. This enables formulating the flow channels estimation problem as a sparse field recovery problem. The ensemble Kalman filter (EnKF) is a widely used technique for the estimation and calibration of subsurface reservoir model parameters, such as permeability. However, the conventional EnKF framework does not provide an efficient mechanism to incorporate prior information on the wide varieties of subsurface geological structures, and often fails to recover and preserve flow channel structures. Recent works in the area of compressed sensing (CS) have shown that estimating in a sparse domain, using algorithms such as the orthogonal matching pursuit (OMP), may significantly improve the estimation quality when dealing with such problems. We propose two new, and computationally efficient, algorithms combining OMP with the EnKF to improve the estimation and recovery of the subsurface geological channels. Numerical experiments suggest that the proposed algorithms provide efficient mechanisms to incorporate and preserve structural information in the EnKF and result in significant improvements in recovering flow channel structures.
机译：估计地下通道的位置和结构对于预测地下流量和储层生产率具有重要意义。这些通道显示出高渗透率，并且容易与周围环境中的低渗透率岩层形成对比。这使得能够将流道估计问题表述为稀疏场恢复问题。集成卡尔曼滤波器（EnKF）是一种用于地下储层模型参数（例如渗透率）的估计和校准的广泛使用的技术。但是，常规的EnKF框架没有提供有效的机制来合并有关各种地下地质结构的先验信息，并且常常无法恢复和保留流动通道结构。压缩感知（CS）领域的最新工作表明，在使用稀疏域进行估计时，使用诸如正交匹配追踪（OMP）之类的算法可以在处理此类问题时显着提高估计质量。我们提出了两种新的且计算效率高的算法，将OMP与EnKF相结合，以改善地下地质通道的估计和恢复。数值实验表明，所提出的算法为在EnKF中合并和保留结构信息提供了有效的机制，并显着改善了恢复流道结构的能力。

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