Water Inrush Risk Assessment And Water Inflow Prediction In Liuzhuang Coal Mine

Water inrush from coal seam roof and floor not only poses a great threat to coal safety production,but also often causes significant economic losses.Therefore,evaluating the risk of roof and floor water inrush and predicting mine water inflow are of great practical significance for preventing mine water disasters and taking water prevention measures in advance.In this paper,Liuzhuang Coal Mine is taken as the research object Based on the latest geological and hydrological drilling data accumulated in recent years in Liuzhuang Coal Mine,the AHP and GIS vulnerability index methods are used to comprehensively evaluate the water inrush risk of coal 11-2 and coal 1 roof and coal 1 floor.At the same time,the analytic method and artificial neural network method are used to analyze and predict the water inflow of the mine.The results and understanding are as follows:(1)The geological structure characteristics,groundwater recharge,diameter,discharge conditions,mine water filling conditions and water filling factors in the study area are analyzed,and it is determined that the water inrush in coal seam is mainly affected by the complexity of the structure,the water abundance of the aquifer,and the performance of the aquifer.(2)According to the research on the mechanism of roof water inrush,eight main control factors such as the height of roof caving zone,fault scale index,structural intersection and endpoint distribution,aquifer thickness,water-resisting layer thickness and brittle plastic ratio are selected to evaluate the water inrush risk of 11₂ coal and 1 coal roof,and the single factor thematic map is generated for the whole area analysis.(3)Based on the study of floor water inrush mechanism,seven main control factors such as fault scale index,structural intersection and endpoint distribution,aquifer water pressure,equivalent water-resisting layer thickness and brittle-plastic ratio are selected to evaluate the water inrush risk of floor limestone in No.1 coal mine,and single factor thematic map is generated for whole area analysis.(4)AHP(analytic hierarchy process)is used to assign weights to the main control factors of roof and floor,in which the weights of roof factors are 0.176,0.126,0.126,0.147,0.132,0.115,0.095 and 0.083,respectively.The weight of floor factors is 0.176,0.130,0.122,0.143,0.110,0.152,0.168 in order.Using the vulnerability index method based on Arcgis,the thematic map of each factor and its corresponding weight value are weighted and superimposed.According to the degree of water inrush risk,the research area is divided into safety area,relative safety area,transition area,relative risk area and risk area.(5)The analytical method and the artificial neural network method based on RBF are used to analyze and predict the mine water inflow.The large-well method is used to predict the water inflow of coal measures sandstone water and floor limestone water at the first level,the second level and the second level of Liuzhuang Coal Mine.The RBF artificial neural network method analyzes the dynamic changes between the mine water inflow and the mining area,the number of structural fractures and the amount of coal mining.The SPSS software is used to model and predict the mine water inflow from 2006 to 2019.The mine water inflow is 104 m3/h,119 m3/h,128 m3/h,127 m3/h,205 m3/h,206 m3/h,251 m3/h,249 m3/h 251 m3/h,257 m3/h,261 m3/h,261 m3/h,268 m3/h and 268 m3/h,respectively.The accuracy of the model is tested.The average error of the model is 6.35%,and the prediction accuracy of the model is 93.75%.Figure[34] Table [38] Reference [80]...