During the construction of underground caverns, the stability of deep underground cavern excavation, which affects the safety and sustainable development of such projects, is a hot issue. First, based on the mechanical properties of surrounding rock in deep tunnels, the strain-softening behavior, damage, and heterogeneity of rock masses are analyzed. Then, a strain-softening model of heterogeneous jointed rock mass that considers statistical damage (SSD) is developed and implemented through FLAC3D simulation software. Finally, the SSD is applied to a deep roadway in the Jinchuan mining area, and a comparative analysis of the computation results of the Mohr–Coulomb (MC) model and the strain-softening (SS) model are carried out. The numerical results are compared with the field-monitoring results, which show that the SSD model simulated the behavior of the surrounding rocks well. The results show that the deformations of the roof and floor are larger, which may serve as a reference for the support pattern of deep roadways.

The safety of underground roadways is a major issue in mining engineering, with economic impacts and potential threats to the lives of workers. Elucidating the deformation failure mechanisms is necessary to solve these problems. The deformation failure modes and characteristics of roadways buried at various depths were investigated using a detailed field survey in the Jinchuan nickel mine. At greater depths, roadway deformation was more serious, the creep phenomena were more prominent, and support structures were more prone to failure. Numerical simulations were performed on the roadways under various geo-stresses and rock mass structures, which indicated that the roadway deformation mode was mainly controlled by a rock mass structure in a lower stress environment and the control effect was weakened with the gradual increase of ground stress. Six deformation failure types were proposed to examine roadway deformation failure mechanisms. Field representation of each failure type was characterized under natural or induced conditions. The findings provide a reference for stability evaluation and support the design of roadway engineering under similar geological conditions.

Ground subsidence is a common geological phenomenon occurring in mining areas. As an important Chinese gold mine, Sanshandao Gold Mine has a mining history of 25 years, with remarkable ground subsidence deformation. Mining development, life security, property security and ecological protection all require comprehension of the ground subsidence characteristics and evolution in the mining area. In this study, the mining subsidence phenomenon of the Sanshandao Gold Mine was investigated and analyzed based on Persistent Scatterer Interferometry (PSI) and small baseline subset (SBAS). The SAR (synthetic aperture radar) images covering the study area were acquired by the Sentinel-1A satellite between 2018 and 2021; 54 images (between 22 February 2018 and 25 May 2021) were processed using the PSI technique and 24 images (between 11 April 2018 and 12 July 2021) were processed using the SBAS technique. In addition, GACOS (generic atmospheric correction online service) data were adopted to eliminate the atmospheric error in both kinds of data processing. The interferometric synthetic aperture radar (InSAR) results showed a basically consistent subsidence area and a similar subsidence pattern. Both InSAR results indicated that the maximum LOS (line of sight) subsidence velocity is about 49 mm/year. The main subsidence zone is situated in the main mining area, extending in the northwest and southeast directions. According to the subsidence displacement of several representative sites in the mining area, we found that the PSI result has a higher subsidence displacement value compared to the SBAS result. Mining activities were accompanied by ground subsidence in the mining area: the ground subsidence phenomenon is exacerbated by the increasing mining quantity. Temporally, the mining subsidence lags behind the increase in mining quantity by about three months. In summary, the mining area has varying degrees of ground subsidence, monitored by two reliable time-series InSAR techniques. Further study of the subsidence mechanism is necessary to forecast ground subsidence and instruct mining activities.

Vertical shafts play an important role in the safe operation of mines. The stability of vertical shafts has always been a difficult problem in mining engineering, especially with the increasing of mining depth. In order to keep the engineering works stable, it is necessary to make the deformation failure mechanism of vertical shafts clear. This paper describes a case study of the deformation and failure mechanisms of the vertical shaft in Jinchuan No. 2 mining area in Gansu Province, China. Long-term deformation trends and characteristics of the vertical shaft are analyzed through ground movement and GPS monitoring of ground fissures. Then, based on previous research experience and a detailed field investigation, the modes, influencing factors, and mechanisms of deformation failure in the vertical shaft are studied. To further investigate the mechanism of shaft deformation failure and damage process under mining, the Universal Discrete Element Code (UDEC) software with Trigon approach is employed to build the numerical model of the vertical shaft. Through displacement, stress, and damage analysis, the time, location, and cause of vertical shaft failure during mining are explicitly illustrated. The results suggest that the upper and lower parts of the fault are activated in different ways. The damage to the vertical shaft is still developing at a very high rate under mining with filling method. All our results throw light on the nature of deformation and failure of vertical shafts, and several suggestions for the engineering of deep vertical shafts are finally put forward, providing a reference for other engineering.

Mixing calculations have been widely applied to identify sources of groundwater recharge, but these calculations have assumed that the concentrations of end-members are well known. However, the end-members of water remain unclear and are not easily available in practical applications. To better determine end-members and mixing ratios, an end-member mixing analysis combining multivariate statistical methods was used on a large, complex water chemistry dataset collected from the Shashandao gold mine in China. Multivariate statistical methods, including principal component analysis (PCA) and hierarchical cluster analysis (HCA), were applied to determine the specific end-members (these two methods verified each other). On the basis of the identified end-members, a maximum likelihood method was then used to estimate the mixing ratios of the water sources. The combined method proposed in this study can help to identify more accurate end-members and deal with uncertainty in end-member concentrations, and it can also adjust the concentrations until the optimal mixing ratios for the calculation are obtained. This method can be a powerful tool for groundwater management and in predicting water inrush in mining operations.

Gas flow mechanisms and apparent permeability are important factors for predicating gas production in shale reservoirs. In this study, an apparent permeability model for describing gas multiple flow mechanisms in nanopores is developed and incorporated into the COMSOL solver. In addition, a dynamic permeability equation is proposed to analyze the effects of matrix shrinkage and stress sensitivity. The results indicate that pore size enlargement increases gas seepage capacity of a shale reservoir. Compared to conventional reservoirs, the ratio of apparent permeability to Darcy permeability is higher by about 1–2 orders of magnitude in small pores (1–10 nm) and at low pressures (0–5 MPa) due to multiple flow mechanisms. Flow mechanisms mainly include surface diffusion, Knudsen diffusion, and skip flow. Its weight is affected by pore size, reservoir pressure, and temperature, especially pore size ranging from 1 nm to 5 nm and reservoir pressures below 5 MPa. The combined effects of matrix shrinkage and stress sensitivity induce nanopores closure. Therefore, permeability declines about 1 order of magnitude compare to initial apparent permeability. The results also show that permeability should be adjusted during gas production to ensure a better accuracy.