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.

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 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.

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.

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.

The European Plate Observing System - Netherlands (EPOS-NL) is the Dutch research infrastructure for solid Earth sciences. EPOS-NL is a cluster of large-scale geophysical facilities for research on georesources and geohazards. It is a partnership between Delft University of Technology (TU Delft), the Royal Netherlands Meteorological Institute (KNMI) and Utrecht University (UU) and is funded by NWO, as part of the national roadmap for large-scale research infrastructure. EPOS-NL facilities include 1) The Earth Simulation Lab at UU, 2) The Groningen gas field seismological network and the ORFEUS Data Centre at KNMI, 3) The deep geothermal (DAP-)well to be installed on the TU Delft campus, and 4) A distributed facility for multi-scale imaging and tomography (MINT) at UU and TU Delft. EPOS-NL aims to further develop the infrastructure for solid Earth scientific research. It also makes cutting-edge research facilities and data available to (inter)national researchers, aiming to address key geo-societal challenges, notably: • Exploration for (renewable) geo-energy resources • Storage of fuels, CO2 and wastewater in the sub-surface, and • Hazards such as induced or natural earthquakes Addressing these challenges requires a multi-physics, multi-scale approach, and open access to state-of-the-art research facilities and data. EPOS-NL contributes to addressing these needs.

Multiphase mass and heat transfer are ubiquitous in the subsurface within manifold applications. The presence of fractures over several scales and complex geometry magnifies the uncertainty of the heat transfer phenomena, which will significantly impact, or even dominate, the dynamic transport process. Capturing the details of fluid and heat transport within the fractured system is beneficial to the subsurface operations. However, accurate modeling methodologies for thermal high-enthalpy multiphase flow within fractured reservoirs are quite limited. In this work, multiphase flow in fractured geothermal reservoirs is numerically investigated. A discrete-fracture model is utilized to describe the fractured system. To characterize the thermal transport process accurately and efficiently, the resolution of discretization is necessarily optimized. A synthetic fracture model is firstly selected to run on different levels of discretization with different initial thermodynamic conditions. A comprehensive analysis is conducted to compare the convergence and computational efficiency of simulations. The numerical scheme is implemented within the Delft Advanced Research Terra Simulator (DARTS), which can provide fast and robust simulation to energy applications in the subsurface. Based on the converged numerical solutions, a thermal Péclet number is defined to characterize the interplay between thermal convection and conduction, which are the two governing mechanisms in geothermal development. Different heat transfer stages are recognized on the Péclet curve in conjunction with production regimes of the synthetic fractured reservoir. A fracture network, sketched and scaled up from a digital map of a realistic outcrop, is then utilized to perform a sensitivity analysis of the key parameters influencing the heat and mass transfer. Thermal propagation and Péclet number are found to be sensitive to flow rate and thermal parameters (e.g., rock heat conductivity and heat capacity). This paper presents a numerical simulation framework for fractured geothermal reservoirs, which provides the necessary procedures for practical investigations regarding geothermal developments with uncertainties.