Uncertainty Assessment of Geothermal Well Injectivity

Geothermal energy has the potential to significantly enhance energy production. A critical factor in the success of geothermal projects is injectivity, which must be evaluated considering subsurface uncertainties. Stochastic simulations of coupled temperature, flow, and rock mechanics can be used to quantitatively assess injectivity and the propagation of induced fractures towards faults and caprock. The findings are used to recommend operational parameters that maximize injectivity while ensuring safe operations under uncertainty. A simulation program was used that integrates coupled fluid-flow, plugging, temperature, and geomechanical effects. The model underwent testing for discretization and parameter ranges. Subsequently, Latin Hypercube Sampling (LHS) and importance sampling was applied to account for all uncertain parameters. Various development scenarios were assessed for their impact on injectivity and fracture growth. The influence of the parameters on injectivity and fracture length was analyzed using distance-based Generalized Sensitivity Analysis (dGSA), leading to recommendations for data acquisition strategies to reduce uncertainty and risk. The results show the significance of integrated modeling, including flow, plugging, temperature, and geomechanics, for assessing geothermal injectivity. Under the field case conditions of a European low enthalpy geothermal reservoir, all development options result in induced fracturing. However, due to the stress contrast between the caprock and the reservoir, no vertical growth into the caprock is anticipated. Regarding lateral fracture growth towards faults, the extent of fractures was evaluated under uncertainty. The findings demonstrate the substantial impact of development strategies on fracture half-length. Cooler water and higher injection rates increase the P95 (i.e., 5% of fractures exceed this length) by 35% compared to the base case. Larger fractures pose a higher risk of connecting to faults. Distance-based generalized sensitivity analysis (dGSA) revealed that sensitive parameters vary with the development strategy. These results inform the selection of the most economical operating conditions (high injection rate, low injection temperature) at an acceptable risk of fracture extension. Depending on the operating conditions, the dGSA identifies which parameters need to be determined to reduce risk.