Risk assessment of water inrush from Ordovician limestone based on analytic hierarchical process modelling and water resistance

Abstract

This study predicts the risk of water inrush from the Ordovician limestone aquifer to No. 17 coal seam in the Yangcun Coal Mine that is mining above confined aquifer. Analysis of geological and hydrogeological data, the analytic hierarchical process modelling of a vulnerability index (VI), water inrush coefficient method, and the safety factor under pressure method were used to systematically assess the risk of water inrush. Firstly, the main influencing factors were determined, including the yield and pressure of water in the Ordovician limestone aquifer, the effective thickness of water-resisting strata, the ratio of limestone to sandstone-mudstone in these strata, the fault fractal dimension, and the fault scale index. A vulnerability assessment model was established and VI values were calculated. Water inrush risk partitioning thresholds were obtained by the natural breakpoint classification method. Secondly, based on the field water injection test of the study area and its surrounding mining areas, the water-resisting strength of the rock layer from No. 17 coal seam floor to the roof of Ordovician limestone is obtained. Finally, to verify the accuracy of the model, water inrush coefficient and safety factor under pressure were calculated. The results can well verify the accuracy of the analytic hierarchical process (AHP) vulnerability index assessment results. These study results provide guidance for predicting water inrush disasters related to the mining above confined aquifer of deep coal seam. KeywordsMining area • Mining above confined aquifer •risk of water inrush • Vulnerability index method • Safety factor under pressure * Shuyun Zhu

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Risk Assessment of Water Inrush from Coal Floor Based on Karst Fractal-Vulnerability Index Method

“…e method decomposes a complex problem into different factors and forms a multilevel structure model according to the mutual influence relationship and membership relationship between factors. By analyzing and comparing the importance of each factor, the judgment matrix was created, and, finally, the qualitative and quantitative analyses of multiple factors were completed [29][30][31]. ere are generally four steps: (a) establishment of a hierarchical structure model, (b) construction of a comparative judgment matrix, (c) calculation of the largest eigenvalue of the matrix and the corresponding eigenvector, and (d) hierarchical ranking and consistency check.…”