GEOTWINS

Uncertainty-aware digital twins and adaptive seismic risk management for deep geothermal energy

Deep geothermal energy offers a renewable source of heat and electricity, but its wider deployment faces challenges associated with induced seismicity, uncertain reservoir performance, and economic viability. In enhanced geothermal systems (EGS), hydraulic stimulation improves the permeability of deep rock formations to enable heat extraction. However, the resulting seismicity must be carefully managed to limit its consequences for surrounding communities and infrastructure. Reliable operational decisions therefore require not only detailed simulations of reservoir behavior, but also a systematic treatment of uncertainty and a connection between monitoring data, predictive models, and seismic risk assessment.

GEOTWINS (Digital Twin Components for Deep Geothermal Energy Power and Heat Generation) aims to develop a modular digital twin framework for safer and more efficient geothermal energy production. The project integrates seismic monitoring and imaging, physics-based reservoir modeling, hazard and loss assessment, and visualization and decision-support tools. Its digital twin components are designed to represent geothermal systems across multiple spatial scales and project stages, supporting the interpretation of reservoir evolution and the evaluation of operational choices. The resulting workflows will be validated at selected laboratory and field demonstration sites, connecting methodological developments with practical geothermal applications.

The University of Trento (UNITN) contributes particularly to uncertainty quantification and induced seismic risk management. Within WP2, Task 2.5, the research addresses efficient and robust forward and inverse uncertainty quantification for geothermal reservoir models. Forward uncertainty quantification examines how uncertain model inputs affect predicted system behavior, while inverse uncertainty quantification uses observations to constrain uncertain model parameters. UNITN leads the associated non-intrusive uncertainty quantification framework (D2.5), which is intended to assess the impact of uncertainties within simulation models. This work provides a basis for interpreting model predictions together with their uncertainty, rather than relying exclusively on a single deterministic representation of the reservoir.

UNITN also co-leads WP3 (Hazards, Vulnerability, and Risk Analysis) with GFZ Potsdam. Prof. Marco Broccardo serves as UNITN’s work-package lead. The broader objective is to support seismic risk management throughout the project life, rather than limiting mitigation to stimulation phases. Together, uncertainty-aware reservoir predictions and adaptive risk assessment are intended to inform operational choices that account for both geothermal performance and seismic safety.

GEOTWINS framework integrating seismic monitoring, reservoir modeling, uncertainty quantification, seismic risk assessment, and decision support
Figure 1. GEOTWINS modular digital twin framework, connecting seismic monitoring, reservoir modeling, uncertainty quantification, risk assessment, and decision support.

This project is funded through the Clean Energy Transition Partnership (CETPartnership) under its 2023 joint call, with co-funding from the European Union and participating national funding agencies. UNITN’s participation is supported by the Italian Ministry of Enterprises and Made in Italy (MIMIT).