Prediction of permeability for porous media reconstructed using multiple-point statistics.
Prediction of permeability for porous media reconstructed using multiple-point statistics.
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DOI：
10.1103/physreve.70.066135
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发表时间：
2004-12
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影响因子：
--
通讯作者：
H. Okabe;M. Blunt
中科院分区：
文献类型：
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作者：
H. Okabe;M. Blunt
为了预测通过地质上真实的多孔介质的多相流，有必要对孔隙空间进行三维（3D）表征。我们使用基于二维（2D）薄片的多点统计作为训练图像来生成地质上真实的3D孔隙空间表征。薄片图像能够提供多点统计信息，其描述了多个空间位置之间的统计关系，并利用特定模式出现的概率。假设介质是各向同性的，就可以生成一个保留薄片中所见空隙空间典型模式的3D图像。该方法在贝雷砂岩上进行了测试，对于该砂岩有来自微计算机断层扫描（CT）的3D图像可用，结果表明，与往往低估连通性的两点统计方法相比，使用多点统计能够保留结构的长程连通性。此外，使用一个碳酸盐岩储层岩石的高分辨率2D薄片图像，通过所提出的方法重建3D结构。使用格子玻尔兹曼方法（LBM）计算统计图像的渗透率。结果与测量值相似，与直接在贝雷砂岩的微CT图像上计算出的渗透率相似，也与使用2D图像分析和有效介质近似法的预测结果相似。
To predict multiphase flow through geologically realistic porous media, it is necessary to have a three-dimensional (3D) representation of the pore space. We use multiple-point statistics based on two-dimensional (2D) thin sections as training images to generate geologically realistic 3D pore-space representations. Thin-section images can provide multiple-point statistics, which describe the statistical relation between multiple spatial locations and use the probability of occurrence of particular patterns. Assuming that the medium is isotropic, a 3D image can be generated that preserves typical patterns of the void space seen in the thin sections. The method is tested on Berea sandstone for which a 3D image from micro-CT (Computerized Tomography) scanning is available and shows that the use of multiple-point statistics allows the long-range connectivity of the structure to be preserved, in contrast to two-point statistics methods that tend to underestimate the connectivity. Furthermore, a high-resolution 2D thin-section image of a carbonate reservoir rock is used to reconstruct 3D structures by the proposed method. The permeabilities of the statistical images are computed using the lattice-Boltzmann method (LBM). The results are similar to the measured values, to the permeability directly computed on the micro-CT image for Berea and to predictions using analysis of the 2D images and the effective medium approximation.