The campus of the Karlsruhe Institute of Technology (KIT) contains several waste heat streams. In an effort to reduce greenhouse gas emissions by optimizing thermal power consumption on the campus, researchers at the KIT are proposing a ‘DeepStor’ project, which will sequester waste heat from these streams in an underground reservoir during the summer months, when the heat is not required. The stored heat will then be reproduced in the winter, when the campus’s thermal power demand is much higher. This paper contains a preliminary geochemical risk assessment for the operation of this subsurface, seasonal geothermal energy storage system. We used equilibrium thermodynamics to determine the potential phases and extent of mineral scale formation in the plant’s surface infrastructure, and to identify possible precipitation, dissolution, and ion exchange reactions that may lead to formation damage in the reservoir. The reservoir in question is the Meletta Beds of the Upper Rhein Graben’s Froidefontaine Formation. We modeled scale- and formation damage-causing reactions during six months of injecting 140 °C fluid into the reservoir during the summer thermal storage season and six months of injecting 80 °C fluid during the winter thermal consumption season. Overall, we ran the models for 5 years. Anhydrite and calcite are expected mineral scales during the thermal storage season (summer). Quartz is the predicted scale-forming mineral during the thermal consumption period (winter). Within ~20 m of the wellbores, magnesium and iron are leached from biotite; calcium and magnesium are leached from dolomite; and sodium, aluminum, and silica are leached from albite. These reactions lead to a net increase in both porosity and permeability in the wellbore adjacent region. At a distance of ~20–75 m from the wellbores, the leached ions recombine with the reservoir rocks to form a variety of clays, i.e., saponite, minnesotaite, and daphnite. These alteration products lead to a net loss in porosity and permeability in this zone. After each thermal storage and production cycle, the reservoir shows a net retention of heat, suggesting that the operation of the proposed DeepStor project could successfully store heat, if the geochemical risks described in this paper can managed.

The essentially non‐magmatic continental rift system of the Upper Rhine Graben (URG) is segmented and characterized by intra‐rift sub‐basins that exhibit NE to NW trends suggesting complex basin development during rifting. Structural modeling and analyses of an about 40 km² 3D seismic survey from the northern part of the central URG segment show deep rooted NNE‐striking faults controlling early, syn‐rift 1, extensional basin evolution from about 47 Ma to 27 Ma. The change in stress field at about 27 Ma and subsequent reactivation of these deep rooted basement faults resulted in a new set of shallow rooted en‐echelon faults. On a larger scale this change in stress field was accompanied by a shift of regional depocenters. The shallow rooted en‐echelon faults nucleated in 32–28 Ma old strata and are linked by conjugated relay ramps that control the development of latest Oligocene to early Miocene syn‐rift 2 basins trending N to NNW. Although we only studied a small part of the >11,000 km² large URG, we hypothesize that this type of intra‐rift basin development in the hanging wall of major deep rooted normal faults is more widespread in the graben and may represent a general style for the development of other late Oligocene‐early Miocene intra‐rift basins, such as for example, the distinct Heidelberg Basin. We suggest increasing mechanical coupling between the European lower plate and Adriatic upper plate at c. 30 Ma to 28 Ma as a possible cause for the Oligocene stress field change.

Evaluating uncertainties of geological features on fluid temperature and pressure changes in a reservoir plays a crucial role in the safe and sustainable operation of high-temperature aquifer thermal energy storage (HT-ATES). This study introduces a new automated surface fitting function in the Python API (application programming interface) of Gmsh (v4.11) to simulate the impacts of structural barriers and variations of the reservoir geometries on thermohydraulic behaviour in heat storage applications. These structural features cannot always be detected by geophysical exploration but can be present due to geological complexities. A Python workflow is developed to implement an automated mesh generation routine for various geological scenarios. This way, complex geological models and their inherent uncertainties are transferred into reservoir simulations. The developed meshing workflow is applied to two case studies: (1) Greater Geneva Basin with the Upper Jurassic (“Malm”) limestone reservoir and (2) the 5° eastward-tilted DeepStor sandstone reservoir in the Upper Rhine Graben with a uniform thickness of 10 m. In the Greater Geneva Basin example, the top and bottom surfaces of the reservoir are randomly varied by ± 10 and ± 15 m, generating a total variation of up to 25 % from the initially assumed 100 m reservoir thickness. The injected heat plume in this limestone reservoir is independent of the reservoir geometry variation, indicating the limited propagation of the induced thermal signal. In the DeepStor reservoir, a vertical sub-seismic fault juxtaposing the permeable sandstone layers against low permeable clay-marl units is added to the base case model. The fault is located in distances varying from 4 to 118 m to the well to quantify the possible thermohydraulic response within the model. The variation in the distance between the fault and the well resulted in an insignificant change in the thermal recovery (∼ 1.5 %) but up to a ∼ 10.0 % pressure increase for the (shortest) distance of 4 m from the injection well. Modelling the pressure and temperature distribution in the 5° tilted reservoir, with a well placed in the centre of the model, reveals that heat tends to accumulate in the updip direction, while pressure increases in the downdip direction.

Evaluating uncertainties of geological features on temperature and pressure changes in reservoir’s fluids are crucial for a safe and sustainable operation of the High-Temperature Aquifer Thermal Energy Storage (HT-ATES). This study uses a new automated surface fitting function in Python API of GMSH (v. 4.11) to model the impact of arbitrary structural barriers and variations of roof and floor geometries on temperature and pressure in heat storage application. A workflow is developed in Python to implement an automated mesh generation routine for varying geological scenarios that cannot be predicted by surface-based exploration methods. This way, the geologic models and their underlying uncertainties are transferred into reservoir simulations. We applied our modelling approach on two case studies: 1) Greater Geneva Basin with the Upper Jurassic (“Malm”) limestone reservoir of 100 m thickness and 2) the DeepStor project in the Upper Rhine Graben with an Oligocene sandstone reservoir of 10 m thickness. In the Greater Geneva Basin showcase, the upper and lower surfaces of the reservoir are shifted ± 8 and ± 10 m, respectively to perturb topology of the thick reservoir. Independence of the heat plume from reservoir's topology indicates the limited propagation of the induced thermal regime in thick reservoirs and redundancy of the advanced exploration campaigns like 3D seismic. In DeepStor, an arbitrary sub-seismic fault juxtaposing the permeable sandstone layers against low-permeable clay-marl units is introduced to the base case model. The arbitrary fault is located in distances varying 4 m to 118 m from the borehole and resulted in a ~10 % difference in the pressure field of the cases. Modelling the pressure and temperature in the tilted reservoir reveals that heat tends to accumulate updip while pressure values are higher in the downdip side.