AI-based monitoring of geothermal Seismicity – AIS

Production, distribution and storage of renewable energies (wind energy, geothermal energy, power lines, reservoirs, etc.) are the central challenges for society and politics to provide secure and sustainable energy supply without fossil fuels. Enormous sums have to be invested for the switch to renewable energies in the coming decades. For geothermal, the IRENA roadmap for energy transition calls for an increase of geothermal heat for buildings from 1% to 3% by 2050. However, one of the major holdbacks of exploiting deep geothermal energy and more generally storage of energy in the subsurface is induced seismicity leading to poor acceptance in the population and significant financial risk for the developing companies as an unexpected earthquake may halt the geothermal project itself (e.g. 2006 Basel, Switzerland, 2017 Pohang, South Korea, and 2019 Vendenheim, France). In this project, we aim to develop an integrated earthquake forecasting method, which will help the operators to manage induced seismicity both during stimulation and exploitation. We will integrate easy to install and maintain seismic monitoring equipment with recent advances in AI based earthquake detection and location tools to be able to apply AI based seismic forecasting tools, which will provide much better insight into the occurrence of seismicity and offers insights to manage seismicity. We will apply our methodology to a site in exploitation (Rittershoffen) in the Upper Rhine graben, a promising place for further geothermal deployment in both France and Germany. The system developed can also be used to better monitor and manage energy storage in the subsurface which has also been linked to induced seismicity.