Geomechanical dynamics in granite-dominated deep geothermal drilling: From mineral-scale thermal damage to macroscopic mechanical responses

Abstract

Deep geothermal energy is a stable, clean, and renewable resource vital to the transition to sustainable energy systems. However, extreme temperatures and hard rock formations in deep reservoirs pose geomechanical challenges to efficient and safe drilling. This paper reviews advances in geomechanical research for deep geothermal reservoir drilling, with the quantitative treatment center on granite and other crystalline basement reservoirs, for which the evidence base is most complete. First, it examines high-temperature mechanisms, including thermal expansion anisotropy in rock minerals and microcrack development associated with quartz phase transitions. It details the resulting degradation of rock strength, the brittle-ductile transition, and the staged nonlinear evolution of permeability and thermal conductivity. Next, addressing low rock-breaking efficiency caused by high confining pressure-induced suppression of crack propagation and enhanced ductility at elevated temperatures, the review summarizes the evolution from conventional mechanical breaking to advanced techniques such as combined axial-torsional impact, thermal stress assistance, and directed energy methods. It contrasts physics-based and data-driven models for drilling performance evaluation and parameter prediction, assessing their suitability for geothermal drilling conditions. From the thermo-hydro-mechanical (THM) multi-field coupling perspective, the review analyzes how drilling fluid cooling-induced transient thermal stresses cause wellbore wall tensile failure, triggering a feedback loop of lost circulation, cooling, and fracture propagation. It further evaluates wellbore stability failure criteria and dynamic lost circulation control strategies optimized for complex conditions. Finally, the review identifies key geomechanical challenges in deep geothermal drilling and outlines future directions, including intelligent evaluation systems, dynamic multi-field coupling models, and integrated engineering efficiency optimization.