Abstract
Due to the influence of geological activities, fractures are commonly found in geological bodies. The fractures overlap and form a fracture network, which is the main channel for seepage and solute transport. The fracture network is deeply buried underground, and its full picture is difficult to observe. Usually, only the structural statistical data of the fracture network can be obtained, including the probability statistical distribution function of fracture properties such as size and occurrence. Therefore, there is a problem: how to infer the macroscopic flow and solute transport characteristics of the fracture network based on the fracture structural statistical data? To solve this problem, based on the percolation theory in statistical physics, the dimensionless finite-size scaling (FSS) hypothetical function of fracture network connectivity, permeability and diffusion coefficient is proposed. The FSS parameters can be obtained using the statistical distribution of relevant fracture properties. To verify the hypothesis function, a GPU-accelerated 3D random fracture network flow and transport simulation code was developed, and a large number of simulations of different working conditions were carried out. The FSS function was applied to the simulation data to verify its universality, and the conversion phenomenon of permeability scale dependence was theoretically revealed. The research results show the application potential of the dimensionless FSS function, and its example verification work can be strengthened in future research.
Brief Biography
Tingchang Yin's research interests are high-performance simulation and physical modeling of underground seepage and solute transport at pore/fracture/continuous scales. He has published more than ten papers (three as the first author) in journals such as Geophysical Research Letters and Computers and Geotechnics. He has won the National Scholarship, Su Wu Scholarship, etc.