Formation mechanism and prediction method of water inrush from separated layers within coal seam mining: A case study in the Shilawusu mining area, China

A New Quantitative Method for Risk Assessment of Coal Floor Water Inrush Based on PSR Theory and Extension Cloud Model

“…The mining disturbance of coal can be regarded as pressure, which has an impact on the state of the hydrological environment around the coal seam, and then, the production department takes measures to respond, as shown in Figure 1. Based on this idea, combined with literature [2][3][4][5][6][7][8][9][10][11][12], the risk assessment of coal floor water inrush is established. For the pressure type indicators, it mainly refers to the mining factors.…”

“…Li et al aimed at the problem that the traditional water inrush coefficient method cannot accurately assess the water inrush risk of a floor under specific conditions, through the analysis of the distribution of water inrush points and the scale of water inrush events, combined with the three indicators of Ts, M, and q, the water inrush vulnerability is divided into four levels: safety, medium safety, potential danger, and high risk [4]. Fan et al analyzed the mechanical mechanism of water inrush (WIFSL) from separated layers, derived theoretical discriminants of the first stage and periodic WIFSL based on this, and used the water inrush coefficient method to divide the water inrush risk [5].…”

Multisource Information Risk Evaluation Technology of Mine Water Inrush Based on VWM: A Case Study of Weng’an Coal Mine

“…Mine water risk has always been one of the important factors restricting coal mining in China, and it is of great application value to carry out research on mine water inrush risk prediction technology [1][2][3][4][5]. In China, the forecast of coal floor water inrush has been studied for more than 40 years.…”

Risk assessment of water inrushes from bed separations in Cretaceous strata corresponding to different excavation lengths during mining in the Ordos Basin

“…However, the role of the fractured aquiclude in BWIs was ignored, although it had the ability to resist water due to closure of the fracture. Fan et al (2019b) established a BWI mechanical model and deduced the theoretical discriminant of the first and periodic BWIs. However, the driving force of BWIs was found to be bed-separation water pressure, which was inconsistent with other results that suggested that the driving force was derived from the fracture and impact of the rock strata above the bed separation.…”

“…However, because the boundary values between different risk levels were obtained by a natural classification method in ArcGIS, the boundary values changed with the mining area range and number of points that were sampled, which was not a realistic assumption. By using the water inrush coefficient method, Fan et al (2019b) obtained the boundary values between different BWI risk levels in the Shilawusu mine. However, the formula determining the water inrush coefficient is an empirical formula based on a large number of floor water inrush cases, which is unsuitable for the assessment of BWI risk due to its association with roof water inrush.…”