Probabilistic Induced Seismicity Assessment (PISA): A THM-Coupled Sensitivity Analysis

The mitigation of seismic risk is a fundamental requirement for the successful development of geothermal projects. Fluid injection and extraction alter the subsurface stress field through pore pressure diffusion, poroelastic stressing, and thermal stressing. Historical cases, such as those in Basel (2006) and Pohang (2017), underscore the necessity for robust hazard assessment. However, predicting fault reactivation remains a challenge due to the complex interaction of thermo-hydro-mechanical (THM) processes and inherent uncertainties in subsurface properties.

This study introduces PISA (Probabilistic Induced Seismicity Assessment), an open-source workflow developed to quantify these uncertainties. The tool integrates Gmsh for automated mesh generation and OpenGeoSys (OGS) for multi-physical simulations. Using a Design of Experiments (DoE) approach, we conduct a comprehensive sensitivity analysis involving 27 variable parameters to identify the key drivers for fault reactivation. The model is based on a simplified three-layer stratigraphy (overburden, aquifer, and underburden), focusing on a wide range of geomechanical and thermal properties, including initial stress state, Young’s modulus, Poisson’s ratio, Biot coefficient, specific heat capacity, and thermal expansivity.

The workflow simulates ten years of continuous injection and production within a fully coupled THM framework. A distinct methodological feature is the post-processing assessment of fault stability: fault planes are stochastically inserted into the simulated stress field, where the Mohr-Coulomb failure criterion is applied to evaluate the destabilization of faults. This decoupling allows for a high-throughput screening of various geological scenarios. The primary objective is to identify which parameters, beyond operational variables such as flow rate and injection temperature, exert the greatest influence on fault stability, thereby enabling operators to prioritize critical subsurface characteristics during exploration prior to field development.