In this paper, transient electromagnetic response excited by ramp-shaped current using a conical source is studied for the sensing of underground environments. The transient time responses from the conical source with either multi-turn coils or a single loop coil are investigated and compared. Although with the same magnetic moment, the turn-off time for conical source is longer than that of the single loop-this is due to the fact that the time of entering different testing stages using a multi-turn coil system is often earlier than that for a single loop system. To correct turn-off error, the conical source type transmitter is used and the one-dimensional modeling of a layered media, in which the calculation of the turn-off response is carried over the entire time range by solving directly an upper limit-variable integral. The turn-off correction method matched the resistivity and the layer thickness, which is critical for the detection of shallow depth problems. Finally, a field example is presented to illustrate the effect of turn-off time on the interpretation of transient sounding data for a conical source system.

The use of the shaft-rate electromagnetic fields generated by moving ships for detection and sensing purposes has several advantages, including effective target recognition and excellent concealment. It offers a solution to the challenges faced in detecting underwater targets. In this study, we propose a method to identify and analyze the shaft-rate electromagnetic field signals using an improved deep learning algorithm and a spectral-direction analysis technique. Initially, we apply variational mode decomposition (VMD) to identify the multi-frequency characteristics of both synthesized and real extremely low-frequency (ELF) electromagnetic signals, creating a reliable sample library for deep learning. Next, we develop an improved deep learning model that combines the Residual Network (ResNet) with the aforementioned sample library to accurately detect the weak narrowband electromagnetic field signals hidden within the noise. Additionally, we use the spectral-direction analysis method to estimate the direction of the ship’s movement. Finally, we validate our proposed method through a synthetic model and a field experiment. The results demonstrate the effectiveness of our approach in identifying the shaft-rate electromagnetic field signals and accurately estimating the direction of moving ships. The developed method shows the potential for accurate sensing and localization of moving ships.

During advancing the working face at Guojiawan Coal Mine, hard rock faults are encountered, which hinder the normal cutting of the shearer. Hydraulic fracturing is applied to pretreat the hard rock materials. Un-directional hydraulic fracturing experiments in transparent gelatin samples are carried out. The influence of the differential stress, the borehole dip angle on the initiation and propagation of un-directional hydraulic fractures (HFs) are investigated. Three field test schemes of hydraulic fracturing are proposed and implemented at the 51207 working face of Guojiawan Coal Mine. Compared with the results of different test schemes, the cutting current ratio of the shearer is reduced by 51.70% and the cutting efficiency is increased by 89.93%. Therefore, the feasibility of hydraulic fracturing to improve the cuttability of the hard rock materials is verified, which provides a theoretical basis and field guidance for hydraulic fracturing pretreatment of the hard rock materials at a coal mining working face.

The small-loop transient electromagnetic method (TEM) refers to a system in which the coil frame length or diameter is less than 2 m. Due to the inductive effects of the multi-turn coils used for both transmission and reception, the induced electromotive force in the measuring coil increases, causing a reduction in the decay rate and an extension of the shutoff time. This results in coupling between the primary and secondary fields in early-time signals, making them difficult to separate and creating a detection blind spot in the shallow subsurface. The opposing coil TEM transmission and reception method can significantly reduce early-time signal distortion caused by coil inductance. However, this approach is constrained by the physical symmetry of the coil dimensions, which makes it challenging to achieve balance in a zero-field space. By performing both forward and reverse measurements at the same location using the opposing coil setup and calculating the difference between the signals, the inductive coupling between coils at the measurement site can theoretically be eliminated. This eliminates the induced potential of the TEM signal, enhancing the induced electromotive force from the formation. As a result, more accurate resistivity values are obtained, detection blind spots are eliminated, and the resolution in shallow TEM exploration is improved. Field experiments were conducted to validate the method on both high-resistivity and low-resistivity anomalies. The results demonstrated that this method effectively identified a high-resistivity corrugated pipe at a depth of 1.2 m and two low-resistivity gas pipelines at a depth of 2 m, thereby essentially eliminating detection blind spots in the shallow subsurface.

Coal spontaneous combustion in arid regions poses severe threats to both ecological security and resource sustainability. Focusing on the detection challenges in Fire Zone No. 1 of the Miaoergou Coalfield, Xinjiang, this study proposes an Integrated Geophysical Collaborative Detection Framework that combines high-precision magnetic surveys, spontaneous potential (SP) measurements, and transient electromagnetic (TEM) methods. This innovative framework effectively overcomes the limitations of traditional single-method detection approaches, enabling the precise delineation of fire zone boundaries and the accurate characterization of spatial dynamics of coal fires. The key findings of the study are as follows: (1) High-magnetic anomalies (with a maximum ΔT of 1886.3 nT) exhibit a strong correlation with magnetite-enriched burnt rocks and dense fracture networks (density > 15 fractures/m), with a correlation coefficient (R²) of 0.89; (2) Negative SP anomalies (with a minimum SP of −38.17 mV) can effectively reflect redox interfaces and water-saturated zones (moisture content > 18%), forming a “positive–negative–positive” annular spatial structure where the boundary gradient exceeds 3 mV/m; (3) TEM measurements identify high-resistivity anomalies (resistivity ρ = 260–320 Ω·m), which correspond to non-waterlogged goaf collapse areas. Spatial integration analysis of the three sets of geophysical data shows an anomaly overlap rate of over 85%, and this result is further validated by borehole data with an error margin of less than 10%. This study demonstrates that multi-parameter geophysical coupling can effectively characterize the thermo-hydro-chemical processes associated with coal fires, thereby providing critical technical support for the accurate identification of fire boundaries and the implementation of disaster mitigation measures in arid regions.