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The height of the water-conducting fractured zone (HWFZ) plays a significant role in environmental protection and engineering safety during underground mining. In this study, to measure the HWFZ in the Cuimu coal mine (CCM), in-situ monitoring, including water leakage tests and video capture through a borehole camera, were conducted. Considering mining height, panel width, and buried depth, 26 sets of samples were collected from mines in the northwest to obtain a multi-factor regression formula. Additionally, we used the 26 sets of samples as training material for machine learning to predict the HWFZ. Then, to assess why the traditional empirical formula proposed to measure the HWFZ is inapplicable for the Jurassic coal mines in the northwest, the sedimentary environment of the Ordos Basin, the RQD of drilled cores, and the overburden structure characteristics were investigated. Finally, a strata subsidence model was built to analyze the mathematical mechanism of the HWFZ induced by mining activity. The results show that the proposed regression formula and machine learning model can accurately predict the HWFZ of mines in the northwest. Due to the more stable sedimentary environment, the RQD of drilled cores from the Jurassic coal seam is higher and the strata tend to have better continuity as compared to the cores from the Carboniferous coal seam. The strata subsidence model indicates that the residual bulging coefficient influences the HWFZ significantly, which can explain why the measured HWFZ in the northwest is much larger than the predicted values based on the traditional empirical formula. This study is useful to accurately predict and understand the HWFZ in Jurassic coal seams in northwestern China. |
