This is a Preprint and has not been peer reviewed. This is version 1 of this Preprint.

Decision-making under uncertainty for shallow geothermal systems in complex subsurface settings: application to a low-transmissivity aquifer
Downloads
Authors
Abstract
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.
DOI
https://doi.org/10.31223/X56B13
Subjects
Geology, Hydrology, Natural Resources and Conservation, Sustainability
Keywords
aquifer thermal energy storage (ATES), hydrogeology, decision-making, sustainability, Optimization, Geothermal energy, Uncertainty quantification
Dates
Published: 2025-05-07 21:32
Last Updated: 2025-05-08 16:30
License
CC BY Attribution 4.0 International
Additional Metadata
Conflict of interest statement:
On behalf of all authors, the corresponding author states that there is no known conflict of interest that could have influenced the work reported in this paper.
Data Availability (Reason not available):
The input and output data of the simulations generated and used for the DGSA’s of this study are openly available on Zenodo https://doi.org/10.5281/zenodo.15119419. The scripts used to process the input and output are available on GitHub https://github.com/lukatas/ATES_SensitivityAnalyses.
There are no comments or no comments have been made public for this article.