CORDIS - EU research results

Deep lEarning foRecasting of Induced Seismicity for risK management operations

Project description

Towards safer global geothermal energy exploitation

To combat climate change, it is necessary to transition to clean and sustainable energy production. Enhanced geothermal systems (EGS) have the potential for harnessing the Earth’s heat in many regions. However, EGS technology has been plagued by a significant obstacle that could undermine the operation of such plants; induced seismicity. Recent years have seen destructive earthquakes linked to EGS projects, prompting their closure and igniting societal concerns. With the support of the Marie Skłodowska-Curie Actions programme, the DERISK project aims to revolutionise induced seismicity monitoring. This ground-breaking initiative combines cutting-edge data acquisition technologies with recent deep-learning strategies, exploiting the full potential of big-data analysis for seismicity hazard mitigation at EGS. The goal is to develop an analysis framework able to detect, locate, and characterise induced seismicity.


Climate change mitigation requires a fast and efficient transition to clean and sustainable energy production.Enhanced Geothermal Systems (EGS) play a key Climate change mitigation requires a fast and efficient transition to clean and sustainable energy production. In this context, Enhanced Geothermal Systems (EGS) can play a key role in facing this challenge since, with this technology, clean energy production from the Earth's heat is no longer confined to volcanic or hydrothermal regions. Despite this potential, EGS presents society and economy-related problems that need to be solved to ensure operational safety, continuity, and public acceptance of such industrial projects. Induced seismicity is the major obstacle to the development and social acceptance of EGS projects. In the last years, several damaging earthquakes have been associated with EGS, leading to the definitive closure of the involved projects and raising social concerns against this form of energy production. With DERISK we aim to develop new paradigms for induced seismicity analysis, combining the latest available data acquisition technologies, such as distributed acoustic sensing (DAS), with innovative deep-learning techniques. To characterize induced seismicity with unprecedented resolution and accuracy, we want to develop a next-generation data analysis framework combining deep-learning and waveform-based seismic imaging techniques. Our final goal is to produce deep-learning-based enhanced microseismicity catalogs that will be used to test the performance of new induced seismicity forecasting models exploiting the recent research advances in the field of physics-informed machine learning. The techniques developed within DERISK will be tested and validated with high-quality induced seismicity datasets collected at different EGS sites. If successful, DERISK will open the way to a safer and more widespread development of EGS projects, contributing to the transition to sustainable energy production.


Net EU contribution
€ 172 750,08
56126 Pisa

See on map

Centro (IT) Toscana Pisa
Activity type
Higher or Secondary Education Establishments
Total cost
No data