Coal and rock electromagnetic radiation (EMR) measurement plays an essential role in the monitoring and early warning of underground engineering dynamic hazards as a real-time, dynamic, non-contact geophysical monitoring method of coal and rock fissure. The electromagnetic field has obvious directionality; however, the EMR measurement instruments used in underground engineering are scalar rather than vector instruments. Therefore, this paper uses a self-developed three-axis antenna to measure the vector EMR for rock Brazil splitting failure. Study the influence of crack size (D), the distance of measuring point (r) and crack azimuth angles (θ ₀) on the vector characteristics of EMR induced by rock splitting failure. Analyze the vector response mechanism of EMR induced by rock splitting failure, and conduct on-site vector EMR measurements in the Lilou Coal Mine. The study achievements are concluded as follows: the amplitude of vector EMR ( A _s) increases linearly with the increase of crack size (D), decreases with the distance square (r ²) from the measurement point to the crack increases, and increases and then decrease with the increase of angles (θ ₀) between the sample direction and the initial fixed position, showing arching changes; The direction of vector EMR ( A _s) is mainly affected by θ ₀ impact. The results of experiments are consistent with that of theoretical analysis. The field measurement results show that the stress concentration area and its orientation of the roadway could be measured using the three-axis vector EMR instrument we researched and developed.

The growing burial depth increases the potential risk of ground stress-induced coal and rock dynamic disasters in coal mining. This study attempts to use microseismic and computed tomography (MS-CT) to quantitatively characterize the stress field in coal seam areas. A comprehensive approach encompassing laboratory experiments, numerical simulations, and field investigations was employed to accomplish this objective. The experimental findings suggest a power function relationship between the wave velocity of coal and stress. The model relating wave velocity ratio to stress proves more suitable for research on stress field quantification. This model captures the positive correlation between wave velocity and stress changes and eliminates the influence of sample differences through normalization, rendering the fitting parameter b applicable in the field. This paper takes the No.22 coal seam of Jinjia coal mine as the research object; MS-CT technology was used to generate the cloud map of wave velocity field distribution in the 11224 working face and combined with the experimentally established relational model to relate the wave velocity ratio to the stress and calculate the results of quantitative characterization of the regional stress. At the same time, a detailed three-dimensional numerical model was established and simulated to obtain the stress distribution in the 11224 working face area. Comparison of the simulated stress field results with the quantitative results of MS-CT shows that the general trend is basically the same, and the stress is higher in the area with greater burial depth. The area affected by the overlying goaf has lower stress in the coal seam. The maximum error value of the two is within ± 2 MPa, and the correlation coefficient is 0.79, indicating a strong correlation. Therefore, the MS-CT technique combined with the experimental wave velocity-stress coupling relationship model can determine the stress field distribution and realize the quantitative stress characterization. This provides a crucial foundation for analyzing the mechanical model of coal seam instability and calculating the judgment index of coal-rock dynamic disaster excitation.

The accurate monitoring and early warning of coal and rock dynamic disasters become challenging in complex geological environments. Mostly, the signal information contains interferences, which misguides the technician, and thus leads to inaccurate monitoring results. To reduce the influence of interference signals, the synchronous response of the acoustic emission (AE) and electromagnetic emission (EME) signals before the failure of coal specimens during uniaxial loading was investigated in this study. Additionally, the coupling relationship between M value, AE energy/AE ringing count per unit time, and the damage of coal is established, and the early warning index of AE and EME (R value) was computed and verified through the field investigations. The results show that a strong synchronization of the acoustoelectric signals occurs only after the specimen enters the strain strengthening area. The analysis of the obtained results showed that the M value of the AE-EME synchronous response signal represents a strong degree of damage occurring in the coal body, however, this is still subject to false alarms. In contrast, the analysis of the R value accurately helped in determining the damage evaluation, thus, it can be regarded as one of the precursors of the imminent failure of coal. With R > 1, the specimen is closed to the failure state, thereby dangerous regions are identified with a dense concentration of R > 1 events. The obtained R value index through on-site AE and EME monitoring corresponds closely with the stress distribution cloud map of the roadway. It is inferred that the anti-interference ability and the reliability of the R value index are stronger than the routine early warning indicators of the single-AE or EME energy.

The presence of a high concentration of Cl⁻ in saltwater will erode the structure and facilities, reducing the stability and service life of the underground oil storage cavern. In order to reduce the risk of seawater intrusion, this paper studies the risk and prevention technology of seawater intrusion based on a case study of a coastal and large-span underground oil storage cavern. A refined three-dimensional hydrogeological model that comprehensively considers permeability coefficient partitions, faults, and fractured zones are constructed. The seepage fields and seawater intrusion risks of the reservoir site in its natural state, during construction, and during operation are examined, respectively. The study quantifies the water inflow and optimizes the seawater intrusion prevention technology. The results indicate that there is no risk of seawater incursion into the cavern under natural conditions. The water inflows after excavating the top, middle, and bottom sections of the main cavern are predicted to be 6797 m³/day, 6895 m³/day, and 6767 m³/day, respectively. During the excavation period, the water supply from the water curtain system is lower than the water inflow of the cavern, providing the maximum water curtain injection of 6039 m³/day. The water level in the reservoir area decreased obviously in the excavation period, but the water flow direction is from the cavern to the sea. Additionally, the concentration of Cl⁻ in the cavern area is less than 7 mol/m³; hereby, there are no seawater intrusion risks. When only the horizontal water curtain system is deployed, seawater intrusion occurs after 18 years of cavern operation. The concentration of Cl⁻ in the southeast of the cavern group exceeds 50 mol/m³ in 50 years, reaching moderate corrosion and serious seawater intrusion. In addition to the horizontal curtain above the cavern, a vertical water curtain system could be added on the southeast side, with a borehole spacing of 10 m and extending to 30 m below the cavern group. This scheme can effectively reduce seawater intrusion risk and extend the service life of the cavern. The findings of this research can be applied as guidelines for underground oil storage caverns in coastal areas to tackle seawater intrusion problems.

Accurate identification of coal and gas outburst (CGO) risk zones in deep coal mining remains a critical challenge for disaster prevention. CGO formation is governed by the coupled effects of stress redistribution, coal–gas occurrence conditions, and mining‐induced disturbances. To address this problem, a quantitative stress–energy analysis model is developed for the region ahead of the working face, in which these governing factors are explicitly quantified as model input parameters. The coupled stress–energy evolution of the coal–rock system is systematically investigated, thereby elucidating the mechanical mechanisms underlying CGO risk formation. The results show that the peak stress ahead of the working face is positively correlated with elastic‐zone stress anomalies, burial depth, coal compressive strength, and gas pressure, while exhibiting no clear correlation with coal seam thickness. In contrast, the plastic zone length is positively correlated with elastic‐zone stress anomalies, coal seam thickness, burial depth, and gas pressure, and negatively correlated with coal compressive strength. Multi‐factor coupling significantly modifies peak stress and plastic zone development, resulting in nonlinear energy accumulation and dissipation that directly control CGO risk. Based on these findings, a dynamic and adaptive CGO risk prediction method is developed by introducing an energy‐based indicator R within a unified mechanical–energy framework that integrates stress evolution, coal‐gas occurrence conditions, coal seam geometry, and mining‐induced disturbances. Field validation demonstrates that the proposed method exhibits reliable predictive performance, stable behavior, and meaningful forecasting lead time under complex geological conditions, providing a practical approach for CGO risk prediction in deep coal mining.