A multiple-point geostatistical reconstruction method of porous media using soft data and hard data

作者：Zhang Ting^*; Du Yi

来源：Journal of Computational Information Systems, 2014, 10(16): 7213-7224.

DOI：10.12733/jcis11741

• Curvilinear structures
• Fluid flow in porous media
• Geo-statistics
• Multiple grid
• Multiple-point
• Multiple-point geostatistics
• Soft data
• Three-dimensional reconstruction

Great progress has been made in the mechanics of fluids flow in porous media, which is based on Darcy's law and widely used in many engineering fields. The three-dimensional reconstruction of porous media is of great significance to the research of mechanisms of fluid flow in porous media. However, it is quite difficult to reconstruct the unknown information only by some sparse known data in the process of reconstruction. Therefore, some interpolation methods are used to reconstruct the unknown region for better results. Multiple-point geostatistics (MPS) integrating soft data with hard data has been proved to be a powerful tool to capture curvilinear structures or complex features in training images. Using soft data with hard data, one solution to capture large-scale structures while considering a data template with a reasonably small number of grid nodes is provided by the multiple-grid method. This method consists in scanning a training image using increasingly finer multiple-grid data templates instead of a big and dense data template. The experimental results demonstrate that multiple-grid data templates and MPS using both soft data and hard data as conditional data are practical in porous media reconstruction.

• 出版日期2014
• 单位上海大学