The EGU General Assembly will take place from April 4 to 9, 2027, in Vienna and online. Every year, around 20,000 researchers from across the Earth, planetary and space sciences come together at the meeting to present new research, exchange ideas and build collaborations.
The new session “AI and Scientific Machine Learning for Subsurface Energy and Environmental Systems” focuses on how artificial intelligence and Scientific Machine Learning (SciML) can support the modelling, prediction, monitoring and management of complex subsurface systems. Applications range from geothermal energy and geological carbon storage to underground hydrogen storage and groundwater systems. These systems are often heterogeneous, multiscale and subject to substantial uncertainty – making them particularly challenging for conventional modelling approaches.
The session invites contributions on topics including physics-informed machine learning, neural operators, reduced-order and surrogate modelling, multimodal data integration, uncertainty quantification and digital twins as well as generative models, explainable and trustworthy AI, large language models and AI agents.
The aim is to bring together researchers from geoscience, hydrology, subsurface energy, computational science and AI to discuss emerging methods, practical applications, current limitations and future research directions. Many of these questions are also closely connected to current SimTech research, where machine learning, uncertainty quantification, model reduction and the integration of data and physics play a central role in advancing simulation methods.
Wolfgang Nowak, spokesperson of SimTech and professor at the Institute for Modelling Hydraulic and Environmental Systems (IWS), serves as co-convener alongside Nanzhe Wang (Heriot-Watt University), Valentina Ciriello (University of Bologna), Ahmed ElSheikh (Heriot-Watt University) and Denis Voskov (Delft University of Technology).
AI and Scientific Machine Learning for Subsurface Energy and Environmental Systems
Call for Abstracts
Researchers working at the interface of AI, Scientific Machine Learning and subsurface energy or environmental systems are invited to submit their work. The deadline for abstract submission is January 12, 2027, at 13:00 CET. The EGU27 Call for Abstracts has been open since October 28, 2026.