The use of deep geothermal energy is an important building block in the planned transformation of energy systems. However, the development of new sources, particularly for the pore aquifers in the North German Basin, has not progressed as far as necessary to make a substantial contribution. Decisive obstacles here are, on the one hand, the exploration risk, which essentially results from uncertainties regarding the subsurface properties, as well as larger cost factors that are difficult to calculate during operation, such as scaling effects, which reduce efficiency and may require expensive countermeasures. The lack of information on the geological properties in the target horizon makes it difficult to plan and make the estimates required for decision-making. Due to the depth of the formations, the generally weak information and data situation will not change quickly. In addition to the further development of exploration methods, methods are therefore needed that generate the best possible information about the subsurface and the processes from the available data and take into account the uncertainties of the information obtained due to the limited data available.
This is to be achieved here by developing AI methods for accessing and linking existing data sources. The aim of the project is to develop and apply an IT-based concept for the planning of geothermal duplicate systems in northern German aquifers and to predict the influence of geochemical processes on the long-term efficiency of these systems. For this purpose, a digital twin of the subsurface with an assessment of uncertainties is being developed and various coordinated digital tools are being created and combined in an open-source workflow that can be flexibly modified. This is being developed as an example for the Neustadt-Glewe geothermal power plant, which has been in operation for many years; in particular the geochemical processes that have been investigated for the plant for a long time are being taken into account. The results of the project are intended to support planning and decision-making and make existing process and site knowledge available for more efficient operation of deep geothermal energy.
The presentation will give an overview of the project and present initial work.
Led by:
Insa Neuweiler, Mattheo Broggi, Monika Sester, André Stechern, Martin Thullner
