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A reconstruction method of porous media integrating soft data with hard data
  • ISSN号:1001-6538
  • 期刊名称:科学通报(英文版)
  • 时间:0
  • 页码:1876-1885
  • 语言:中文
  • 分类:TP311.13[自动化与计算机技术—计算机软件与理论;自动化与计算机技术—计算机科学与技术] TK124[动力工程及工程热物理—工程热物理;动力工程及工程热物理—热能工程]
  • 作者机构:[1]Department of Modern Mechanics, University of Science and Technology of China, Hefei 230027, China, [2]Research Center of Oil and Natural Gas, University of Science and Technology of China, Hefei 230027, China, [3]Key Laboratory of Software in Computing and Communication of Anhui Province, University of Science and Technology of China Hefei 230027. China
  • 相关基金:Supported by the National Basic Research Program of China (Grant No. 2006CB705805) and National Natural Science Foundation of China (Grant Nos. 10672159, 10702069)
  • 相关项目:使用同步辐射光进行细观渗流研究
中文摘要:

多孔的媒介的三维的重建具有到液体流动的机制的研究的大意义。多孔的媒介的真实三维的结构的数据是有用的在多孔的媒介描述不规则的 topologic 结构。当仅仅难的数据或没有有条件的数据是可得到的时,多孔的媒介的重建将是不精密的。重建的结果能是更精确的,用在重建期间的软数据。与难数据集成软数据,一个方法基于多重点的 geostatistics (MPS ) 被建议重建多孔的媒介的三维的结构。 variogram 曲线和渗透,由格子 Boltzmann 方法( LBM )计算了,重建的图象和从真实体积获得的目标图象,数据被比较,证明把软数据和难数据用作有条件的数据的重建的多孔的媒介的结构的特征很类似于真实的卷数据的那些。

英文摘要:

The three-dimensional reconstruction of porous media is of great significance to the research of mechanisms of fluid flow. The real three-dimensional structural data of porous media are helpful to describe the irregular topologic structures in porous media. The reconstruction of porous media will be inaccurate while only hard data or no conditional data are available. Reconstructed results can be more accurate, using soft data during reconstruction. Integrating soft data with hard data, a method based on multiple-point geostatistics (MPS) is proposed to reconstruct three-dimensional structures of porous media. The variogram curves and permeability, computed by lattice Boltzmann method (LBM), of the reconstructed images and the target image obtained from real volume data were compared, showing that the structural characteristics of reconstructed porous media using both soft data and hard data as conditional data are most similar to those of real volume data.

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