• Energy Research

Exploiting geothermal energy using existing deep mining systems streamlines the development of geothermal systems while addressing the cooling needs of deep mines. However, the combined effects of low-temperature and high-pressure injection during geothermal operations adversely impact the stability of deep mine drifts. This makes it crucial to reliably assess the stability of the drifts and ensure the desired temperature evolution near drifts and the production well. In this paper, we investigate the impact of deep geothermal operations on the stability of mine drifts through thermo-hydro-mechanical (THM) numerical modeling. The results show that impact of cold water injection on the stability of the mine is predominantly influenced by thermal effects, in addition to poro-elastic effects. The reduction in temperature and the increase in pore pressure both contribute to a decrease in effective stress, which is detrimental to the drift stability, though the evolution of the different mechanisms differs. Furthermore, we utilize the distance-based generalized sensitivity analysis (DGSA) method to quantify the sensitivity of the THM model parameters (including design parameters and material properties), thereby optimizing the system design. The results show that the distance between the mine system and the geothermal system is the paramount factor influencing the system's response. Other design parameters (injection rate and temperature, well spacing) and material properties (thermal expansion coefficient, permeability, Young's modulus and heat capacity) also hold substantial significance. Conversely, the system's behaviour is not sensitive to parameters such as porosity and thermal conductivity. By analyzing the range of parameters using DGSA, we provide recommendations for optimizing the system. The verification results show that, given favorable geological settings as suggested, rational selection of system design parameters can facilitate efficient geothermal extraction activities in deep mines. This approach finds optimized development options considering uncertainty of the subsurface, offering valuable advice and guidance for decision-making in geothermal production.

AbstractThe installed capacity of geothermal systems for direct use of heat is increasing worldwide. As their number and density is increasing, the their interaction with subsurface faults becomes more important as they could lead to safety risks from induced seismicity. Assessment and management of such risks is essential for the further development and extension of geothermal energy for heating. At the same time, the economic output of geothermal systems can be marginal and is hence often supported by subsidy schemes. A combined assessment of fault stability and economic output could help operators to balance economic and safety aspects, but this is currently not common practice. In this study we present a methodology to assess field development plans based on fault stability and Net Present Value (NPV) using reservoir simulations of a fluvial, heterogeneous sandstone representative of the majority of direct-use Dutch geothermal systems. We find that the highest friction coefficient leading to exceedance of the Mohr–Coulomb failure criteria in this sandstone is 0.17; such values could be encountered in clay-rich fault gouges. Similar or lower fault permeability compared to the reservoir results in no changes and an increase respectively of both NPV and fault stability with larger Fault-to-Well Distance (FWD). Fault permeability higher than the reservoir permeability results in a minor increase in NPV with smaller FWD. Our results demonstrate that a combined analysis of thermal, hydraulic, mechanical and economic assessment supports a responsible and viable development of geothermal resources at a large scale. The importance of a high spatial density of supporting stress data will be essential for a better understanding and quantification of economic and fault stability effects of geothermal operations.

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. Reservoir Engineering

Energy is released when feed waters with different salinity mix. This energy can be captured in reverse electrodialysis (RED). This paper examines experimentally the effect of varying feed water concentrations on a RED system in terms of permselectivity of the membrane, energy efficiency, power density and electrical resistance. Salt concentrations ranging from 0.01 M to 5 M were used simultaneously in two stacks with identical specifications, providing an overview of potential applications. Results show a decrease of both permselectivity and energy efficiency with higher salt concentrations and higher gradients. Conversely, power density increases when higher gradients are used. The resistance contribution of concentration change in the bulk solution, spacers and the boundary layer is more significant for lower concentrations and gradients, while membrane resistance is dominant for high concentrations. Increasing temperature has a negative effect on permselectivity and energy efficiency, but is beneficial for power density. A power density of 6.7 W/m(2) is achieved using 0.01 M against 5 Mat 60 degrees C. The results suggest that there is no single way to improve the performance of a RED system for all concentrations. Improvements are therefore subject to the specific priorities of the application and the salt concentration levels used. Regarding ion exchange membranes, higher salinity gradients would benefit most from a higher fixed charge density to reduce co-ion transport, while lower salinity gradients benefit from a thicker membrane to decrease the osmotic flux. (C) 2013 Elsevier Ltd. All rights reserved.

Geothermal energy is gaining momentum as a renewable energy source. Reservoir simulation studies are often used to understand the underlying physics interactions and support decision making. Uncertainty related to geothermal systems can be substantial for subsurface and operational parameters and their interaction with regards to the output in terms of lifetime, energy and economic output. Specifically, for geothermal systems with the fault acting as the main fluid pathway the relevant field development uncertainties have not been comprehensively addressed. In this study we show how the produced energy, system lifetime and NPV are affected considering a range of subsurface and operational parameters as uncertainty sources utilizing an ensemble of 16,200 3D Hydraulic-Thermal (HT) reservoir simulations, conceptually based on the Rittershoffen field. A well configuration with oblique angles with respect to the main permeability anisotropy axes results in higher system lifetime, generated energy and NPV. A well spacing of 600 m consistently yields a higher economic efficiency (€/MWh) under all uncertainty parameters considered. More robust development options could be utilized in the absence of fault permeability characterization to ensure improved output prediction under uncertainty. Studies based on the methodology presented can improve investment efficiency for field development under subsurface and operational uncertainty. Renewable Energy, 171 ISSN:0960-1481 ISSN:1879-0682

This paper presents a techno-economic analysis of a deep, direct use geothermal heat system in a conductive geological setting (Groningen, NE Netherlands). The model integrates the previously discussed uncertainties of the initial reservoir state, geological and operational conditions with the economic uncertainties. These uncertainties are incorporated in the form of probability distributions and 20,000 iterations of the model are performed over a project lifetime of 40 years. A combination of Ex-Ante and Ex-Post criteria are used to evaluate the economic performance of the system based on the Net Present Value (NPV), Levelised Cost of Heat (LCOH) and Expected Monetary Value (EMV). The sensitivity analysis highlights the load factor (effective flowrate) as the most important parameter for the economic performance and energy costs. However, the differences between the NPV and LCOH sensitivities highlight the importance of using both metrics for the economic performance of such systems. The presented project remains economically challenging, exhibiting a 50% probability of marginal revenues over its lifetime. Systematic insights are drawn with regard to potential improvements of technical and economic aspects of such geothermal heat systems.

GeoDFN is an open-source software that provides comprehensive control over fracture properties and allows us to explore how a broad range of geological uncertainties impact the geometry and connectivity of fracture networks. GeoDFN employs a hybrid approach, combining the advantages of mechanical and statistical methods in generating DFNs, which ensures geological consistency in fracture placement while maintaining computational efficiency. At the core of this hybrid approach is the consideration of stress shadow, as buffer zone around fractures, which impose a minimum spacing between fractures and prevent them from being placed in geologically unrealistic locations. Considering stress shadow also imposes a natural limit on the maximum fracture intensity of the network, reflecting the network saturation observed in real geological formations. Various models for calculating fracture apertures are provided in GeoDFN, including models that account for external stress conditions, such as the Barton-Bandis model. This capability enables detailed analysis of how fracture apertures influence fluid flow and network permeability under different geological conditions.GeoDFN can be linked to any flow simulator capable of modeling fluid flow in fractured geological formations, providing a versatile tool for subsurface flow analysis. Here, we demonstrate its integration with the MATLAB Reservoir Simulation Toolbox (MRST), an open-source simulator widely used for modeling flow and transport processes. The integration with MRST enables users to easily import generated DFNs and conduct a variety of simulations, including single-phase and multiphase flow, heat transfer, and solute transport. By utilizing MRST’s Embedded Discrete Fracture Model (EDFM) approach, the complex interactions between fractures and the surrounding rock matrix are accurately represented. This connection facilitates the evaluation of how different uncertainties in fracture properties affect subsurface flow behavior, making it a powerful tool for uncertainty quantification and sensitivity analysis in diverse geological settings.

High-Temperature – Aquifer Thermal Energy Storage (HT-ATES) can significantly increase Renewable Energy Sources (RES) capacity and storage temperature levels compared to traditional ATES, while improving efficiency. Combined assessment of subsurface performance and surface District Heating Networks (DHN) is key, but poses challenges for dimensioning, energy flow matching, and techno-economic performance of the joint system. We present a novel methodology for dimensioning and techno-economic assessment of an HT-ATES system combining subsurface, DHN, operational CO 2 emissions, and economics. Subsurface thermo-hydraulic simulations consider aquifer properties (thickness, permeability, porosity, depth, dip, artesian conditions and groundwater hydraulic gradient) and operational parameters (well pattern and cut-off temperature). Subject to subsurface constraints, aquifer permeability and thickness are major control variables. Transmissivity ≥ 2.5×10 -12 m 3 is required to keep the Levelised Cost Of Heat (LCOH) below 200 CHF/MWh and capacity ≥ 25 MW is needed for the HT-ATES system to compete with other large-scale DHN heat sources. Addition of Heat Pumps (HP) increases the LCOH, but also the nominal capacity of the system and yields higher cumulative avoided CO 2 emissions. The methodology presented exemplifies HT-ATES dimensioning and connection to DHN for planning purposes and opens-up the possibility for their fully-coupled assessment in site-specific assessments.