Abstract
Aquifer storage and recovery (ASR) involves the injection, and later extraction, of freshwater into aquifers, which often contain saline groundwater. Mixing between the fresh injectant and native saltwater often leads to part of the injectant becoming unrecoverable, thereby impacting ASR performance. This study explores freshwater-saltwater mixing within ASR operations arising from aquifer heterogeneity using Monte Carlo analysis of 2D-axisymmetric, density-dependent flow and transport models. Logarithmic hydraulic conductivity (lnK) distributions are generated using either two-point statistics or higher-order connectivity features. Results show that higher variance in lnK leads to stronger freshwater-saltwater mixing, which lowers the recovery efficiency (RE; i.e., ratio of extracted to injected freshwater). On average, the lowest RE values were obtained from lnK fields with connected high-K features, across all ASR cycles. In contrast, RE values from lnK fields with connected low-K features were typically the highest, at least where buoyancy was considered. The impact of aquifer heterogeneity on RE reduces with subsequent ASR cycles. Buoyancy was a major factor in lowering RE regardless of the adopted heterogeneity model. Heterogeneity tended to mitigate the adverse impacts of buoyancy, leading to some heterogeneous cases having higher RE values than the corresponding homogeneous case. These results highlight the importance of understanding buoyancy effects and subsurface heterogeneity (including the connectivity of geological structures), and interrelationships thereof when assessing the feasibility of multi-cycle ASR in heterogeneous saline aquifers.
Original language | English |
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Article number | e2021WR031306 |
Pages (from-to) | 1-20 |
Number of pages | 20 |
Journal | Water Resources Research |
Volume | 58 |
Issue number | 5 |
Early online date | 9 May 2022 |
DOIs | |
Publication status | Published - May 2022 |
Bibliographical note
Funding Information:This study was sponsored by the National Key Research Project (2021YFC3200500), National Natural Science Foundation of China (51879088), Fundamental Research Funds for the Central Universities (B200204002), and Natural Science Foundation of Jiangsu Province (BK20190023). Adrian Werner was the recipient of an Australian Research Council Future Fellowship (project number FT150100403) during this research. This study was supported by the High Performance Computing Platform of Hohai University.