Optimization of the planning and operation of geothermal systems using innovative forecasting tools
M.Sc. Kim Niehage
Deep geothermal heat supply from porous aquifers in the North German Basin involves coupled thermo-hydraulic and hydrogeochemical processes in the subsurface. Although the resource base is promising, the development of new sites is still limited by two major obstacles:
- exploration uncertainty regarding key reservoir properties (e.g., transmissivity, permeability and heterogeneity), which translates into substantial well productivity risk, and
- efficiency losses during operation caused by geochemically driven precipitation (scaling), which can reduce injectivity and productivity and necessitate costly mitigation.
Because target formations occur at several kilometres depth, data availability remains sparse and heterogeneous, and will not improve rapidly. Consequently, planning and decision-making require methods that extract the maximum information from existing data while explicitly quantifying the uncertainties that remain.
The objective of this project is to develop an IT-based, modular concept to support the planning and long-term performance assessment of geothermal doublets for heat supply in North German aquifers, with a specific focus on the impact of geochemical processes on sustained thermal and hydraulic performance. This is achieved through the construction of an uncertainty-aware digital subsurface twin that integrates geological structure information, petrophysical parameters, operational data and hydrogeochemical evidence into a consistent modelling framework, and the development of coordinated digital tools for data integration, model calibration, uncertainty analysis and scenario-based forecasting of scaling-related impacts on injectivity/productivity. All components are assembled into a open-source workflow that can be adapted to varying site conditions. The approach is implemented and demonstrated for the long-operating geothermal site Neustadt-Glewe, leveraging existing operational and geochemical investigations to validate the workflow and to translate site-specific process understanding into robust support for planning and operational decisions.
