Numerical Study on the Surface Movement Regularity of Deep Mining Underlying the Super-Thick and Weak Cementation Overburden: A Case Study in Western China

A new indicator for estimating the degree of mining-induced land subsidence: the overburden's average GSI value

Underground coal mining leads to land subsidence, which, in turn, results in damage to buildings and infrastructure, disturbs the original ecological environment, and hinders the sustainable development of coal mining cities. A reasonable estimation of land subsidence, on the other hand, is the foundation for building protection, land reclamation, and ecological environment reconstruction. However, when we applied the existing land subsidence estimation theory to the deep mining areas of the Ordos coalfield in western China, there was a significant deviation between the estimations and the measurements. To explain such unusual case, we propose using the overburden's average GSI (Geological Strength Index) value instead of the compressive strength (UCS) of rock specimens for a better representation of the overburden's overall properties. By using on-site subsidence monitoring results and historical data, we provided evidence which supports that the overburden's average GSI value has a much greater impact on subsidence rates than the UCS. Subsequently, we investigated the relationship between three typical overburden's GSI values and the subsidence rates via a calibrated numerical model, revealing the variation patterns of maximum surface subsidence when the overburden's average GSI value is set at 30, 50, and 75, respectively. Finally, on the basis of the measured and simulated results, we discussed a non-conventional strip mining method for mining subsidence control in the deep mining areas of the Ordos coalfield in western China, and explained why it is possible and what are the significant advantages behind. The proposed methods, findings, and suggestions in this paper are therefore quite helpful for researchers and engineers who wish to estimate and control the mining-induced land subsidence, as well as for those who are particularly interested in the study of environment science related to land subsidence.

Analysis of Factors Influencing Mining Damage Based on Engineering Detection and Machine Learning

The direct results of mining damage are overburden fracture and surface subsidence, which may induce groundwater seepage and surface vegetation degradation. Therefore, it is essential to research the factors and mechanisms influencing mining damage. Based on the geological characteristics of the Xiaobaodang minefield in the Yushen Mine area in China, the engineering detection of fractured zone height (FZH), sampling tests of rock mechanical properties, and field measurements of the surface settlement were carried out. Firstly, the factors influencing the FZH were screened by correlation analysis and partial correlation analysis. Next, a model for predicting the maximum height of the fracture zone with the BP neural network (BPNN) was established and trained with Python. Finally, the FLAC3D numerical simulation experiment was adopted to reveal the variation law of overburden stress during coal mining, and the relationship between stress and overburden fracture was analyzed. The results show the following: When the average mining thickness in the study area is 5.8 m, the maximum height of the fractured zone is 157.46 m, and the maximum surface subsidence is 3715 mm. Further, the mining thickness, mining depth, the compressive strength of overburden, the width of the working face, and the mining velocity are the main factors affecting the maximum height of the fractured zone. Additionally, the goodness of fit of the BPNN model can reach 97.22%, meaning that it can effectively predict the maximum height of the fractured zone caused by coal mining. Finally, the area where the stress changes markedly above the goaf is the area where the fractures develop rapidly. Meanwhile, there is a positive correlation between the surface subsidence and the FZH. The research results obtained provide new ideas for reducing mining damage and will be helpful for the green and sustainable development of the mine.

A Field Study on the Law of Spatiotemporal Development of Rock Movement of Under-Sea Mining, Shandong, China

The phenomenon of rock movement in mining areas has always been a difficult problem in mining engineering, especially under complicated geological conditions. Although the backfilling method mitigates the destruction of the surrounding rock, deformation can still exist in the mining area. In order to ensure the safety of under-sea mining, it is necessary to study the rock movement laws and the mechanisms. This paper focuses on a settlement analysis of the monitoring data of the No. 55 prospecting profile. By analyzing the shape of the settlement curves, the spatial distribution characteristics of settlements of different mining sublevels are summarized. Additionally, the fractal characteristics of the settlement rate under different space–time conditions are studied. We also discuss the relationship between the fractal phenomenon and the self-organized criticality (SOC) theory. The findings are of great theoretical value for the further study of mining settlements to better understand the physical mechanisms of internal movement and rock mass failures through the fractal law of the settlement. Furthermore, elucidating the rock movement law is an urgent task for the safety of seabed mining.