The German Geothermal Congress 2025
18 - 20 November 2025 | Frankfurt, Germany
Conference Agenda
Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).
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Session Overview |
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WS4: Artificial Intelligence in the Geothermal Sector: Practical Pathways and Real-World Applications
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This focused workshop offers a structured and practical introduction to Artificial Intelligence (AI) in the geothermal sector. It begins with a broad introduction to AI, then progressively zooms in on company integration strategies and real-world geothermal use cases. With expert inputs from industry and academia, attendees will leave with a better understanding of how AI can enhance both daily operations and specialized geothermal tasks, from seismic interpretation to borehole optimization. | ||
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9:00am - 9:20am
ID: 339 Topics: 2.10 Calculation Approaches for Designing Near-Surface Systems, Modeling, Simulation, AI Introduction to AI & Its Evolution, Overview of AI Types: ML, DL, Agentic & Generative AI University of Göttingen -- 9:20am - 9:40am
ID: 340 Topics: 2.10 Calculation Approaches for Designing Near-Surface Systems, Modeling, Simulation, AI How to Integrate AI into a Company Structure University of Göttingen -- 9:40am - 10:00am
ID: 341 Topics: 2.10 Calculation Approaches for Designing Near-Surface Systems, Modeling, Simulation, AI Artificial intelligence and digitalization in the geothermal energy, case studies of applying machine learning, generative AI and digital twin in geothermal energy systems The Netherlands Organisation for Applied Scientific Research (TNO), Netherlands -- 10:00am - 10:20am
ID: 333 Topics: 1.08 Co-Production of Critical Raw Materials Tools for the implementation of raw material extraction from geothermal fluids: the CRM-geothermal AI Lithium estimation tool and Guidelines towards Social Licence to Operate 1Helmholtz Centre for Geosciences (GFZ); 2Inlecom Innovation; 3Green Horizons Environmental Consultants Ltd; 4Levin Sources; 5University of Miskolc The energy and digital transitions require a large amount of raw materials which are considered ‘critical’ in the EU. Interestingly, there is an untapped resource in geothermal fluids, some of which contain significant amounts of Critical Raw Material (CRM). The EU-funded CRM-geothermal project therefore proposes to combine the extraction of raw materials and geothermal heat. To enable a faster market deployment of combined heat and CRM-extraction projects, the CRM-geothermal project has developed a database that gives an overview of the potential for raw materials in geothermal fluids for a large range of CRM across Europe. Based on the data, INLECOM INNOVATION (Greece) developed the CRM AI-based Lithium Prediction Tool to uncover intricate relationships between elemental features and Lithium concentrations in geothermal waters with the adoption of the Decision Tree regression model. The tool development extends to the domain of Explainable AI, with Shapley values shedding light on the intricate decision-making processes of Lithium estimation. Another key requirement for the successful development and operation of combined extraction projects is obtaining and maintaining a social licence to operate (SLO) from local communities and other relevant stakeholders. However, while there is a wealth of academic research on the theoretical basis for SLO, there is little guidance on how to obtain SLO and integrate such activities with wider stakeholder strategies. In the CRM-geothermal project, we have developed practical guidance that project staff can use in planning their day-to-day activities. We present the principles that underpin SLO and a range of potential approaches to obtaining and maintaining SLO. 10:20am - 10:40am
ID: 343 Topics: 2.10 Calculation Approaches for Designing Near-Surface Systems, Modeling, Simulation, AI Open Q&A and Discussion 1University of Göttingen, Germany; 2The Netherlands Organisation for Applied Scientific Research (TNO), Netherlands -- | ||