Identification of coal mine water-bursting source using multivariate statistical analysis and tracing test

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• 作者：Meng Chen ; Yong Wu ; Dongdong Gao ; Ming Chang
• 关键词：KeywordHydrogeochemical ; Major ion ; Multivariate statistical analysis ; Tracing test ; Water ; bursting source identification
• 刊名：Arabian Journal of Geosciences
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：10
• 期：2
• 全文大小：
• 刊物类别：Earth and Environmental Science
• 刊物主题：Earth Sciences, general;
• 出版者：Springer Berlin Heidelberg
• ISSN：1866-7538
• 卷排序：10

文摘

This study aims to identify the water source of a water-bursting disaster that occurred at the Longmen Gorge South Coal Mine ventilation adit on May 2011. The chosen approach includes the investigation of hydrogeochemical processes of major ions and a tracing test. The relative abundance of major ions is proposed to be Ca2+ > > K++Na+ > Mg for cations and HCO₃− > > SO₄2− > NO₃− > Cl− for anions. A piper diagram of the water samples demonstrates that they are of an HCO₃-Ca water type. Principal component analysis implies that the hydrochemistry of water is a result of multiple factors. PC1 represents ion exchange and natural mineral weathering. PC2 and PC3 indicate hydrological processes of agricultural activities and evaporation, respectively. Cluster analysis of water samples is divided into four groups of clusters (group 1–group 4) and suggests a certain homology and similarity between water samples M1/M2 and S3/S5. The tracer breakthrough curves suggest that there is a large possibility that the injection points are connected with the monitoring points, consistent with the CA view. Analysis and research of the hydrogeochemistry of mine groundwater demonstrate that the use of PCA and CA is a feasible method of identifying the mine’s water-bursting source and determining the possibility of a water-bursting event.