Process-based reconstruction of digital rock based on discrete element method considering thermal-mechanical coupling effect and actual particle shape

Abstract

The digital rock is a crucial platform for numerical simulations of pore-scale flow in various fields such as geo-energy, carbon (CO2) sequestration, and hydrogen (H2) storage. Under these conditions, rocks deform, and pore structures change due to temperature and stress effects. However, existing methods for reconstructing digital rocks, such as physical experimental, stochastic simulation, and machine learning, can not consider the influence of high temperature and stress. Therefore, a process-based reconstruction method based on the discrete element method (DEM) considering the thermal-mechanical coupling effect is proposed in this paper. Initially, the computed tomography (CT) images are segmented based on the watershed algorithm, and a contour database is established using the spherical harmonic analysis method. A clump template library is then constructed in PFC3D (Particle Flow Code in 3 Dimensions). Subsequently, the DEM model is established using clumps from the template library according to porosity and particle radius distribution, and the model's accuracy is evaluated based on two-point and linear path correlation functions. Micro-mechanical and thermal parameters between particles are calibrated, and different temperature and stress boundary conditions are applied to obtain digital rocks under varying conditions. Finally, digital rocks' geometric and topological structures under different conditions are analyzed, and permeability and relative permeability are calculated. Using Bentheim sandstone as an example, digital rocks are constructed under various temperature and stress conditions. The research findings indicate that high temperatures and stress result in decreased pore and throat radii, elongated throats, deteriorated connectivity, reduced porosity, and permeability, making the digital rocks more water-wet. This study provides theoretical guidance for the accurate pore-scale flow simulation of geo-energy fluids, CO2, and H2.