Decision Making Software for Moderating Induced Seismicity Risk and Optimizing Thermal Energy Revenues in Enhanced Geothermal Systems

Abstract

The development of many novel deep geothermal technologies, such as Enhanced Geothermal Systems (EGS), has decelerated due to induced seismicity. Sophisticated traffic light systems, which assess the efficiency of the implemented stimulation strategy in time for altering it, can assist in successfully developing the EGS technology. Here is presented the modeling approach for a hybrid model that combines numerical calculations with stochastic geo-mechanical modeling and which can be used from such a traffic light. This hybrid model can assist in probabilistically assessing both the induced seismicity hazard and the thermal energy revenues that should be expected from the decided stimulation strategy. The numerical part is performed by HFR-Sim. HFR-Sim is an EGS simulator that numerically solves flow and heat transport problems inside 3D dynamically changing fracture networks. It offers discrete fracture representation and it can simulate a wide range of scenarios that are EGS related. The stochastic computations are performed by a 3D seed model, which has been used by the Swiss Seismological Service (SED) for forecasting induced seismicity hazard. It stochastically samples possible earthquakes (so called seeds) and by considering simple failure criteria, it decides which seeds are triggered and when. Here, the main elements of this hybrid model and the coupling between them are discused. The model is tested on a realistic scenario and is used for studying the effect that different injection strategies have on induced seismicity hazard and on the commerciality of the project.