Zhenxing Li

Geothermal reinjection is critical for sustainable exploitation of geothermal resources, yet the permeability evolution mechanism of carbonate geothermal reservoirs remains poorly understood. Taking dolomite geothermal reservoirs of the Wumishan Formation in the Xiong’an New Area as the research object, high-temperature and high-pressure dynamic flow experiments and TOUGHREACT simulations were performed to investigate the effects of injection pressure, temperature, and water chemistry on the permeability of matrix and fractured cores. Results show that the optimal injection pressure and temperature for both core types are 14 MPa and 70 °C. Under such conditions, the final average permeability of matrix and fractured cores is 0.0015 mD and 0.0287 mD, with CV values of 7.3% and 6.2%, respectively. Chemically treated water suppresses calcite dissolution by altering ionic composition and pH, thereby reducing permeability of both cores, while the reduction is less significant for fractured cores. Simulations indicate that reinjection water triggers slightly stronger calcite dissolution than dolomite precipitation and yields permeability enhancement. When treated water is injected, reaction intensity declines, Mg²⁺ concentration approaches zero, and dolomite precipitation becomes more thorough. Matrix cores follow an “activation-stabilization” pattern, whereas fractured cores exhibit a “decay-convergence” pattern and are more sensitive to pressure. This study reveals distinct responses of matrix and fractures to hydrochemical perturbations in dual-porosity carbonate geothermal reservoirs, demonstrating that permeability evolution during reinjection is jointly governed by reservoir pore type and hydrochemical conditions. The findings provide mechanistic support for targeted regulation of reinjection water chemistry.

The development of high-salinity geothermal resources is hindered by corrosion, scaling, and high water treatment costs, posing severe challenges for conventional hydrothermal systems. Deep borehole heat exchanger (DBHE) technology, which extracts heat without water production and avoids contact with high-salinity fluids, offers a promising alternative. In this study, field experiments on a coaxial DBHE were conducted in well SQ-1 (over 3000 m deep) in the Xining Basin, targeting its dual structure: a shallow high-salinity aquifer and a deep high-temperature low-permeability basement. Results show that the deep Proterozoic metamorphic basement has extremely low permeability (10⁻⁸ cm/s), with a bottom hole temperature of 113 °C and an average geothermal gradient of 3.39 °C/100 m, confirming it as a stable solid heat source. Under steady-state operation, the heat extraction rate averaged 150 W/m (144–155 W/m, with an uncertainty of approximately ±3 W/m). A marginal effect of flow rate was observed: increasing flow from 40 to 50 m³/h increased heat extraction by only 1.5%, indicating a threshold flow-rate range beyond which continued flow increases yield diminishing returns. No groundwater extraction, corrosion, or scaling was observed during the 13-day test, confirming the short-term operational reliability of the system under the tested conditions. This study validates shifting heat extraction to deep low-permeability basements to avoid high-salinity issues, providing a scientific basis for clean geothermal utilization in similar regions globally.

Geothermal exploration and monitoring often require dense temperature observations in terrains where wired networks are impractical and battery replacement for in situ sensors is costly. This paper proposes an infrared-assisted, temperature-aware access scheme for a UAV-enabled backscatter IoT network tailored to geothermal hotspot sensing. A rotary-wing UAV equipped with a thermal infrared camera and an RF transceiver first surveys the area to construct a surface temperature map and identify candidate hotspots, and then hovers above a selected hotspot to perform periodic frames consisting of wireless energy transfer followed by backscatter uplink collection. Ground sensors harvest RF energy, measure their local temperature, and autonomously activate only when both the harvested energy exceeds a threshold and the measured temperature falls within a target interval broadcast by the UAV, thereby concentrating channel access on thermally relevant nodes. We develop a system model that couples a geothermal-like thermal field, RF energy harvesting, and framed slotted backscatter access, and introduce hotspot-oriented performance metrics including effective hotspot throughput, task completion time, and energy per hotspot report. The simulation results show that the proposed temperature–energy-gated access significantly increases the fraction of successfully decoded packets originating from hotspot regions and improves the energy efficiency of geothermal monitoring compared with full activation and purely energy-based activation.