Three-Dimensional Stochastic Characterization of Shale SEM Images

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• 作者：Pejman Tahmasebi ; Farzam Javadpour ; Muhammad Sahimi
• 关键词：Shale ; gas ; Flow in nanoscale ; Reconstruction ; CCSIM
• 刊名：Transport in Porous Media
• 出版年：2015
• 出版时间：December 2015
• 年：2015
• 卷：110
• 期：3
• 页码：521-531
• 全文大小：1,632 KB
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• 作者单位：Pejman Tahmasebi (1) (2)
  Farzam Javadpour (1)
  Muhammad Sahimi (2)
  
  1. Bureau of Economic Geology, Jackson School of Geosciences, The University of Texas at Austin, Austin, TX, 78713, USA
  2. Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA, 90089-1211, USA
  
• 刊物类别：Earth and Environmental Science
• 刊物主题：Earth sciences
  Geotechnical Engineering
  Industrial Chemistry and Chemical Engineering
  Civil Engineering
  Hydrogeology
  Mechanics, Fluids and Thermodynamics
  
• 出版者：Springer Netherlands
• ISSN：1573-1634

文摘

Complexity in shale-gas reservoirs lies in the presence of multiscale networks of pores that vary from nanometer to micrometer scale. Scanning electron microscope (SEM) and atomic force microscope imaging are promising tools for a better understanding of such complex microstructures. Obtaining 3D shale images using focused ion beam-SEM for accurate reservoir forecasting and petrophysical assessment is not, however, currently economically feasible. On the other hand, high-quality 2D shale images are widely available. In this paper, a new method based on higher-order statistics of a porous medium (as opposed to the traditional two-point statistics) is proposed in which a single 2D image of a shale sample is used to reconstruct stochastically equiprobable 3D models of the sample. Because some pores may remain undetected in the SEM images, data from other sources, such as the pore-size distribution obtained from nitrogen adsorption data, are integrated with the overall pore network using an object-based technique. The method benefits from a recent algorithm, the cross- correlation-based simulation, by which high-quality, unconditional/conditional realizations of a given sample porous medium are produced. To improve the ultimate 3D model, a novel iterative algorithm is proposed that refines the quality of the realizations significantly. Furthermore, a new histogram matching, which deals with multimodal continuous properties in shale samples, is also proposed. Finally, quantitative comparison is made by computing various statistical and petrophysical properties for the original samples, as well as the reconstructed model. Keywords Shale-gas Flow in nanoscale Reconstruction CCSIM