Geothermal Reservoir Characterisation and Probability Analysis of Fractured Media at Grimsel Test Site, Switzerland

Exploitation of deep geothermal energy is considered as one of the most efficient renewable energy applications. In this sense, reservoir stimulation is established to extract geothermal energy from EGS (Enhanced Geothermal System) which is highly dependent on its in-situ structural properties: damage/shear zones, faults, fractures, its statistics and characteristics. In more detail, damage zones may behave like a conduit providing preferential pathways for fluid flow in otherwise impermeable rock such as granite or gneiss. To improve the reservoirs’ characteristics frequently hydro-shearing or hydro-fracturing are used. It is imperative to account for the natural heterogeneities of the reservoir particularly with respect to the existing fracture network. In this study, we analyze the pre-stimulation fracture network of the EGS experiments conducted at the Grimsel Test Site, in the Swiss Alps. We use original data acquired at the tunnel wall and in boreholes to constrain a probabilistic 3D model further used for H-M simulations of the enhancement experiments. Fracture analysis include scanline mapping, cluster analysis of the spatial distribution and density plots. Keywords: geostatistics, fracture analysis, DFN modeling, 3D geological modeling, geothermal energy