THC-Prognos - Hydrochemical characterisation for predictive modelling of sustainable reservoir management
The project focuses on the following areas:
1. Creation of a hydrogeochemical database of the known reservoir thermal waters in Germany: The aim is the area-wide recording and provision of validated hydrochemical data of thermal, mineral and deep groundwater as well as thermal brines. The focus is on the three most important geothermal regions in Germany: the North German Basin, the Upper Rhine Graben and the Molasse Basin. The data are compiled from various sources and published under a free license on TUdatalib of the TU Darmstadt, a long-term data storage facility.
2. Development of a thermal-hydraulic-chemical (THC) modeling tool and establishment of a guideline for THC modeling: The aim is a coordinated, reliable method for evaluating hydrogeochemical interactions, validation, and the provision of reference data for calibrating our own model approaches. These tools will be developed from the research environment status into the practice of the consulting engineering offices and project planners.
3. Prognostic thermal-hydraulic-chemical modeling: The aim is to quantitatively forecast the hydrochemical interactions in the affected area (e.g. reservoir, vicinity of the borehole) of medium-deep heat storage and deep hydrothermal direct heat generation at selected project locations.
4. Extension of the geothermal information system GeotIS: The georeferenced findings on hydrochemistry of reservoir fluids will be made publicly accessible over time in relation to the formation and location. For this purpose, GeotIS is to be supplemented and provided with new functions for the interactive display of hydrochemical reservoir parameters.
Aims of the subproject are: (i) Holistic investigation of THC interactions in the reservoir and in the area near the borehole using numerical simulation. (ii) Further development of a general-purpose modeling tool that can be used to explain and predict hydrogeochemical processes in the reservoir and at a borehole or doublets (geothermal energy, heat storage, but also drinking water).
In holistic THC modeling, proof-of-concept studies from the academic sector must be put into practice for both the conceptual model and the specific implementation in order to enable application by others. On the conceptual side, the model structure must be designed to be automated and transferable, a modeling approach to represent electrochemical processes must be implemented, and the quality of the model should be quantifiable. The following development steps are necessary for this:
• Technical implementation THC reservoir simulator
• Electrochemistry tool development
• THC modeling example location
• Machine learning
- Technische Universität Darmstadt 64287 Darmstadt Deutschland
- Technische Universität Berlin 10623 Berlin Deutschland
- Helmholtz-Zentrum Potsdam Deutsches GeoForschungsZentrum 14473 Potsdam Deutschland
- Leibniz Institut für Angewandte Geophysik 30655 Hannover Deutschland
- Hydroisotop GmbH 85301 Schweitenkirchen Deutschland
- Büro für Geohydrologie und Umweltinformationssysteme 75392 Deckenpfronn Deutschland
