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In the urban environment, the transient electromagnetic method often suffers from severe electromagnetic interference because it employs coils to perceive the electromagnetic field. To address this issue, the DC method employs electrodes to shield the electromagnetic noise in the urban environment. In this paper, a new geophysical resistivity imaging sensing approach based on a DC inversion model is proposed to explore and identify the path of underground water to solve the water disaster problem. A real-world case study is carried out in Xinjiang Region. In order to investigate the underground water conducted path, an electrode network is designed and installed for the buildings of interest to collect the DC electrical current and DC electrical potential data. Then, the proposed method establishes a DC resistivity inversion model based on the forward theory and finite-volume technique to extract the geological information from the collected data and visualize the underground water conducted path. Different from existing popular numerical techniques, such as the finite element and finite difference, the finite-volume technique has clear theoretical explanations to make the obtained geological images understandable. As a result, the underground water path can be directly observed from the geological images calculated by the proposed approach to successfully identify and locate the underground water disaster in real-world applications.

This work aims to remotely monitor the grouting process of double-layered wellbores in deep coal mining area by proposing a new geophysical electrical potential inversion imaging method. The proposed geophysical method is able to evaluate the grouting quality between the inner and outer walls of the wellbores by inverting the geologic electrical potential. Th challenge lies here in the potential inversion is that the thickness of the grouting space is extremely narrow when comparing with the wellbore diameter. To solve this problem, a constrained inversion model is developed to precisely generate the three-dimensional (3D) resistivity distributions of the double-layered wellbore based on the measured geologic electrical potential. A special designed test platform is constructed and experimental tests have been conducted to examine the performance of the proposed geophysical inversion imaging method. The geologic electrical potential of the grouting space is measured and remotely transmitted to the ground processing center; and the constrained inversion model is applied to the geologic signals to calculate the resistivity distributions at different grouting stages and produce the 3D geophysical images. The analysis results suggest that the present geophysical monitoring method can effectively visualize the grouting to evaluate the construction quality of the wellbore.

The seismic signals collected underground in coal mines often exhibit complex waveforms accompanied by significant noise interference, leading to a reduction in the accuracy of first arrival time picking of seismic signals and thereby impacting the inversion and interpretation of seismic data. In response to the low signal-to-noise ratio seismic signals collected in complex interference environments, a method for seismic noise suppression and first arrival extraction based on the Variational Mode Decomposition (VMD) and the Genetic Algorithm-optimized Support Vector Machine (GA-SVM) is proposed to enhance the quality of seismic signals under complex noise conditions in coal mines. The approach employs the Variational Mode Decomposition for adaptive decomposition of the noisy seismic signals, yielding several Variational Mode Components (IMF). The feature extraction is applied to the IMFs obtained from VMD decomposition, utilizing the extracted signal features as the basis for discerning signal validity. Genetic Algorithm is utilized to optimize the Support Vector Machine model, obtaining the optimal penalty factor (c) and kernel function parameter (g). The optimized SVM model is then employed for the validity discrimination of the IMF components, reconstructing them into high signal-to-noise ratio signals. By applying the noise suppression algorithm to artificially noised seismic signals, the common types of noise encountered in coal mines are effectively suppressed, validating the feasibility of the algorithm. Noise suppression processing is applied to the seismic records obtained from mine roadways, successfully mitigating interference noise in the data and significantly improving the signal-to-noise ratio of the seismic records, thereby enhancing the accuracy of first arrival time picking. The results indicate that the seismic noise suppression and first arrival extraction method based on the VMD and GA-SVM can effectively separate and extract valid signals from noisy seismic records, improving first arrival time picking accuracy. This approach demonstrates a significant potential for its application in complex interference conditions in mines, which is of significance for the seismic exploration in the mining environments with complex interference conditions.

With the increase of the depth, mining intensity and area of coal resource, the mining disturbances in the mining face can easily induce mine water inrush accidents, seriously threatening the safe mining of coal resources in China. Mine water disasters are mainly caused by the joint action of rock mass rupture and mine water seepage. The research results show that the parameters such as the longitudinal and transverse wave time, amplitude, frequency, and other microseismic signal parameters can effectively characterize the fracture location and intensity, as well as the source mechanism of rock mass. The parameters such as resistivity, excitation current and self-potential in geoelectric field signals can effectively characterize rock mass seepage evolution process. The characteristics of microseismic field indicate the formation of permeable channels, while the characteristics of geoelectric field indicate groundwater seepage. Therefore, the coupling of microseismic and electrical method has the function of monitoring and early warning for the development process of mine water hazards, which can accurately capture three elements of water hazards including water inrush channel, water source location and seepage process formed in the process of mining failure. It reduces the multiple solutions of a single geophysical method, and improves the monitoring accuracy of water disaster, which is of great significance to the prevention and control of water in coal mines. At present, the microseismic and electrical coupling monitoring technology has begun to be applied in the real-time dynamic monitoring of water hazards in coal mines. Breaking through the limitations of traditional microseismic and electrical data collected independently, the research group has developed the first coal-certified microseismic and electrical coupling parallel monitoring system. With the microseismic field and geoelectric field parallel acquisition base station as the core, this system integrates the passive source micrvoseismic wave field and active and passive geoelectric field. By connecting the mine Internet of Things, the acquisition control, transmission and cloud storage of the remote data are realized. Its integrated network server host can connect multiple acquisition base stations, so as to realize the optimal arrangement of the multi-field observation system in the limited space of the underground and borehole with the separation of microseismic sensor, current electrode and potential electrode while parallel acquisition. It can obtain the spatial and temporal cloud map of microseismic event density and energy level distribution, resistivity distribution and self-potential distribution to monitor and predict the three elements of water hazards. The microseismic and electrical coupling monitoring technology still needs more research particularly in intelligent identification and location of microseismic events, three-dimensional resistivity inversion of geoelectric field and self-potential seepage inversion. Combined with the microseismic and electrical data sets of parallel monitoring, the joint inversion of microseismic and electrical data and intelligent monitoring and early warning method need to be further studied. As a new method of active early warning and monitoring of mine water disaster, the microseismic and electrical coupling monitoring technology will play an important role in the construction of intelligent mine in China.

Abstract A concealed geological structure encountered during the excavation of a coal working face could connect the working face to high-pressure water in limestone strata, which can result in a serious or catastrophic water inrush accident. However, existing geophysical detection methods used to ensure the geological safety of working faces cannot detect small geological anomalies reliably. Based on the generalized theory of scattered waves, we have developed a novel and superior scattered wave imaging method for the detection at the roadway lateral wall, capable of wave vector extraction and multiwave imaging. In this method, the waves scattered from a geological anomaly can be dynamically and accurately extracted by the polarized filter function during the mapping processes of common scattering point (CSP) gathers. A numerical simulation was performed to study the seismic wave response characteristics of a small collapse column in a coal working face. The P and channel waves of the model were extracted and imaged using the novel imaging method. A field study of three-component seismic detection was performed in the Xuzhuang Coal Mine, demonstrating that the joint imaging of body and channel waves can detect small drop faults invisible to channel wave imaging alone. These results indicate that the proposed method can effectively image anomalous bodies on working faces in complex and noisy mine wavefields using multiwave information, providing a new approach for the reliable and timely detection of hazardous geological features hidden in working faces.

An unsuspected fault in front of a roadway is a key hidden disaster-causing factor that can result in major accidents in coal mines; therefore, the accurate advanced detection of faults is important for the safe coal mining. However, existing seismic advanced detection methods are difficult to execute because of the narrow space limits of roadways. Therefore, on the basis of the generalized theory of scattered waves and the scenes of advanced detections in roadways, we construct a new and superior advanced detection method using scattered waves. In this method, a virtual equivalent survey line perpendicular to the roadway strike is established to reconstruct scattered wave records and a polarization filter function is built to dynamically and accurately extract different types of scattered waves in the target area. An analysis of numerical simulations indicates the following. 1) The true reflection position of a fault in front of a rock roadway is closely related to its dip, and the proposed method can accurately extract and image the scattered multiwaves generated at the true reflection position to identify the inclination of the fault, which can avoid the arc-shaped illusion problem caused by the false reflection signal. 2) Under the condition that the scattered waves at the breakpoint of a broken coal seam are significantly disturbed by the coal seam waveguide effect, the fault inclination of the coal roadway can be determined by the joint imaging and interpretation on the reflected channel wave of the hanging wall breakpoint and the scattered wave of the footwall breakpoint. A field study was performed to verify the effectiveness of the proposed method. The results indicate that this method can effectively identify the position and inclination of faults and provide an effective new means for the accurate detection of faults in front of coal mine roadways.

With the increase in coal mining depth, water hazards in deep, strong karst aquifers have seriously threatened the safety of coal mine production. Dynamic monitoring of floor damage during coal seam mining under complex conditions is of great significance for the prediction of water inrush at the working face and for improving coal mining methods. Based on parallel electrical monitoring technology, a constrained time-lapse resistivity inversion method was adopted to process the electrical data of the working face floor. The background resistivity inversion results were used as an a priori model to act on the inversion of subsequent monitoring resistivity data, and the subsequent inversion results of resistivity were fed back to the prior model, which greatly eliminated inversion artifacts. Finally, the dynamic change process of the resistivity profile before and after the failure of the bottom floor of the mining face was determined, and the maximum depth of the failure zone of the floor is 25m, which is located above the lower aquifer. The field monitoring data show that compared with the method of directly comparing the differences between consecutive monitoring images, the inversion profiles obtained by the constrained time-lapse resistivity inversion method have clearer differences in the spatial and temporal dimensions. The depth of the water-conducting damage zone of the floor was clarified, and the basic development characteristic of the floor damage zone of the working face was obtained, which has practical application value for ensuring the safe mining of the working face.

In the two-dimensional Cartesian coordinate system, a transient electromagnetic forward algorithm of the magnetic moment in arbitrary direction is developed to simulate the electromagnetic response characteristics of the whole space geoelectric model. The magnetic moment ${\mathbf {M}}_{r}$ in arbitrary transmitting direction is decomposed into ${\mathbf {M}}_{x}$ and ${\mathbf {M}}_{y}$ . The transient electromagnetic fields excited by the magnetic moments ${\mathbf {M}}_{x}$ and ${\mathbf {M}}_{y}$ are forwarded separately, and then synthesized to obtain the electric field excited by the magnetic moment ${\mathbf {M}}_{r}$ . The time domain iteration’s results of the uniform whole space are compared with the analytical solutions to verify the correctness of algorithm. The comparison results show that the algorithm is reliable and can be used for whole space transient electromagnetic simulation in an arbitrary direction. The forward response of the magnetic moment in an arbitrary transmitting direction removes the shortcomings of the traditional two-dimensional whole space transient electromagnetic simulations where the magnetic moment can only be in the horizontal or vertical direction. The program code can be used for the forward response of other two-dimensional whole space geological mining models. It is of great significance to study the two-dimensional transient electromagnetic diffusion characteristics of different geological models by the sector sweeping method.

The deformation and fracturing of coal rock is a crucial part of coal and rock dynamic disasters and is accompanied by variations in the electrical field of the rock. In this study, the self-potential characteristics of coal rock were measured to dynamically monitor the spatiotemporal evolution of coal rock deformation and fracturing. By using an MTS816 rock mechanics test system, an AE acoustic emission system and a self-developed SEMOS-LAB experimental system, synchronous measurements of the self-potential, stress and acoustic emission of anisotropic bituminous coal under uniaxial compression were obtained. The self-potential of anisotropic bituminous coal exhibited a good correspondence with the stress and acoustic emission counts during the damage and fracturing. As the stress gradually increased, the bedding-perpendicular coal samples exhibited a stronger linear relationship with the stress during initial loading than the bedding-parallel samples. The amplitude of the self-potential and stress of the bedding-perpendicular samples were higher than those of the bedding-parallel samples. Anisotropy is an important factor that affects the variation in the self-potential of a rock mass under loading. The results of this study can be applied to evaluate the stress state of coal by measuring its loading-induced electrical potential; thus, this work is important in the field for the monitoring and warning of coal and rock dynamic disasters.

Underground seismic exploration is a technical assurance for the geological transparency of the mining face. However, seismic exploration with explosive seismic source has shortcomings such as acquisition difficulties and serious safety hazards. Besides, dynamic detection of the mining face with explosive source is challenging. To this end, the study proposes a supercritical CO2 source based on the underground seismic geological condition of the roadway. The phase change blasting mechanism of the supercritical source was revealed, and the equivalent energy of the source was calculated. Additionally, a field test was also carried out. The results show that the seismic signals of the CO2 source have clear P-waves, S-waves, and channel waves; the signal excited by the source has strong energy and rich frequency bands; the signal-to-noise ratio of single CO2 source is high; and the attenuation images of transmitted channel wave excited by the source shows high resolution and the result is consistent with field validation data. CO2 source can be used as a new source of underground in-seam seismic exploration and it also helps in reducing the dependence of explosive seismic source. Besides, the study can achieve early warnings of dynamic geological disasters in the working face and has the advantages of high efficiency, safe, low cost, and environmentally friendly. Keywords: Seismic exploration, Seismic source, CO2 source, Spectrum, Transmitted channel wave

Safety of the mine roadway constructions is controlled by geological disasters such as faults, goaves and so on. The advanced prediction has become an in-demand topic, and advanced detection method of the reflected wave is a crucial technology for advanced prediction of geological anomalies. However, due to the influence of the complex near-source seismic wavefield in the coal mine roadway, the result of wavefield separation and migration imaging is not accurate, which lead to the fact that the fine imaging of geological anomaly is difficult. A comparative analysis of wavefield separation method of kinematics and dynamics is carried out in this paper to solve this problem. A factor of principal polarization direction is introduced according to “the orthogonal difference between the propagation direction of P-wave and S-wave and the vibration direction of particle” starting from the real-time polarization analysis from three-component seismic signals. By the factor, a modified function is constructed and integrated into pre-stack diffraction migration, which put forward the polarization migration method that incorporates wavefield separation with migration imaging. The results of physical simulation and field survey in Xiangyuan coal mine in western China are as follows: The fine imaging by using advanced detection of the reflected waves in underground coal mine can be achieved by using polarization migration in linear observation system and the polarization migration has the effect of enhancing the spatial resolution.

Small fault ahead of the tunnel face in coal roadway is the important hidden hazard factor of coal and gas outburst accidents. The study of small fault prediction has important practical significance, which is the urgent demand of coal mine safety production. The diffraction of breakpoint can be used to identify the fault. However, unlike surface seismic exploration, the diffraction is with approximately horizontal incidence when the advanced detection is carried out in the roadway. The common advanced detection system is mainly as the reference of traffic tunnel, without considering the influence of low-velocity coal seam. Considering the influence of an acoustic wave of the roadway cavity and channel wave of the coal seam, the advanced detection model of small fault ahead of tunnel face is established. Diffraction advanced observation system in which sources located in front of tunnel face is constructed, and the numerical calculation of the high-order staggered-grid finite difference is carried out. The simulation results show that: Compared with the data collected by reflection observation system, in seismic records acquired by diffraction observation system, the suppression effect of acoustic wave is appeared. The diffracted P-wave of the breakpoint of component X is clear with strong energy and short-wave group. Multiple diffractions of the breakpoint are not found, but the multiple diffraction of tunnel face endpoint is obvious. The difference between breakpoint diffraction and multiple diffractions of the endpoint is clear, and diffracted P-wave of the breakpoint is easy to identify. The multiple reflected channel wave between the fault and the tunnel face is very obvious, and the reflected channel wave of small fault is so hard to identify. Migration results show that the imaging resolution of diffracted P-wave of small fault is higher than the reflected channel wave, and breakpoint location of imaging is consistent with the actual model.

With the continuous improvement of precision requirements for borehole geophysical exploration, the application of transient electromagnetic method (from now on referred to as TEM) in a borehole has become a hot spot. The conventional borehole TEM can only determine the longitudinal depth of the geological anomaly, the radial azimuth and depth cannot be resolved. A double-transmitting and sextuple-receiving borehole TEM is proposed, through which the radial anomaly is excited by the electromagnetic field generated by the double-emitting loops, and the azimuth and depth of the anomaly will be identified by the difference characteristics of the six receiving loops signals. In this paper, the response equations of the transmitting-receiving mode of double-transmitting and sextuple-receiving borehole TEM are deduced, and the response characteristics of the induction segment and the attenuation segment of the receiving loops are obtained based on the response equations under ramp function turn-off condition, providing the basis for theoretical analysis. Due to the negative value of the double-transmitting and sextuple-receiving transient electromagnetic response signals, a negative transformation algorithm under the double logarithmic coordinate system is proposed to provide the essential method for the analysis of two kinds of physical simulation experimental data of the radial azimuth and radial depth detection of the anomaly. The results show that the double-transmitting and sextuple-receiving borehole TEM has decent resolution ability in detecting the radial azimuth of the anomaly, and the effective resolution is 30°. The geometric difference among induced voltages of different measuring points can be used to evaluate the radial depth of the anomaly qualitatively. It is expected that the double-transmitting and sextuple-receiving borehole TEM can provide technical guidance for little borehole geophysical exploration in the fields of oil, natural gas, coal and basic engineering construction.

Mine water is a menace to coal mining. Mine water quantity is generally detected by drilling in the coal mine roadway, and the disadvantage is high workload and low efficiency. Therefore, transient electromagnetic method (TEM) was proposed, and TEM data was processed to detect the water yield property of a targeted layer in coal mine. Through a mine-oriented 3D Transient Electromagnetic Method observing system, the signal of induced voltage is obtainable. Transient Electromagnetic Method 3D data volume can be calculated through the calculation of all-time resistivity and time-depth conversion. After an appropriate apparent resistivity value is set, the spatial distribution range of an aquifer can be determined. Then, with water-filling coefficient of the aquifer, its water quantity can be estimated. The water yield property detection results in the No.4 coal seam goaf of the No.80101 workface in Jude Mine of Shanxi, China, demonstrates that the apparent resistivity of this goaf is less than 3 Ω.m, and the projection area of low-resistivity anomaly zone is 22,383 m2. By using the formula Q=KMS, we can estimate that the water volume is 33,574 m3. Three boreholes have been constructed for the later dredging and drainage project, which results in a total water yield of 33,089 m3. The error percentage of the predicted water quantity is less than 1.5%. It can thus be concluded that it is feasible to predict aquifer water content with TEM data.

To research the elasticity of gas-bearing coal fluid-solid two-phase medium with seismic exploration method is critical to the prevention of gas disasters. To investigate the elasticity, the ultrasonic elastic test of anthracite samples under different gas pressures was carried out and the ultrasonic velocity and anisotropy of the samples were analyzed in this study. The results show that the velocities (P- and S-waves) decrease in turn in the strike, dip, and vertical directions. However, a negative linear correlation is proved to exist between ultrasonic velocity and gas pressure. With the increase of gas pressure, the anisotropy degree of both the P-wave and the S-wave of the samples decreases but the declining degree of the P-wave is greater than that of the S-wave. In addition, the decrease in velocity and the anisotropy degree of the P-wave is greater than that of the S-wave, indicating that the P-wave is more sensitive to gas pressure changes in terms of velocity and its anisotropy degree.

Uniaxial cyclic loading-unloading compression experiments with schemes of six loading rates and six unloading rates were carried out on the combined testing platform. Impact of loading and unloading rates on rock AE characteristics was revealed. Results show that increasing loading and unloading rates resulted in decreasing total AE rings in the entire rock deformation and failure process. Increasing loading rate decreased the AE rings at loading stages, and increasing unloading rate decreased the AE rings at unloading stages in the same cycle. Total AE counts had a negative linear relationship to the loading and unloading rates. The loading stage was the active period of the AE phenomena, and impacts of the loading rate on the AE characteristics were more apparent. Especially when the loading rate was greater than 2.0 kN/s, brittle failure of rock specimens became noticeable. After the cyclic load reached the uniaxial compressive strength of 1/3∼1/2 times, the rock Felicity effect became more obvious. With the increase of the loading rate, the Felicity ratio decreased in the elastic stage and increased a little in the plastic stage, whereas with the increase of the unloading rate, the Felicity ratio decreased gradually in the elastic stage and remained almost the same in the plastic stage.

Based on the energy attenuation characteristics of residual wave in deep rock, a method was developed to determine the microseismic focus energy. Differential energy loss in infinitesimal spreading distance is logically deduced, upon which energy attenuation equation was established. With a logarithmic transformation, a linear relation of the residual seismic energy with distance is formulated. Its intercept was used to determine the microseismic focus energy. The result is compared with that determined by the energy density method. The reliability of the determined focus energy and the impact of the built-in velocity threshold on the residual wave energy computation are discussed. Meanwhile, the energy absorption coefficient used for representing the absorption characteristics of the rock medium in the mining region under study is also clarified. Key findings show that the microseismic focus energy confirmed by the residual wave attenuation is reliable. The result’s accuracy is quite high, especially for the events in deep rock with great homogeneity. The developed focus energy computation method is closely dependent on the integrity of waveform, accuracy of repositioning, and reliability of effective components extraction. The new method has been shown to be effective and practical.

To reduce noise components from original microseismic waves, a comprehensive fine signal processing approach using the integrated decomposition analysis of the wave duration, frequency spectrum, and wavelet coefficient domain was developed and implemented. Distribution regularities of the wave component and redundant noise on the frequency spectrum and the wavelet coefficient domain were first expounded. The frequency threshold and wavelet coefficient threshold were determined for the identification and extraction of the effective wave component. The frequency components between the reconstructed microseismic wave and the original measuring signal were compared. The noise elimination effect via the scale-changed domain decomposition was evaluated. Interaction between the frequency threshold and the wavelet coefficient threshold in the time domain was discussed. The findings reveal that tri-domain decomposition analysis achieves the precise identification and extraction of the effective microseismic wave component and improves the reliability of waves by eliminating the redundant noise. The frequency threshold and the wavelet coefficient threshold on a specific time window are two critical parameters that determine the degree of precision for the identification of the extracted wave component. This research involves development of the proposed integrated domain decomposition method and provides a diverse view on the fine processing of the microseismic signal.

To explore the influence of confining pressure on the energy evolution characteristics of loaded rocks, triaxial cyclic loading-unloading experiments on sandstones were carried out under 6 kinds of confining pressures using the axial loading and circumferential deforming control modes. Total energy density, elastic energy density, and dissipated energy density absorbed by rock specimens under different confining pressures were obtained. The confining pressure effect of the evolution process and distribution law in energy accumulation and dissipation was analyzed. Energy conversion mechanism from rock deformation to failure was revealed, and energy conversion equations in different stress-strain stages were established. The method of representing the rock energy accumulation, dissipation, and release behaviors by energy storage limit density, maximum dissipated energy density, and residual elastic energy density was established. The rock showed that, with the increase of confining pressure, the characteristic energy density of rock increased in the power exponent form, and the energy storage limit density increased faster than the maximum dissipated energy density. The greater the confining pressure was, the greater the proportion of elastic energy before peak was. It is indicated that the confining pressure increased the energy inputting intensity, improved the energy accumulating efficiency, and inhibited the energy releasing degree.

As essential equipment in rotating machinery, the fault diagnosis technology of rolling bearings has achieved great success. However, it still suffers from limitations in terms of generalization and noise resistance performance when operating under complex conditions. To accurately identify the fault types of rolling bearings under different loads and nosy environments, a novel intelligent fault diagnosis method is proposed. Firstly, the utilization of dilated convolution expands the network's receptive field, thereby effectively enhancing the scope of fault extraction. Then, by incorporating the Efficient Channel Attention (ECA) in different convolutional layers, the extracted features are adaptively recognized, highlighting important representation information and improving fault diagnosis performance. Finally, the proposed network is utilized for rolling bearing fault diagnosis under diverse operating and noise conditions, and its efficacy is evaluated on various datasets. The experimental results demonstrate that the proposed method exhibits good generalization performance and strong robustness, compared with other methods. [ABSTRACT FROM AUTHOR]