Der Geothermiekongress 2025
18. - 20. November 2025 | Frankfurt
Veranstaltungsprogramm
Eine Übersicht aller Sessions/Sitzungen dieser Veranstaltung.
Bitte wählen Sie einen Ort oder ein Datum aus, um nur die betreffenden Sitzungen anzuzeigen. Wählen Sie eine Sitzung aus, um zur Detailanzeige zu gelangen.
|
Sitzungsübersicht |
| Sitzung | ||
WS4: Artificial Intelligence in the Geothermal Sector: Practical Pathways and Real-World Applications
| ||
| Zusammenfassung der Sitzung | ||
|
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. | ||
    | ||
9:00 - 9:20
ID: 339 Themen: 2.10 Berechnungsansätze zur Auslegung oberflächennaher Systeme, Modellierung, Simulation, KI Introduction to AI & Its Evolution, Overview of AI Types: ML, DL, Agentic & Generative AI University of Göttingen -- 9:20 - 9:40
ID: 340 Themen: 2.10 Berechnungsansätze zur Auslegung oberflächennaher Systeme, Modellierung, Simulation, KI How to Integrate AI into a Company Structure University of Göttingen -- 9:40 - 10:00
ID: 341 Themen: 2.10 Berechnungsansätze zur Auslegung oberflächennaher Systeme, Modellierung, Simulation, KI 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 -- 10:00 - 10:20
ID: 333 Themen: 1.08 Koproduktion von kritischen Rohstoffen 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. 10:20 - 10:40
ID: 343 Themen: 2.10 Berechnungsansätze zur Auslegung oberflächennaher Systeme, Modellierung, Simulation, KI Open Q&A and Discussion 1University of Göttingen, Germany; 2The Netherlands Organisation for Applied Scientific Research (TNO), Netherlands -- | ||