Quantifying the heterogeneity of shale through statistical combination of imaging across scales |
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| Authors: | Shabnam J Semnani Ronaldo I Borja |
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| Institution: | 1.Department of Civil and Environmental Engineering,Stanford University,Stanford,USA |
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| Abstract: | Shale is a highly heterogeneous material across multiple scales. A typical shale consists of nanometer-scale pores and minerals mixed with macroscale fractures and particles of varying size. High-resolution imaging is crucial for characterizing the composition and microstructure of this rock. However, it is generally not feasible to image a large sample of shale at a high resolution over a large field of view (FOV), thus limiting a full characterization of the microstructure of this material. We present a stochastic framework based on multiple-point statistics that uses high-resolution training images to enhance low-resolution images obtained over a large FOV. We demonstrate the approach using X-ray micro-tomography images of organic-rich Woodford shale obtained at two different resolutions and FOV. Results show that the proposed technique can generate realistic high-resolution images of the microstructure of shale over a large FOV. |
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