DERISK · Deep lEarning foRecasting of Induced Seismicity for risK management operations

Deep lEarning foRecasting of Induced Seismicity for risK management operations

Europe has set an ambitious goal towards achieving climate neutrality, aiming to reduce to zero the net greenhouse gas emissions by 2050 under the European Green Deal. This transition to a zero-carbon economy requires not only a transformation of energy systems but also the large-scale deployment of reliable, sustainable, and low-carbon technologies. While solar and wind power dominate the current renewable landscape, they remain dependent on weather variability and extensive storage solutions. In contrast, geothermal energy offers a continuous, base-load renewable resource, harnessing the Earth’s internal heat to provide both electricity and heating. Its vast potential across many worldwide regions makes it an attractive solution in the transition to a resilient, low-carbon energy mix. However, geothermal energy is not without risks. The process of deep drilling and fluid injection needed to exploit geothermal reservoirs can alter subsurface stress conditions and, in some cases, trigger induced seismicity. Unlike natural earthquakes, which are caused by tectonic forces, induced seismic events are directly linked to human activity and can raise concerns in densely populated or seismically sensitive areas, highlighting the seismic risk associated to this extraction. While most induced seismic events are small and not hazardous, there remains the possibility of stronger tremors that may pose safety risks and undermine public acceptance. Balancing the immense benefits of geothermal as a stable, carbon-free energy source with the careful management of seismic hazards will be central to its role in Europe’s path to a climate-neutral future. The DERISK project aims at leveraging novel Deep-Learning (DL) techniques to tackle the challenges of monitoring seismic activity at geothermal sites (both enhanced and natural) and reduce the risks associated with operational tasks (i.e., injection and extraction of fluids). In particular, it seeks to develop next-generation software and methods for creating enhanced microseismicity catalogs (EMC) and forecasting the maximum magnitude expected in a short-time window. The impact of this project could lead to new strategies to be embedded to the well-known and widely used decision-making scheme (i.e., Traffic Light System, TLS) for safer energy extraction, thereby promoting and helping the spread of EGS deployment in Europe.

Data: CORDIS, © European Union