Obtaining information on scientific topics and access to websites with multidimensional data is a crucial part of any geothermal project development. Using the Internet to publish information according to the FAIR principles (Findability, Accessibility, Interoperability and Reusability) on topics that are not yet well known to stakeholders could improve not only general knowledge but also public acceptance for increased use of geothermal in the future. This research lists 90 geothermal websites from eight countries: nine in Austria, 13 in Croatia, eight in Hungary, 17 in Italy, seven in Germany, 16 in Iceland, 13 in the Netherlands and seven in Slovenia, and classifies them based on findability and content criteria. It is an issue that only 41 % of these national-relevant websites are easy to find using a browser and keywords, while for the rest an expert advice is needed. The user-impression by searching these websites was checked, for example, on language, graphical presentation, type of information, content, and references. It was expected that Iceland, Italy and Germany, as the countries with the largest geothermal utilization, have the most information available. Iceland has the most findable and quality websites, while Italy has the most listed websites but only a few are easy to find. Germany is not ranked as high as expected. The Netherlands and Croatia do not stand out but have few very good websites. Hungary and Austria show similar results while Slovenia needs most improvements.

The energy transition is inevitable since approximately two-thirds of the current global GHG emissions are related to energy production. Subsurface can provide a great opportunity for innovative low-carbon energy solutions such as geothermal energy production, hydrogen storage, carbon capture, and sequestration, etc. Well and borehole operations play an important role in all these applications. In order to operate wells intelligently, there must be a robust simulation technology that captures physics and the expected production scenario. In this study, we design a numerical framework for predictive simulation and monitoring of injection and production wells based on the general multi-segment well model. In our simulation model, wells are segmented into connected control volumes similar to the finite-volume discretization of the reservoir. Total velocity serves as an additional nonlinear unknown and it is constrained by the momentum equation. Moreover, transforming nonlinear governing equations for both reservoir and well into linearized equations benefits from operator-based linearization (OBL) techniques and reduce further the computational cost of simulation. This framework was tested for several complex physical kernels including thermal compositional multiphase reactive flow and transport. The proposed model was validated using a comparison with analytic and numerical results.

Simulation of CO₂ utilization and storage (CCUS) in subsurface reservoirs with complex heterogeneous structures requires a model that captures multiphase compositional flow and transport. Accurate simulation of these processes necessitates the use of stable numerical methods that are based on an implicit treatment of the flux term in the conservation equation. Due to the complicated thermodynamic phase behavior, including the appearance and disappearance of multiple phases, the discrete approximation of the governing equations is highly nonlinear. Consequently, robust and efficient techniques are needed to solve the resulting nonlinear system of algebraic equations. In this study, we present a powerful nonlinear solver based on a generalization of the trust-region technique for compositional multiphase flows. The approach is designed to embed a newly introduced Operator-Based Linearization technique and is grounded on the analysis of multi-dimensional tables related to parameterized convection operators. We split the parameter space of the nonlinear problem into a set of trust regions where the convection operators preserve the second-order behavior (i.e., they remain positive or negative definite). We approximate these trust regions in the solution process by detecting the boundary of convex regions via analysis of the directional derivative. This analysis is performed adaptively while tracking the nonlinear update trajectory in the parameter space. The proposed nonlinear solver locally constrains the update of the overall compositions across the boundaries of convex regions. We tested the performance of the proposed nonlinear solver for various scenarios. In many cases, our approach yields an improved behavior of the nonlinear solution in comparison to state-of-the-art solvers.

The efficient operation and management of a geothermal project can be largely affected by geological, physical, operational and economic uncertainties. Systematic uncertainty quantification (UQ) involving these parameters helps to determine the probability of the focused outputs, e.g., energy production, Net Present Value (NPV), etc. However, how to efficiently assess the specific impacts of different uncertain parameters on the outputs of a geothermal project is still not clear. In this study, we performed a comprehensive UQ to a low-enthalpy geothermal reservoir using the GPU implementation of the Delft Advanced Research Terra Simulator (DARTS) framework with stochastic Monte Carlo samplings of uncertain parameters. With processing the simulation results, large uncertainties have been found in the production temperature, pressure drop, produced energy and NPV. It is also clear from the analysis that salinity influences the producing energy and NPV via changing the amount of energy carried in the fluid. Our work shows that the uncertainty in NPV is much larger than that in produced energy, as more uncertain factors were encompassed in NPV evaluation. An attempt to substitute original 3D models with upscaled 2D models in UQ demonstrates significant differences in the stochastic response of these two approaches in representation of realistic heterogeneity. The GPU version of DARTS significantly improved the simulation performance, which guarantees the full set (10,000 times) UQ with a large model (circa 3.2 million cells) finished within a day. With this study, the importance of UQ to geothermal field development is comprehensively addressed. This work provides a framework for assessing the impacts of uncertain parameters on the concerning system output of a geothermal project and will facilitate analyses with similar procedures.

Mesozoic sandstone aquifers in the North German Basin offer significant potential to provide green and sustainable geothermal heat as well as large‐scale storage of heat or chill. The determination of geothermal and subsurface heat storage potentials is still afflicted with obstacles due to sparse and partly uncertain subsurface data. Relevant data include the structural and depositional architecture of the underground and the detailed petrophysical properties of the constituting rocks; both are required for a detailed physics‐based integrated modeling and a potential assessment of the subsurface. For the present study, we combine recently published basin-wide structural interpretations of depth horizons of the main stratigraphic formations, with temperature data from geological and geostatistical 3D models (i.e., CEBS, GeotIS). Based on available reservoir sandstone facies data, additional well‐log‐based reservoir lithology identification, and by providing technical boundary conditions, we calculated the geothermal heat in place and the heat storage potential for virtual well doublet systems in Mesozoic reservoirs. This analysis reveals a large potential for both geothermal heating and aquifer thermal energy storage in geologically favorable regions, and in many areas with a high population density or a high heat demand. Given the uncertainties in the input data, the applied methods and the combination of data from different sources are most powerful in identifying promising regions for economically feasible subsurface utilization, and will help decrease exploration risks when combined with detailed geological site analysis beforehand.

The hydraulic performance and mechanical stability of open fractures are crucial for several subsurface applications including fractured geothermal reservoirs or nuclear waste repositories. Their hydraulic and mechanical properties (fluid flow and fracture stiffness) are both strongly dependent on the fracture geometry. Any change in effective stress impacts aperture and thus the ability of fractures to promote flow. Here, we carried out flow experiments with shear displaced tensile fractures in pre-loaded, low-permeability sandstones with two different cyclic loading scenarios with up to 60 MPa hydrostatic confining pressure. During “constant cyclic loading” (CCL) experiments, the fracture was repeatedly loaded to the same peak stress (up to 60 MPa). During “progressive cyclic loading” (PCL) experiments, the confining pressure was progressively increased in each cycle (up to 15, 30, 45, and 60 MPa). The matrix and fracture deformation was monitored using axial and circumferential LVDT extensometers to obtain the fracture stiffness. The fracture geometry before and after the experiment was compared by calculating the aperture distribution from 3D surface scans. Initial loading with confining pressure of the fracture leads to a linear fracture specific stiffness evolution. For any subsequent stress cycles fracture stiffness shifts to a nonlinear behavior. The transition is shown to be related to a stress memory effect, similar to the “Kaiser Effect” for acoustic emissions. PCL of fractures possibly leads to less permeability reduction compared to continuous cyclic loading.

A realistic deep low-enthalpy geothermal reservoir based on real data with high detail and complicated sedimentary structure is utilized to perform sensitivity analyses of the geological features influencing reservoir properties. We perform simulations using the Delft Advanced Research Terra Simulator (DARTS). Compelling numerical performance of DARTS makes it suitable for handling a large ensemble of models including efficient sensitivity and uncertainty analyses. The major finding is that shale facies, generally ignored in hydrocarbon reservoir simulations, can significantly extend the predictive lifetime of geothermal reservoirs exploited by deep well doublets. It is important to accurately account for the shale facies in the simulation, though with an additional computational overhead. The overburden layers can improve doublet performance, but the impact depends on reservoir heterogeneity. In addition, heterogeneity will also divert the flow path with even a minor shift in the well placement. The discharge rate, an essential parameter of geothermal operation strategy, inversely corresponds to the doublet lifetime but positively correlates with the energy production for studied parameter ranges. Low sensitivity of doublet lifetime to vertical-horizontal permeability ratio and permeability-porosity correlation is observed. All these systematic findings for a realistic geothermal field with characterization at unprecedented level of detail can help to provide a general guideline for forward simulation and farther improve the profitability of geothermal energy production in realistic deep geothermal reservoirs through computer-assisted modeling and optimization.

Using an innovative experimental set-up (Punch-Through Shear test), we initiated a shear zone (microfault) in Flechtingen sandstone and Odenwald granite under in situ reservoir conditions while monitoring permeability and fracture dilation evolution. The shear zone, which has a cylindrical geometry, is produced by a self-designed piston assembly that punches down the inner part of the sample. Permeability and fracture dilation were measured for the entire duration of the experiment. After the shear zone generation, the imposed shear displacement was increased to 1.2 mm and pore pressure changes of ± 5 or ± 10 MPa were applied cyclically to simulate injection and production scenarios. Thin sections and image analysis tools were used to identify microstructural features of the shear zone. The geometry of the shear zone is shown to follow a self-affine scaling invariance, similar to the fracture surface roughness. The permeability evolution related to the onset of the fracture zone is different for both rocks: almost no enhancement for the Flechtingen sandstone and an increase of more than 2 orders of magnitude for the Odenwald granite. Further shear displacement resulted in a slight increase in permeability. A fault compaction is observed after shear relaxation which is associated to a permeability decrease by a factor more than 3. Permeability changes during pressure cycling are reversible when varying the effective pressure. The difference in permeability enhancement between the sandstone and the granite is related to the larger width of the shear zones.