Application of Clustering and Stepwise Discriminant Analysis Based on Hydrochemical Characteristics in Determining the Source of Mine Water Inrush

Abstract

In order to explore the law of groundwater evolution, the water source connection between faults and aquifers and the main sources of mine water inrush in the deep mining area of Yangcheng Coal Mine in Jining City, 40 groups of hydrochemical samples were collected and analyzed by Piper Diagram and Durov Diagram. The results showed that the fluidity of groundwater developing to the deep became weaker, the value of total dissolved solids (TDS) became larger. So, the roof and floor of coal seam were more similar in water quality types due to the conduction of faults. Using principal component analysis (PCA) to the raw data, two principal components were extracted, and the principal component scores were used as clustering variables for hierarchical cluster analysis (HCA), 5 groups of abnormal water samples were eliminated and 3 clustering groups M1, M2 and M3 were obtained from the other water samples on the tree diagram. The results showed that the combination of HCA and hydrochemical analysis was more effective in screening water samples, and the 3 clustering groups could be qualified samples to represent 3 major aquifers (Taiyuan Formation limestone aquifer, Shanxi Formation sandstone aquifer and Ordovician limestone aquifer). Finally, taking M1, M2 and M3 as grouping variables, the discriminant functions f 1 , f 2 and f 3 of the 3 aquifers were obtained, the results of stepwise discrimination analysis (SDA) showed that the discrimination model established by using 25 groups of standard water samples could discriminate the known water samples with the correct rate of 96%, 10 groups of unknown water samples collected at the fault are identified as Taiyuan Formation limestone water samples, which was consistent with the classification results of HCA, proving that the water inrush of fault DF53 was from Taiyuan Formation limestone aquifer, while the fault had little influence on Ordovician limestone aquifer.

Interpreting Mine Water Sources and Determining Mixing Ratios Based on the Spatial and Chemical Characteristics of Bedrock Brines in a Coastal Mine

“…Principal component analysis replaces the original water sample information with the extracted principal components, which is a linear combination of the original information. Although it contains complete water sample information, it also results in the main information becoming "neutralized" by the secondary information, which weakens the indication role of the key information and may lead to an inability to accurately identify the water source [23].In this study, principal component analysis, cluster analysis, hydrogeochemical analysis, the maximum likelihood method, and other methods were used to identify the water sources in the Xishan mining area [8,16,24]. However, due to the limitation of timescales and the research area, the common problem with the methods was that only one type of brine was considered in all of the sublevels.…”