Towards Large-Scale DRP Simulations: Generation of Large Super-Resolution images and Extraction of Large Pore Network Models
نویسندگان
چکیده
Representativity and accuracy of digital rock physics (DRP) simulations depend strongly on the size image volume resolution obtained. Even with one fastest DRP simulation techniques like pore network modelling, volumes have typically been limited to few cubic millimetres for highly resolved images. In this paper, a super-resolution technique named enhanced generative adversarial (ESRGAN) is used obtain well-resolved images large field view generate micro-CT enhancement factors × 4 8. Subsets resulting ESRGAN were tested against same (of acquisitions at high low resolution) by comparing petrophysical properties interest. Pore extraction multiphase results showed that distribution, porosity, permeability, drainage capillary pressure relative permeability curves obtained using more accurate. Large images, however, pose subsequent limitations as code needs lot memory process them (usually than 60 GB RAM 15003 voxels image). Thus, we present novel stitching strategy developed enable networks such Several validation cases method are presented test from stitched single- flow properties. Finally, our tool was two 3.6 million 9.2 elements, respectively, approximately 49003 voxels.
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ژورنال
عنوان ژورنال: Transport in Porous Media
سال: 2023
ISSN: ['0169-3913', '1573-1634']
DOI: https://doi.org/10.1007/s11242-023-01913-9