Decision-making under uncertainty for shallow geothermal systems in complex subsurface settings: application to a low-transmissivity aquifer

Excess thermal energy can be stored in the subsurface and recovered when needed to heat and cool buildings sustainably. Aquifer thermal energy storage systems (ATES) are gaining popularity worldwide. Most operational systems are located in thick productive aquifers. Their efficiency and wide applicability have been proven and there is now a tendency to explore more complex settings. Aquifers with high natural groundwater flow, fractured rocks, and low-transmissivity aquifers could be added to the list of potential ATES targets. Currently, uncertainty about the systems’ efficiency due to geological complexity hinders the investment in these settings. Reducing investment risk through improved decision-making becomes crucial. This paper introduces a methodology to establish a decision tree for ATES, enabling decision-makers to develop ATES systems effectively, and applies this methodology to a low-transmissivity aquifer. Decisions need to be made on two prediction targets: hydraulic feasibility and thermal feasibility. A sensitivity analysis of the output of groundwater flow and heat transport models improves our understanding of the impact of model parameters and engineering actions on both prediction targets. From that analysis, we find that storage conditions with transmissivity below 20 m²/d lead to inefficient systems. Desirable storage conditions have transmissivity above 40 m²/d. Thermal breakthrough risk is higher when longitudinal dispersion is above 3 m. Our approach results in some minimum system requirements in terms of subsurface properties that have to be reached for which an investment is justified. Finally, the decision tree proposes target engineering actions to decrease the investment risk while optimizing the return.