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 Netherlands aims to be CO2 neutral by 2050, aligning with the Paris Agreement. To achieve this, it is crucial to increase the contribution of geothermal energy to renewable energy sources, necessitating large-scale exploitation to speed up the energy transition. Only small-scale (1–2 km) geothermal field developments exist in the Netherlands primarily for heating. Expanding to extensive geothermal fields (10 km length) requires a strategic approach to well placement and consideration of the economic constraints associated with geothermal projects. The heterogeneity of the subsurface is a critical factor in developing large-scale geothermal reservoirs. This study introduces an innovative approach to optimising well placement based on geological trends, using a well-density function as a proof of concept. Implementing and optimising flexible well patterns for large-scale geothermal developments significantly enhances profitability compared to conventional oil and gas industry methods. Optimised flexible well patterns favour a long-term utilisation of energy recovered, minimise pressure extrema in the reservoir, and improve sweep efficiency. However, their application depends on reservoir operational decisions. The optimisation process ensures economic viability, even with lower heat prices. Broadly, this methodology could be key to scaling up geothermal developments to meet the objectives of the Paris Agreement.

Injectivity decline during brine reinjection poses a significant challenge in the geothermal industry, with reported cases of substantial injectivity reduction and in severe cases, complete well shutdown. Among the reasons behind these issues, chemical processes play a key role due to potential changes in the fluid properties throughout the operation cycle. When reinjected, the fluid with altered chemical composition mixes with in situ fluids, potentially triggering mineral precipitation, which can obstruct flow and reduce injectivity. To better characterize the mechanisms behind the mixing-induced mineral precipitation processes, we performed a series of core-flooding experiments combined with high-resolution imaging techniques. Our study focuses on the direct visualization of barite precipitation fronts in Berea sandstone and characterizes their spatial and temporal evolution under varying flow conditions. Pressure response and time-resolved 2D scanning were analyzed to capture real-time changes in the system, whereas post-experiment micro-CT scanning, electron microprobe analysis, and mass spectrometry were employed to examine the morphology and distribution of the mineral deposits. Our results highlight the critical role of flow velocities on the kinetics of mixing-induced precipitation and demonstrate how mineral accumulation may significantly reduce permeability. These findings provide valuable insights into the dynamics of mineral precipitation in porous media, highlighting the impact of flow conditions on formation damage in geothermal systems.

Nearly half of the Netherlands’ natural gas consump tion is allocated to heating, with direct -use geothermal heating being one of the available low-carbon energy solutions. A geothermal well doublet, designed with the two primary aims of research and commercial heat supply, is currently being installed on the campus of Delft University of Technology. The project is a key national research infrastructure and is being incorporated into the European sustainable and distributed infrastructure (EPOS: European Plate Observing System, https://www.epos-eu.org/), such that accessibility and data availability will be as wide as possible. All observations will be included in a digital-twin framework, which will allow us to make better decisions in future geothermal projects. The project includes a comprehens ive research program, involving the installation of a wide range of instruments alongside an extensive logging and coring program and monitoring network. The doublet has been cored, with substantial continuous samples from the heterogeneous reservoir, alongside a large suite of well logs in both the reservoir and overlying geological units. Such investigation is rarely undertaken in geothermal projects. A fiber-optic cable will monitor the producer well all the way down to the reservoir section, at approximately 2300m depth, in the Lower Cretaceous Delft Sandstone that is used as a geothermal reservoir in a series of existing and planned doublets in the West Netherlands Basin. A local seismic monitoring network has been installed in the surrounding area with the aim of monitoring very low-magnitude natural or induced seismicity. A vertical observation well with electromagnetic sensors will be drilled in the near future between the injector and producer to monitor cold-front propagation. This paper presents the initial modeling for the project and steps towards the production of a digital twin. Two modeling examples in the paper will emp hasize current operational challenges relevant to the project.

A geothermal doublet has been installed in a sedimentary reservoir for direct-use heating on the TU Delft campus, targeted to supply around 25 MW of thermal energy at peak conditions. This contribution presents the implementation and initial data collection from the doublet, including an initial evaluation of the logging and coring campaign. Nearly half of Netherlands natural gas consumption is allocated to heating, and the on-campus CO2 emissions from heating exceed 50%. The doublet has been designed with two primary aims of research and commercial heat supply, with the wells being completed in December 2023. The project will be operated by a commercial entity, and built into a larger thermal energy system including a high temperature underground storage system, with the first energy production planned in 2025. The research questions relate to field-scale geothermal operations, e.g. how reliable is the long-term energy production?, how do materials perform in the long-term? and how can geothermal projects be best monitored? The research programme involves the installation of a wide range of instruments alongside an extensive logging and coring program and monitoring network. The doublet has been cored, with substantial continuous samples from the heterogenous reservoir, alongside a large suite of open hole well logs in the reservoir and through casing logs in overlying geological units. A fiber-optic cable will monitor distributed pressure throughout the producer reservoir section, at approximately 2300m depth, which will be installed during commissioning. A local seismic monitoring network has been installed in the surrounding area with the aim of monitoring very low-magnitude natural or induced seismicity. The project is a key national research infrastructure and is being incorporated into the European EPOS (European Plate Observing System, https://www.epos-eu.org/), such that accessibility and data availability will be as wide as possible. All observations will be included in a digital-twin framework that will allow to make better decisions in future geothermal projects.

A geothermal well doublet, designed with two primary aims; one of research and the second of commercial thermal energy supply, is currently being installed on the campus of Delft University of Technology, with the wells being drilled in the second half of 2023. The project includes a comprehensive research program, involving the installation of a wide range of instruments alongside an extensive logging and coring program and monitoring network. The doublet has been cored, with continuous samples from the heterogenous reservoir being complimented with more distributed side-wall cores, alongside a large suite of open-hole well logs in the reservoir section of both wells. Such investigation is rarely undertaken in geothermal projects. A fiber optic cable will monitor the production well, and will be installed all-the-way down to the reservoir section when the well completion is installed, at approximately 2300m depth. The reservoir is the fluvial Lower Cretaceous Delft Sandstone that is used as a geothermal reservoir in a series of existing and planned doublets in the West Netherlands Basin. A local seismic monitoring network has been installed in the surrounding area with the aim of monitoring very low-magnitude natural or induced seismicity. A vertical observation well with electromagnetic sensors will be drilled in a few y ears’ time between the injector and producer to monitor cold-front propagation. The total project is targeted to supply around 25 MW of thermal energy at peak conditions, next to this project a thermal energy storage system is planned to provide a seasonal buffer. The project is a key national research infrastructure and is being incorporated into the European infrastructure EPOS (European Plate Observing System, https://www.epos-eu.org/), such that accessibility and data availability will be as wide as possible. All observations will be included in a digital-twin framework that will allow better decisions to be made in future geothermal projects. This paper presents the implementation and initial data collection from the project, including an initial evaluation of the logging and coring campaigns.

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.

The primary goal of this study is to build new and integrated conceptual models for a high temperature field in Indonesia. Providing new data, combining models, visualizing them in 3D is significant to refine previous 2D traditional models, which are limited for reservoir characterization and wellplacement. During field utilization, constantly updating conceptual models helps to verify the pre-existing models and to renew spatial description of the geothermal system. The new geology models aim to refine the description of subsurface units, the fault models help to renew outdated knowledge on structures, temperature and hydrothermal models aim to eludicate new spatial temperature distribution, and geochemistry models serve to link structures with fluid chemistry. New and pre-exisiting subsurface datasets are investigated, processed in Leapfrog and interpreted integratively. The current geology model confirmed the dominant rock types in the Lahendong reservoir: breccia and andesite with a minor fraction of tuff. Also, it shows the spatial distribution of feed-zones with respect to the geological units. The new fault model revealed that the southern reservoir is more structurally controlled than the northern reservoir. A major thrust fault in the south has a vital role as a fluid pathway because the surrounding rocks have low porosity. The updated temperature models show no changes with respect to the temperature range of 250-350 oC compared to previous studies. However, the current model revealed that the southern reservoir still contains higher temperatures than the northern as evidently manifested by the dome-shape of temperature lines. Recent studies suggested local cooling in the southern reservoir, as suggested by the decline of temperatures around faults. The geochemistry model unveils barrier and conductor structures based on electrical conductivity of fluids The current models significantly improve the former subsurface knowledge/studies. They also support a better reservoir characterization and visualization in 3D. The models will be a proper basis for the onward numerical models to identify reservoir behavior in future production scenarios/ operation.

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.

Large-scale energy storage plants based on power-to-gas-to-power (PtG–GtP) technologies incorporating high temperature electrolysis, catalytic methanation for the provision of synthetic natural gas (SNG) and novel, highly efficient SNG-fired Allam reconversion cycles allow for a confined and circular use of CO2/CH4 and thus an emission-free storage of intermittent renewable energy. This study features a thorough technology assessment for large-scale PtG–GtP storage plants based on highly efficient sCO2 power cycles combined with subsurface CO2 storage. The Allam cycle employs supercritical CO2 as working fluid as well as an oxy-combustion process to reach high efficiencies of up to 66%. The entire PtG–GtP process chain assessed in this study is expected to reach maximum roundtrip efficiencies of 54.2% (with dedicated and sufficient O2 storage) or 49.0% (with a dedicated air separation unit). The implementation of said energy storage systems into existing national energy grids will pose a major challenge, since they will require far-reaching infrastructural changes to the respective systems, such as extensive installations of renewable generation and electrolysis capacities as well as sufficient subsurface storage capacities for both CO2 and CH4. Therefore, this study incorporates an assessment of the present subsurface storage potential for CO2 and CH4 in Germany. Furthermore, a basic forecast study for the German energy system with an assumed mass deployment of the proposed SNG-based PtG–GtP energy storage system for the year 2050 is conducted. In case of a fully circular use of CO2/CH4, when electricity is solely generated by renewable energy sources, 736 GW of renewables, 234 GW of electrolysis and 62 GW of gas-to-power capacities are required in the best case scenario in 2050. The total storage volume on the national scale of Germany for both CO2 and CH4 was determined to be 7.8 billion N m3, respectively, leading to a CH4 storage capacity of 54.5 TW h. The presented investigations illustrate the feasibility of large-scale energy storage systems for renewable electricity based on high temperature electrolysis, catalytic methanation and Allam power cycles paired with large subsurface storages for CO2 and CH4.

The number of geothermal operations worldwide has been actively growing over the last decades. To increase their efficiency, prevent reservoir depletion and avoid environmental issues, produced water is commonly reinjected. Despite these benefits of fluid reinjection, various clogging problems resulting in injectivity decline have been reported by field operators. Research on individual clogging mechanisms is published in various studies. However, fluid injectivity problems are still widely faced, leading to decreased overall productivity and even abandonment of some wells. Therefore, it is essential to better understand reasons of fluid pathway clogging processes and especially their interactions to efficiently predict and prevent them. In this research, we present a theoretical analysis of different clogging mechanisms. The influence of various parameters on different clogging mechanisms from existing experimental studies and field reports has been reviewed and summarized. Additionally, we compared these experimental literature concepts with a real case study of a running geothermal field facing clogging problems in the Netherlands. The study includes a detailed analysis of production data, as well as fluid and filter sample analyses. Results show correlation patterns between concentration changes of chemical species in the fluid, as well as influence of injection parameters (temperature, flow rate) on injectivity. The outcomes were compared to literature examples to generalize the conclusions. This will allow an improved understanding of processes occurring in geothermal fluids during fluid production and reinjection. As a next step of this research, more field data will be analyzed to identify similar trends and correlations as well as the interdependency of injectivity problems.

Direct Use Geothermal Systems (DUGS) are increasing their installed capacity worldwide and denser developments with multiple doublets are becoming more common. Interference between doublets therefore becomes an additional concern to subsurface uncertainties. Faults can be either barriers or conduits to flow and can affect the fluid pathways inside the reservoir. The interference between two doublets that are separated by a fault has not been previously studied for DUGS. In this work considering subsurface uncertainty in a full factorial design using 5184 3D reservoir simulations we show that a fault can reduce the system lifetime of a two-doublet system by more than 40 % if one doublet is at close proximity to it. Further, we identify that the fault can also improve both the system lifetime and generated Net Present Value (NPV) with appropriate development decisions. Contrary to previous results that did not consider reservoir architecture, a tramline well configuration is preferable when the doublets have the fault in the centre, while a checkerboard configuration is preferable as the distance to the fault decreases. The Heat In Place (HIP) recovery shows a linear relationship with flow rate and well spacing that is not affected by the fault distance or flow properties. The dimensions of the Influence Area (IA) previously considered are insufficient to capture the temperature drop at the producer wells and the fault position can increase this discrepancy. Our results show the importance of fault characterisation and well positioning with respect to a fault considering subsurface uncertainty and how this can affect denser field development of DUGS. Our findings suggest to integrate faults and the relative positioning of well doublets with respect to a fault more strongly in field development plans. Such considerations should also be included in future optimization plans of multi-well geothermal systems. Moreover, the regulatory framework should be revised to achieve a better match between the IA boundary and the production well temperature drop to enable better planning for denser development of DUGS.

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.

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.

Designing low-cost network layouts is an essential step in planning linked infrastructure. For the case of capacitated trees, such as oil or gas pipeline networks, the cost is usually a function of both pipeline diameter (i.e. ability to carry flow or transferred capacity) and pipeline length. Even for the case of incompressible, steady flow, minimizing cost becomes particularly difficult as network topology itself dictates local flow material balances, rendering the optimization space non-linear. The combinatorial nature of potential trees requires the use of graph optimization heuristics to achieve good solutions in reasonable time. In this work we perform a comparison of known literature network optimization heuristics and metaheuristics for finding minimum-cost capacitated trees without Steiner nodes, and propose novel algorithms, including a metaheuristic based on transferring edges of high valency nodes. Our metaheuristic achieves performance above similar algorithms studied, especially for larger graphs, usually producing a significantly higher proportion of optimal solutions, while remaining in line with time-complexity of algorithms found in the literature. Data points for graph node positions and capacities are first randomly generated, and secondly obtained from the German emissions trading CO2 source registry. As political will for applications and storage for hard-to-abate industry CO2 emissions is growing, efficient network design methods become relevant for new large-scale CO2 pipeline networks.

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.

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.