Background Deep storage technology is an effective method for disposing high-salinity mine water in western mining areas. The directional well configuration can significantly enhance water injection efficiency, wherein selecting favorable seepage zones with good injectability as the target intervals for drilling is key to the implementation of this technology. However, the precise identification of such favorable seepage zones in deep formations remains a challenging research problem.
Methods By analyzing the characteristics of wellbore temperature changes during water injection, a qualitative evaluation model for dominant permeable zones based on temperature curves was proposed. Based on the principles of momentum conservation and energy conservation, a forward model for predicting temperature in injection wells during deep storage of mine water was established, considering multiple thermal effects. A temperature inversion interpretation model was developed using DTS measured data, with temperature error as the evaluation metric. An iterative fitting process was used to establish a quantitative identification method for dominant permeable zones. On this basis, a deep-well injection test was conducted in a test well of the typical mining area. Distributed optical fiber sensing was used to monitor temperature data at different well depths during three phases: initial well shutdown, water injection, and post-injection warm-back. The temperature curve of the injection well was predicted using the forward and inversion models, and segmented injection flow rates were calculated.
Results and Conclusions (1) During the entire test, the bottom hole temperature was 71.8 ℃. In the initial well shutdown phase, the temperature curve showed a linear distribution with depth, closely approximating the geothermal gradient. During the injection phase, the temperature of the injection layer gradually decreased due to the influence of low-temperature injected water, stabilizing at 23.5-31.8 ℃ by the end of the injection test. The low-temperature extended to a depth of 1 970 m, showing a significant temperature differential boundary with the deeper formation. Based on the well temperature curve model, this depth was identified as the lower boundary of the dominant permeable zone. During the well shutdown phase, the wellbore temperature was slightly lower than the initial shutdown temperature, and a slow recovery was observed between 1 850~1 950 m. The well temperature curve model preliminarily identified this interval as the dominant permeable zone. (2)The predicted temperature profile of the injection well showed good agreement with the DTS (Distributed Temperature Sensing) measured data, with an error margin of less than 0.05. The calculated injection volumes accounted for 69% and 31% of the total well injection within the depth intervals of 1850-1950m and 1505-1850 m, respectively. This indicated that the middle-lower section of the Triassic Liujiagou Formation was the favorable seepage zone, the Heshanggou and upper Liujiagou Formations were secondary seepage zones, while the remaining strata were non-seepage zones. These research findings were consistent with the comprehensive interpretation results based on lithology, drilling fluid loss, and core fracture development, thereby verifying the reliability of the DTS interpretation method. The results provide a valuable reference for optimizing the well configuration and selecting target storage horizons for deep mine water disposal projects.
DownLoad: