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首页> 外文期刊>Transport in Porous Media >Geostatistical Simulation and Reconstruction of Porous Media by a Cross-Correlation Function and Integration of Hard and Soft Data
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Geostatistical Simulation and Reconstruction of Porous Media by a Cross-Correlation Function and Integration of Hard and Soft Data

机译：互相关函数和硬，软数据集成的孔隙介质地统计学模拟和重构

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摘要

A new method is proposed for geostatistical simulation and reconstruction of porous media by integrating hard (quantitative) and soft (qualitative) data with a newly developed method of reconstruction. The reconstruction method is based on a cross-correlation function that we recently proposed and contains global multiple-point information about the porous medium under study, which is referred to cross-correlation-based simulation (CCSIM). The porous medium to be reconstructed is represented by a reference image (RI). Some of the information contained in the RI is represented by a training image (TI). In unconditional simulation, only the TI is used to reconstruct the RI, without honoring any particular data. If some soft data, such as a seismic image, and hard data are also available, they are integrated with the TI and conditional CCSIM method in order to reconstruct the RI, by honoring the hard data exactly. To illustrate the method, several two- and three-dimensional porous media are simulated and reconstructed, and the results are compared with those provided by the RI, as well as those generated by the traditional two-point geostatistical simulation, namely the co-sequential Gaussian simulation. To quantify the accuracy of the simulations and reconstruction, several statistical properties of the porous media, such as their porosity distribution, variograms, and long-range connectivity, as well as two-phase flow of oil and water through them, are computed. Excellent agreement is demonstrated between the results computed with the simulated model and those obtained with the RI.
机译：通过将硬（定量）和软（定性）数据与一种新开发的重建方法相结合，提出了一种用于多孔介质的地统计学模拟和重建的新方法。重建方法基于我们最近提出的互相关函数，并且包含有关正在研究的多孔介质的全局多点信息，这称为基于互相关的仿真（CCSIM）。要重建的多孔介质由参考图像（RI）表示。 RI中包含的某些信息由训练图像（TI）表示。在无条件仿真中，仅TI用于重建RI，而无需遵守任何特定数据。如果还提供了一些软数据（例如地震图像）和硬数据，则将它们与TI和有条件的CCSIM方法集成在一起，以通过精确地遵守硬数据来重建RI。为了说明该方法，对几种二维和三维多孔介质进行了模拟和重构，并将结果与​​RI提供的结果以及传统的两点地统计学模拟（即连续序列）生成的结果进行了比较。高斯模拟。为了量化模拟和重构的准确性，计算了多孔介质的几种统计属性，例如其孔隙率分布，变异函数和远程连通性，以及油和水通过它们的两相流动。用仿真模型计算的结果与用RI获得的结果之间显示出极好的一致性。

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