Li Yu, Haonan Li, Yue Wu, Weihao Wang, Xinyuan Zhang
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引用次数: 0
Abstract
In the process of harnessing geothermal energy, the enduring effects of thermal cycling on granite within the geothermal reservoir led to alterations in rock permeability. This, in turn, directly impacts the efficiency of thermal energy extraction. Hence, delving into the micro-permeability dynamics of granite is imperative to understand the characteristics of prevalent fractures. Employing micro-CT technology, we meticulously extract and analyze the pores of granite samples, unveiling the distribution patterns of pores and micro-permeability variations under successive thermal cycles. The resultant three-dimensional pore model vividly showcases the evolving pore structures during both heating and cooling cycles. Notably, the distribution curve of granite pore volume adheres to a chi-square distribution. Through the utilization of pore volume distribution curves, we categorize rock pores into four distinct types: micropores, mesopores, macropores, and fractures. Both quantitatively and visually, micropores and mesopores predominate, while a fraction of pores gradually transitions into sizable fractures. By employing suitable representative elements to construct the flow field within the large pore model and subsequently calculating permeability, we observe a positive correlation between porosity, permeability, and cyclic temperature-induced damage. Notably, the estimated permeability closely aligns with the measured values, exhibiting an acceptable margin of error. Furthermore, under the influence of thermal cycle-induced damage, the flow simulation demonstrates a noticeable increase in the number of flow lines, consequently resulting in enhanced permeability. This effectively validates the accuracy of the flow simulation based on micro-CT results.
期刊介绍:
Computational Geosciences publishes high quality papers on mathematical modeling, simulation, numerical analysis, and other computational aspects of the geosciences. In particular the journal is focused on advanced numerical methods for the simulation of subsurface flow and transport, and associated aspects such as discretization, gridding, upscaling, optimization, data assimilation, uncertainty assessment, and high performance parallel and grid computing.
Papers treating similar topics but with applications to other fields in the geosciences, such as geomechanics, geophysics, oceanography, or meteorology, will also be considered.
The journal provides a platform for interaction and multidisciplinary collaboration among diverse scientific groups, from both academia and industry, which share an interest in developing mathematical models and efficient algorithms for solving them, such as mathematicians, engineers, chemists, physicists, and geoscientists.