Assessment of water inrush risk using the principal component logistic regression model in the Pandao coal mine, China

Liu, Weitao; Li, Qiang; Zhao, Jiyuan; Fu, Biao

doi:10.1007/s12517-018-3815-9

Cited by 17 publications

(8 citation statements)

References 11 publications

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“…The IWYPI model in this paper is established according to Equation ( 29) and shown as Equation (30). Correspondingly, the water yield property index (WYPI) model weighted by the FDAHP and EWM can also be calculated by Equation (29).…”

Section: : ð15þmentioning

confidence: 99%

“…The fuzzy clustering method is theoretical and difficult to combine with actual mining areas [28]. However, principal component analysis effectively eliminates the influence of information superposition among evaluation indexes [29], but it compromises by making the evaluation index value fuzzy to reduce the dimensionality of the variables [30].…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of the Water Yield of Coal Roof Aquifers Based on the FDAHP-Entropy Method: A Case Study in the Donghuantuo Coal Mine, China

Zhang

et al. 2021

Geofluids

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The water yield of coal seam roof aquifers is the key factor for evaluating and controlling water disasters in coal seam roofs. To evaluate the water yield of the sandstone aquifer in the roof of the Carboniferous-Permian Damiaozhuang Formation no. 8 coal seam in the Donghuantuo Mine, North China, seven main controlling factors affecting the water yield of sandstone aquifers are determined, including the permeability coefficient, consumption of drilling fluid, core recovery, aquifer thickness, brittle-plastic rock thickness ratio, fault scale index, and fault point density. Further, the fuzzy Delphi analytic hierarchy process (FDAHP) and entropy weight method (EWM) are used to calculate the subjective and objective weights of each main factor, respectively, and a combination weight model (CWM) is proposed based on the least square method to compose the comprehensive weights. Then, an improved water yield property index (IWYPI) model is established, and the water yield zoning map of sandstone aquifers is acquired. Engineering practice shows that the evaluation accuracy of the water yield property index (IWYPI) model based on the CWM is as high as 93.75%, which is 18.75% and 12.5% higher than that of the water yield property index (WYPI) model based on the FDAHP and EWM, respectively. The research results propose a novel method for evaluating the water yield of coal seam roof aquifers and can provide scientific guidance for the prevention and control of water disasters in the no. 8 coal seam roof of the Donghuantuo Coal Mine.

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Section: : ð15þmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Evaluation of the Water Yield of Coal Roof Aquifers Based on the FDAHP-Entropy Method: A Case Study in the Donghuantuo Coal Mine, China

Zhang

et al. 2021

Geofluids

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“…Basing on the data fusion method of the grey theory system, the water inrush risk of the deep coalface from Ordovician limestone in the Xingdong Coal Mine was evaluated (Guo et al 2020). A predictive model of the Pandao Coal Mine was established by combining principal component logistic regression analysis with GIS and the predicted results were consistent with observed water inrush points (Liu et al 2018). Numerical simulation technology was used to analyse the floor-failure mechanism of a typical working face in the Chenghe Coal Mine and the risk of water inrush from Ordovician limestone was evaluated by determining the maximum failure depth of the working face floor (Li et al 2020).…”

Section: Introductionmentioning

confidence: 99%

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

2021

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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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“…Unfortunately, coal mining and groundwater resources frequently come into conflict due to the detrimental effects of coal mining on water resources and mining disasters. These impacts have been well documented around the world (ISTVAN et al 1982;Jarvis and Younger 2000;Osenbr€ uck et al 2006;Kallioras and Ruzinski 2011;Chen et al 2018). One primary issue is related to mine safety, as the potential inrush of groundwater at the working face during the mining of deep coal seams poses a serious threat to safe operations (Guo et al 2009).…”

Section: Introductionmentioning

confidence: 99%

“…In recent years, deep coal mining has emerged in China due to the exhaustion of shallow coal resources. Due to the complex and unpredictable geological conditions in deep mines, coal mining operations face tremendous challenges (Xu et al 2016;Qiu et al 2017;Zhang et al 2017;Dai et al 2018;Li 2018;Liu et al 2018;Zhao et al 2018).…”

Section: Introductionmentioning

confidence: 99%

Prediction of floor water disasters based on fractal analysis of geologic structure and vulnerability index method for deep coal mining in the Yanzhou mining area

Qiao

Zhang³

et al. 2019

Geomatics, Natural Hazards and Risk

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Assessment of water inrush risk using the principal component logistic regression model in the Pandao coal mine, China

Cited by 17 publications

References 11 publications

Evaluation of the Water Yield of Coal Roof Aquifers Based on the FDAHP-Entropy Method: A Case Study in the Donghuantuo Coal Mine, China

Evaluation of the Water Yield of Coal Roof Aquifers Based on the FDAHP-Entropy Method: A Case Study in the Donghuantuo Coal Mine, China

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

Prediction of floor water disasters based on fractal analysis of geologic structure and vulnerability index method for deep coal mining in the Yanzhou mining area

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