Fervo Energy, NVIDIA, and the Pacific Northwest National Laboratory (PNNL) have reached an agreement to develop a next-generation digital twin platform for EGS technology, known as EGS-Twin.
The system is designed to deliver real-time insight into subsurface behaviour and operational performance through the integration of high-resolution field data with physics-based modeling and AI-driven forecasting.
PNNL will use Fervo’s industry expertise and field data to train AI models on NVIDIA AI infrastructure. The trained models will be integrated into the NVIDIA Omniverse libraries to help geothermal operators quickly identify and respond to subsurface changes, optimise power generation and strengthen scalability.
PNNL will develop the workflows and data pipelines, leveraging high-performance computing, including the US Department of Energy supercomputing resources, to run large-scale simulations. Using proprietary field data from Fervo’s Nevada and Utah sites, the PNNL team will begin training the digital twin immediately. The platform is scheduled for implementation by 2029.
Fervo’s CTO and Co-Founder, Jack Norbeck, said, “We believe that digital twins will expedite the learning curve for geothermal development as we build and operate our GeoBlock assets. Integrating high-fidelity physics-based models with AI-driven forecasting has the potential to reshape reservoir management, improve heat recovery, and enhance system reliability.”