This study presents a systematic review of the latest progress in experimental studies and numerical modeling related to deep rock mechanics in recent years. The mechanical behavior and micro-damage mechanisms of deep rocks under the influence of multiple factors are elaborated, revealing that triaxial testing remains the most direct and effective method for investigating rock mechanics. With the rapid development of digital technologies and artificial intelligence, experimental approaches and observational techniques have experienced significant innovation, bringing about the considerably enhanced precision and applicability of rock mechanical research. The properties of deep rock mechanics are governed by various factors, among which mineral composition, pore structure, and the coupled effects of temperature and pressure are particularly critical. Numerical simulations play a vital role in deep rock mechanics studies. Specifically, the discrete element method (DEM) and finite element method (FEM) serve as crucial tools for analyzing both the micromechanical processes and macroscopic behaviors of rocks. Nevertheless, a major frontier in deep rock mechanics lies in establishing a quantitative correlation between rock micro-mechanical processes and their macroscopic mechanical behavior. Current studies are also subjected to several challenges, including the limited reproducibility of experimental results, constraints in accurately simulating deep subsurface environments, difficulties in quantitatively characterizing microstructural features, and obstacles in obtaining reliable simulation parameters. In future research, priority should be given to elucidating micro-mechanical mechanisms under multi-field coupling conditions, conducting systematic investigations of deep geological settings, and integrating advanced digital technologies. These efforts support the development of ultra-deep oil and gas extraction, the enhancement of geothermal systems, and stability assessment for deep underground engineering.
Building similarity graph...
Analyzing shared references across papers
Loading...
Zhuoyuan Ma
Shu Tao
Fan Yang
Archives of Computational Methods in Engineering
China University of Geosciences (Beijing)
Research Institute of Petroleum Exploration and Development
Beijing Institute of Petrochemical Technology
Building similarity graph...
Analyzing shared references across papers
Loading...
Ma et al. (Sat,) studied this question.
www.synapsesocial.com/papers/696ed06d6d8d470fca57abeb — DOI: https://doi.org/10.1007/s11831-026-10495-w