Numerical modeling reveals strong fault-controlled horizontal permeability anisotropy in a sedimentary geothermal reservoir, suggesting adaptive reinjection is vital for sustainable exploitation.
The structurally complex Cangdong fault zone controls the medium- to low-temperature geothermal potential of the Dongli Lake field in Tianjin, China. Previous assessments in Chinese sedimentary basins predominantly employed simplified volumetric methods that cannot capture transient system behavior under production–reinjection conditions, largely due to the scarcity of systematic dynamic monitoring data. This study addresses this gap by exploiting relatively abundant dynamic monitoring records in the study area, integrating borehole stratigraphy, geological cross-sections, and well logging data to construct a 3D geological model and coupled numerical model of the fault-controlled reservoir. Meticulous natural-state calibration against temperature and pressure logging monitoring data yields key reservoir parameters, achieving mean relative errors of 2.35–3.33% for temperature and 6.32–9.73% for pressure. These results are based on calibration against wells DL-19 and DL-40, which intersect the Jxw reservoir at depths of 1850–2300 m. This process quantifies thermal conductivity and reveals pronounced permeability anisotropy in the primary Jixian Wumishan (Jxw) reservoir, with horizontal permeability (3.00 × 10−13 m2) an order of magnitude higher than vertical (3.00 × 10−14 m2), directly evidencing the fault zone’s hydraulic dominance. Dynamic sensitivity analysis demonstrates that optimal well placement must target high-permeability zones adjacent to the main fault, and adaptive reinjection protocols are proposed for pressure maintenance and thermal drawdown mitigation. This research provides a calibrated, data-driven framework and scientifically grounded strategies for long-term sustainability of the Dongli Lake resource, with transferable implications for optimizing development in other fault-controlled sedimentary basin systems.
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Liu et al. (2026) studied this question.
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