Aquifer thermal energy storage (ATES) has great potential to mitigate CO₂ emissions associated with the heating and cooling of buildings and offers wide applicability. Thick productive aquifer layers have been targeted first, as these are the most promising hydrogeological context for ATES. Regardless, there is currently an increasing trend to target more complex aquifers such as low-transmissivity and alluvial aquifers or fractured rock formations. There, the uncertainty of subsurface characteristics and, with that, the risk of poorly performing systems is considerably higher. Commonly applied strategies to decide upon the ATES feasibility and well design standards for optimization need to be adapted. To further promote the use of ATES in such less favorable aquifers an efficient and systematic methodology evaluating the optimal conditions, while not neglecting uncertainty, is crucial. In this context, the distance-based global sensitivity analysis (DGSA) method is proposed. The analysis focuses on one promising thick productive aquifer, first used to validate the methodology, as well as a complex shallow alluvial aquifer. Through this method, multiple random model realizations are generated by sampling each parameter from a predetermined range of uncertainty. The DGSA methodology validates that the hydraulic conductivity, the natural hydraulic gradient and the annual storage volume dominate the functioning of an ATES system in both hydrogeological settings. The method also advances the state of the art in both settings. It efficiently identifies most informative field data ahead of carrying out the field work itself. In the studied settings, Darcy flux measurements can provide a first estimate of the relative ATES efficiency. It further offers a substantiated basis to streamline models in the future. Insensitive parameters can be fixed to average values without compromising on prediction accuracy. It also demonstrates the insignificance of seasonal soil temperature fluctuations on storage in unconfined shallow aquifers and it clarifies the thermal energy exchange dynamics directly above the storage volume. Finally, it creates the opportunity to explore different storage conditions in a particular setting, allowing to propose cutoff criteria for the investment in ATES. The nuanced understanding gained with this study offers practical guidance for enhanced efficiency of feasibility studies. It proves that the DGSA methodology can significantly speed up the development of ATES in more complex hydrogeological settings.

This paper introduces a comprehensive thermo-hydro-mechanical (THM) modeling framework tailored for high-temperature aquifer thermal energy storage (HT-ATES) systems. Our framework presents a novel dual-assessment approach that simultaneously evaluates thermal performance and geomechanical stability of HT-ATES systems. The framework combines advanced sensitivity analysis with multi-objective optimization to concurrently boost thermal efficiency and maintain geomechanical safety. The model simulates the cyclic injection-extraction process while capturing the interdependent effects of heat transfer, fluid flow, and mechanical stress evolution. A distance-based Generalized Sensitivity Analysis (DGSA) is applied to identify and rank the most critical parameters influencing system performance and stability, particularly in regions such as the cold well and overlying caprock. Furthermore, surrogate models constructed with eXtreme Gradient Boosting (XGBoost) facilitate a computationally efficient Non-dominated Sorting Genetic Algorithm II (NSGA-II) optimization that investigates the trade-offs between enhancing heat production and minimizing failure risks. Validation against high-fidelity simulations reveals that, compared to a benchmark model with a thermal recovery efficiency of approximately 85% and a caprock slip tendency of 34°, the optimized designs achieve around 88% efficiency and reduce the caprock slip tendency to 29°. These quantitative improvements demonstrate that the proposed framework significantly enhances both energy production and geomechanical stability, offering valuable guidance for the design of robust HT-ATES systems under fixed geological conditions.

Geothermal energy extraction through deep mine systems offers the potential to reduce the cost of geothermal systems while meeting the cooling needs of deep mines. However, the injection of cold water into the subsurface triggers strongly coupled thermo-hydro-mechanical (THM) processes that can affect the stability of underground excavations. This study evaluates the impact of geothermal energy extraction on the temperature and stability of a deep mine. By quantifying the sensitivity of the mine temperature and stability to various parameters, we propose a scheme to optimize geothermal energy production, while achieving rapid mine cooling and maintaining stability. We first evaluate the impact of geothermal operations on mine temperature and stability through THM numerical modeling. The simulations show that poro-elastic stress quickly affects mine stability, while thermal stress has a more significant impact on the long-term stability. We then use Distance-based Generalized Sensitivity Analysis (DGSA) to quantify parameter sensitivity. The analysis identifies the distance between the mine system and the geothermal system as the most influential factor. Other important parameters include the injection rate, injection temperature, well spacing, coefficient of thermal expansion, permeability, Young's modulus, and heat capacity. Finally, we propose a DGSA-based optimization framework that accounts for subsurface uncertainty and validate the optimized results. Our results indicate that, with favorable geological conditions, a rational selection of system design parameters can enhance geothermal energy production while ensuring rapid mine cooling and stability. This study provides essential insights for the optimization of deep mine geothermal systems and supports effective decision-making.