Enhanced geothermal systems (EGSs) expand geothermal energy production in reservoirs with low natural permeability by inducing fractures or exploiting existing fracture networks to improve permeability and fluid circulation. In this context, fault-damage zones (FDZs) are particularly relevant because they control fracture connectivity, govern localized permeability enhancement, and act as critical pathways for fluid migration and stress redistribution. These zones strongly influence the mechanical and hydraulic properties of the reservoir rock mass, thereby affecting stimulation efficiency and long-term system performance. Accurate characterization of these zones is thus necessary for a successful stimulation to avoid unresponsive/disconnected areas or trigger seismic activity. In this study, we focus on OPTV data collected at 11 boreholes strategically positioned to intersect the major fault-damage zones at the Grimsel Test Site (GTS), Switzerland. The OPTV datasets include significant artifacts generated by drilling operations and previous hydraulic stimulation experiments, which must be filtered to isolate the natural fracture network. While structural geology studies have long recognized complex damage-zone architectures (e.g., Kim et al., 2004 ), such architectural detail is not always incorporated into reservoir-scale models. In several site-specific reservoir modeling studies, damage zones have been represented as simplified planar discontinuities without explicit resolution of internal damage-zone architecture (e.g., Amann et al., 2018). However, fracture-network structure and the finite, spatially variable thickness of damage zones exert primary control on mechanical anisotropy and hydraulic behavior. Explicit delineation of damage-zone thickness is therefore essential for reducing structural uncertainty in reservoir characterization. To address these issues, we develop a workflow to build an accurate model of the damage zones and characterize the fractures within them from the OPTV datasets of In-Situ Stimulation and Circulation (ISC) experiment at the GTS. First, we remove all artificial fractures based on orientations and stress field measurements. Next, we use statistical analysis of cumulative fracture frequencies to delineate damage zones. Based on our analysis, we suggest two areas as key targets for stimulation: (1) an inner damage zone indicated by high deformation frequency and steep slope in the cumulative fracture distribution, and (2) an outer damage zone with lower deformation frequency and gentler slope. Previous stress-characterization studies at GTS (Krietsch et al., 2017; 2018) have shown that damage zones are associated with perturbed stress conditions, characterized by a drop in minimum stress magnitude and a change in stress orientation as major damage zones are approached. Our method improves the accuracy of damage zone delineation by constraining their true thickness from OPTV data. By integrating cumulative fracture frequency analysis and geological context, we were able to establish a robust framework for identifying and depicting damage zone architecture. These findings enhance our ability to optimize stimulation, thereby supporting the development of efficient and reliable EGSs that contribute to economically viable and environmentally sustainable energy production.
Türkdoğan et al. (2026) studied this question.