Anomalous Body Research Articles

Ant Colony Optimization Inversion Using the L1 Norm in Advanced Tunnel Detection

During the construction of the tunnel, there may be water-bearing anomalous structures such as fault fracture zone. In order to ensure the safety of the tunnel, it is necessary to carry out advanced tunnel detection. The traditional linear inversion method is highly dependent on the initial model in the tunnel resistivity inversion, which makes the inversion results falling into the local optimal optimum rather than the global one. Therefore, an inversion method for tunnel resistivity advanced detection based on ant colony algorithm is proposed in this paper. In order to improve the accuracy of tunnel advanced detection of deep anomalous bodies, an ant colony optimization (ACO) inversion is used by integrating depth weighting into the inversion function. At the same time, in view of the high efficiency and low cost of one-dimension inversion and the advantages of L1 norm in boundary characterization, a one-dimensional ant colony algorithm is adopted in this paper. In order to evaluate the performance of the algorithm, two sets of numerical simulations were carried out. Finally, the application of the actual tunnel water-bearing anomalous structure was carried out in a real example to evaluate the application effect, and it was verified by excavation exposure.

An Analytical Method to Estimate Seabed Topography Only from Vertical Gravitational Gradient

In the present methods to estimate seafloor topography from gravimetric data, some parameters need be computed in advance from the known bathymetric data, which leads some uncertainties in applying the methods. To overcome such uncertainties, an analytical method to estimate the seafloor topography from the vertical gravity gradient (VGG) is introduced in the paper. Based on the expression of VGG generated by a cubic prism, the observation equations for the seabed depth are established firstly. Then, the simulation results show that the observation equations established are solvable. Especially, the piecewise bilinear interpolation is introduced to separate the influence of the far-field anomalous bodies on VGG. In addition, some imitation arithmetic examples are given in order to examine the solvability of the observation equations and estimate the accuracies of their solutions. Finally, an actual seafloor topography located in South China Sea (117.6-118.25°E, 17-17.65°N), is estimated by the method proposed in the paper, and compared with ship depth sounding, the root mean square (RMS) error of bathymetry prediction is 77 m.

Processing and interpretation of full tensor gravity anomalies of Southern Main Ethiopian Rift

The study area is situated in the Southern Main Ethiopian Rift being bounded within the limit of 37o00″0′-38o50′00″E and 5o50′00″-7o00′00″N. It is well known that the complex geological structure of the Main Ethiopian Rift has attracted intense attention so far and numerous geophysical investigations have been performed using potential field data-sets in Central and Northern Main Ethiopian Rift with the exception of the Southern Main Ethiopian Rift which is poorly constrained. Analysis of Full Tensor Gravity anomalies helps in understanding of the nature of shallow subsurface structural features and has a paramount importance in building general understanding of subtle details about subsurface geology of the area.Separation of regional and residual gravity field is performed using upward continuation filtering technique. The residual gravity anomaly caused by local structures and anomalous body delineated four sub-basins with low amplitude response which is in agreement with the vertical gravity gradient anomaly (Gzz) and tilt derivative horizontal (TDX) that clearly outlined and characterize edges of the sub-basins. The sub-basins delineated are the northern and southern Abaya, Chamo and Gelana basins. The tilt angle method which is used to delineate major subsurface structures and determine the source depth results showed that the area was affected by different lineament trending NE-SW, N–S, NNE-SSW, NW-SE and E-W, directional analysis performed indicates that the dominant trend is in agreement with the regional fault orientations. The estimated depth to the top of the lineaments on average varies from 0.9 km to 3.1 km and it is relatively deeper in the basins compared to the surrounding areas giving clues to the amount of sediment infill.

Mineral Prospectivity Prediction via Convolutional Neural Networks Based on Geological Big Data

Today’s era of big data is witnessing a gradual increase in the amount of data, more correlations between data, as well as growth in their spatial dimension. Conventional linear statistical models applied to mineral prospectivity mapping (MPM) perform poorly because of the random and nonlinear nature of metallogenic processes. To overcome this performance degradation, deep learning models have been introduced in 3D MPM. In this study, taking the Huayuan sedimentary Mn deposit in Hunan Province as an example, we construct a 3D digital model of this deposit based on the prospectivity model of the study area. In this approach, 3D predictor layers are converted from the conceptual model and employed in a 3D convolutional neural network (3D CNN). The characteristics of the spatial distribution are extracted by the 3D CNN. Subsequently, we divide the 22 extracted ore-controlling variables into six groups for contrast experiments based on various combinations and further apply the 3D CNN model and weight of evidence (WofE) method on each group. The predictive model is trained on the basis of the coupling correlation between the spatial distributions of the variables and the underground occurrence space of the Mn orebodies, and the correlation between different ore-controlling factors. The analysis of 12 factors indicates that the 3D CNN model performs well in the 3D MPM, achieving a promising accuracy of up to 100% and a loss value below 0.001. A comparison shows that the 3D CNN model outperforms the WofE model in terms of predictive evaluation indexes, namely the success rate and ore-controlling rate. In particular, the 1–12 ore-controlling factors selected in experiment 5 provide a significantly better prediction effect than the other factors. Consequently, we conclude that the Mn deposit in the study area is not only related to the stratum and interlaminar anomalous bodies but also to the spatial distribution of the faults. The experimental results confirm that the proposed 3D CNN is promising for 3D MPM as it eliminates the interference factors.

Integrated geophysical study in the cemetery of Marquis of Haihun

AbstractA group of Han dynasty tombs were found in a small town in central eastern China. It is difficult to infer the underground structures of the cemetery based on surface information. Geophysical methods are nonintrusive technology that can be used in archaeological excavations to provide important underground information. Multiple geophysical methods including total magnetic field (TMF), self‐potential (SP), direct‐current resistivity (DCR) and ground‐penetrating radar (GPR) were used to investigate the structure of ancient tombs. Total magnetic anomaly (TMA) and SP data can be used to obtain the projections of anomalous bodies on earth surface. DCR and GPR data can be used to gauge and further determine the spatial locations and depths of the anomalies. The results of the integrated geophysical interpretation were used to optimize the excavation plans and were verified by the subsequent works, such as coffin chambers, dromoi, ancient building foundations and funeral pit. Integrated geophysical survey can effectively reduce the uncertainly of a single method and obtain the targets more accurately.

Wireline Logs Constraint Borehole-to-Surface Resistivity Inversion Method and Water Injection Monitoring Analysis

Detection of the oil–water encroachment front is of great importance to water injection of oil reservoirs. In borehole-to-surface electrical imaging (BSEI), a high-power direct current is applied into a borehole through a well case and the electric potential on the surface, which is affected by the subsurface electrical change, is measured. However, further accurate interpretation of BSEI data is difficult due to the weak surface response, deep target layer, long inversion time, and uncertainty in unconstrained inversion. Therefore, a new method to enhance the surface response of the anomalous body and a new three-dimensional inversion approach based on the damped least-squares method are proposed. Simulation of the water injection and fracturing process was modeled in three dimensions using the finite difference method and the incomplete Cholesky conjugate gradient method. The inversion approach was applied by using the log data to construct a layered resistivity model and constrain the inversion. The forward modeling results suggest that the electric potential gradient can enhance the response of electrical variations in the target layer and help estimate the water injection direction, depending on the distance of electrical anomalies and the current source. In actual water injection monitoring, the BSEI inversion results suggest that layered resistivity model constrained three-dimensional inversion can improve the precision and accuracy of the resistivity inversion results and outline the water injection channeled to the adjacent wells.

Analysis of IP response characteristics in wells on undulating topography

This paper studies the effect of undulating topography on resistivity method and induced polarization (IP) method between the wells. The 3D forward modeling of borehole resistivity/induced polarization method is realized by abnormal potential algorithm based on unstructured finite-element method (FEM). The algorithm is verified in layered medium and spherical abnormal bodies. We studied the response characteristics of apparent resistivity and apparent polarizability in well-well mode and the situation when the source is at different positions in the well, and analyzed the effects of undulating topography on resistivity and induced polarization. The results show that the apparent polarizability and apparent resistivity response have a great relationship with the depth of the emission source in the well, the relative position of the emission source and the measurement electrode. The undulating topography only affects the measuring electrodes at a short distance, and it has a greater impact on the low-resistance anomalous body.

Three-Dimensional Inversion of Controlled-Source Electromagnetic Data in Fanchang Region, Anhui Province

Fanchang area of Anhui Province is an important link in the middle and lower reaches of the Yangtze River. To study the distribution of rock mass near the surface of the area and the contact relationship between the strata, and to determine the possible ore body space, we carry out a 15km controlled-source electromagnetic(CSEM) survey. The observed data is the electric field amplitude data simulating wide-area electromagnetic. For the single-section electric field amplitude data of controlled source, because of the lack of magnetic field data, the impedance data needed for audio geomagnetic inversion cannot be formed. This paper uses the limited memory quasi-Newton(L-BFGS) method to perform a three-dimensional inversion with the source directly. The theoretical model test results show that the inversion method can recover the underground resistivity structure and obtain better anomalous body resolution. The three-dimensional inversion of the CSEM data in Fanchang area shows that we could get the best inversion results when the grid size is about 1/3~1/2 of the dot pitch, the background resistivity is 100 Ω·m, and the error level is 5%. The inversion result of the full-section data, including two sources, shows that the south and north end of the profile is high-resistivity, and the intermediate resistivity is low. However, in the middle of the profile, the resistivity is significantly higher than the two sides. Combined with geological data, this change reflects the distribution of strata/rock masses on the surface of the work area and the contact relationship between them. This consistency verifies the feasibility and necessity of three-dimensional source inversion for the CSEM field amplitude |Ex| data of multi-source and single profile. The underground three-dimensional resistivity structure can be effectively obtained by using the L-BFGS method with the controlled source.

Three-component response of transient electromagnetic method

Based on the three-component TEM forward simulation, through varying the dip angle and strike of underground target, changing overburden conditions, three-component response characteristics were analyzed. According to the three-component responses, the geometric features (the position, size, and occurrence) of anomalous body can be determined. The extreme points of the X and Y component response curves reflect the boundary of the tabular body; the zero-crossing point of the curves corresponds to the center of the tabular body. According to the range size of X and Y component curves, and the position of extreme points and zero-crossing points, the dip angle and extension direction and the center of the tabular body can be determined.

Firefly Algorithm for Transient Electromagnetic Inversion

Transient electromagnetic (TEM) method is widely used in regional mineral resources surveys, environmental engineering geological surveys and shallow surface geophysical exploration, and so on. However, interpretation and inversion of TEM data is a complicated process. The traditional algorithm of TEM inversion employs the “smoke ring” fast imaging method, which can only reflect the approximate morphology of the stratigraphic model, and the inversion accuracy is low. Therefore, this method cannot meet the requirements of high-precision inversion. In this article, we present the firefly algorithm (FA) technology for TEM inversion. First of all, the response of the rectangular loop source TEM based on electric dipole integration was calculated and compared with the analytical solution results of the rectangular loop source and the accuracy of the algorithm was verified. Then, a layered medium model was established. The FA technology and “smoke ring” fast imaging method were used to perform inversion calculation, and the influence of random noise on the accuracy of the FA algorithm was analyzed. The results show that the FA has a high degree of fitting to the model, good anti-noise property, and fast search speed. Next, to illustrate the application effect of the FA algorithm in pseudo 2-D inversion, the 2-D model was established. The results show that the FA algorithm can reflect the distribution of the anomalous body more accurately, especially for the low-resistance anomalous body. Finally, we examined the effectiveness of the FA for TEM data processing by inverting survey data and comparing the results with those from the “smoke ring” fast imaging and particle swarm optimization (PSO) algorithms. The research works provide new methods and techniques for TEM data processing.

Research Note: Recovering sparse models in 3D potential‐field inversion without bound dependence or staircasing problems using a mixed Lp norm regularization

ABSTRACTSparse inversions have proven to be useful for interpreting potential‐field data because the recovered models are characterized by sharp boundaries, compact features and elevated values, compared with conventional smoothness‐based inversion results. However, several open problems remain to be addressed, including the bound dependence and staircasing problems. The former results in recovered anomalous values being close to the upper bound, while the latter leads to recovered anomalous bodies with either horizontal or vertical boundaries. We have developed a mixed Lp norm regularization strategy to address these two problems. Inversion results based on two synthetic examples confirm the validity of our approach.

Giant Quasi-Ring Mantle Structure in the African–Arabian Junction: Results Derived from the Geological–Geophysical Data Integration

The tectonic–geodynamic characteristics of the North African–Arabian region are complicated by the interaction of numerous factors. To study this interaction, we primarily used satellite gravimetric data (retracked to the Earth’s surface), which has been acknowledged as a powerful tool for tectonic–geodynamic zoning. The applied polynomial averaging of gravity data indicated the presence of a giant, deep quasi-ring structure in the Eastern Mediterranean, the center of which is located under the island of Cyprus. Simultaneously, the geometrical center of the revealed structure coincides with the Earth’s critical latitude of 35°. A quantitative analysis of the obtained gravitational anomaly made it possible to estimate the depth of the upper edge of the anomalous body as 1650‒1700 km. The GPS vector map coinciding with the gravitational trend indicates counterclockwise rotation of this structure. A review of paleomagnetic data on the projection of the discovered structure into the Earth’s surface also confirms its counterclockwise rotation. Analysis of the geoid anomalies map and seismic tomography data commonly prove the presence of this deep anomaly. The structural and geodynamic characteristics of the region and paleobiogeographic data are consistent with the proposed physical–geological model. Comprehensive analysis of petrological, mineralogical, and tectonic data suggests a relationship between the discovered deep structure and near-surface processes. The deep structure also sheds light on specific anomalous effects in the upper layer of the crust, including the high-intensity Cyprus gravitational anomaly, counterclockwise rotation of the Mesozoic terrane belt, configuration of the Sinai Plate, and asymmetry of sedimentary basins along continental faults.

Nonlinear Inversion for Complex Resistivity Method Based on QPSO-BP Algorithm

The significant advantage of the complex resistivity method is to reflect the abnormal body through multi-parameters, but its inversion parameters are more than the resistivity tomography method. Therefore, how to effectively invert these spectral parameters has become the focused area of the complex resistivity inversion. An optimized BP neural network (BPNN) approach based on Quantum Particle Swarm Optimization (QPSO) algorithm was presented, which was able to improve global search ability for complex resistivity multi-parameter nonlinear inversion. In the proposed method, the nonlinear weight adjustment strategy and mutation operator were used to enhance the optimization ability of QPSO algorithm. Implementation of proposed QPSO-BPNN was given, the network had 56 hidden neurons in two hidden layers (the first hidden layer has 46 neurons and the second hidden layer has 10 neurons) and it was trained on 48 datasets and tested on another 5 synthetic datasets. The training and test results show that BP neural network optimized by the QPSO algorithm performs better than the BP neural network without initial optimization on the inversion training and test models, and the mean square error distribution is better. At the same time, a double polarized anomalous bodies model was also used to verify the feasibility and effectiveness of the proposed method, the inversion results show that the QPSO-BP algorithm inversion clearly characterizes the anomalous boundaries and is closer to the values of the parameters.

Mantle flow: The deep mechanism of large-scale growth in Tibetan Plateau

<p indent="0mm">The origin and growth of the Tibetan Plateau, located in the back lands of the Himalayan orogenic belt, have always been considered controversial. Based on data from previous studies and our own comprehensive research, we found that a giant high-heat flow zone thousands of kilometres long developed, spanning different tectonic units of the Qinghai-Tibet Plateau, encompassing the Kunlun, Qiangtang, Mangkang-Dali and Honghe-Ailao Mountain ranges. All these tectonic units show a tendency to have migrated from the inner plateau towards the northeast edge. Several rock groups are distributed along this giant high-heat flow zone in a continuous pattern: The potassic mafic rock-lamprophyre group (42–32 Ma) and potassic alkaline rock-carbonate rock (27–7 Ma) from partial melting of lithosphere and mantle, the ocean island basalt (16–1 Ma) from decompression melting of the asthenosphere, and the potassic feldspathic rock (40–0.3 Ma) from the melting of the middle-lower crust. The high temperature deep metamorphic zone, characterized by granulite facies metamorphism in the peak period, was accompanied by a large strike-slip fault zone (40–17 Ma). The metamorphic temperatures of the lower crust granulite xenoliths rose to <sc>800°C.</sc> However, the mantle peridotite xenoliths show characteristics of vertical mantle flow. The six large low-speed anomalous bodies revealed by geophysical exploration are clustered, equidistant, and intermittently distributed. Our research proposes that the Indian continental lithospheric-mantle subduction triggered the Asian continental asthenosphere surge, which caused vertical upwelling along a number of mantle channels in the posterior continental region, thermally corroding and engulfing the mantle-lithosphere and reaching as far as the bottom of the crust. These “mantle flow channels” came from depths around <sc>400 km.</sc> They began forming after the late (hard) collision 40 Ma, and not only provided deep heat to sustain the Tibetan Plateau uplift but also prepared new mantle source material for the plateau’s crustal growth. At the same time, this high-heat flow zone caused the plastic and lateral flow of the middle-lower crust, driving the lateral growth of the Tibetan Plateau to the northeast.

Processing of Body-Induced Thermal Signatures for Physical Distancing and Temperature Screening

Massive and unobtrusive screening of people in public environments is becoming a critical task to guarantee safety in congested shared spaces, as well as to support early non-invasive diagnosis and response to disease outbreaks. Among various sensors and Internet of Things (IoT) technologies, thermal vision systems, based on low-cost infrared (IR) array sensors, allow to track thermal signatures induced by moving people. Unlike contact tracing applications that exploit short-range communications, IR-based sensing systems are passive, as they do not need the cooperation of the subject(s) and do not pose a threat to user privacy. The paper develops a signal processing framework that enables the joint analysis of subject mobility while automating the temperature screening process. The system consists of IR-based sensors that monitor both subject motions and health status through temperature measurements. Sensors are networked via wireless IoT tools and are deployed according to different configurations (wall- or ceiling-mounted setups). The system targets the joint passive localization of subjects by tracking their mutual distance and direction of arrival, in addition to the detection of anomalous body temperatures for subjects close to the IR sensors. Focusing on Bayesian methods, the paper also addresses best practices and relevant implementation challenges using on field measurements. The proposed framework is privacy-neutral, it can be employed in public and private services for healthcare, smart living and shared spaces scenarios without any privacy concerns. Different configurations are also considered targeting both industrial, smart space and living environments.

Time-Domain Electromagnetic Fractional Anomalous Diffusion Over a Rough Medium

The theory of magnetic-source electromagnetic anomalous diffusion is developed in this article. As the geological medium is spatially rough, the late-time tail phenomenon can be explained as a multiscale electromagnetic anomalous diffusion, which is a union of fractional subdiffusion and regular diffusion. The roughness parameter β and weighting parameter W are introduced into the generalized electrical conductivity to indicate the roughness level and ratio. The characteristics and superiority of the improved generalized electrical conductivity are analyzed in the time domain. A 3-D modeling method is proposed based on the fractional finite-difference time-domain method. The introduced Caputo fractional derivative in the time domain is calculated by the Alikhanov superconvergent approximation method, so that the stability of the solution is improved. Several half-space models are designed to verify the 3-D modeling efficiency. It turns out that the improved generalized electrical conductivity can model the electromagnetic late-time tail efficiently, which is characterized by responses that coincide with the classical attenuation law at earlier times and the departure at later times. Moreover, this approach is also applied to anomalous models with 3-D bodies; the results indicate that the proposed method can recognize 3-D anomalous bodies efficiently. The improved method can model the complex electromagnetic propagation in the rough geologic medium more accurately, providing a theoretical basis for multiscale and refined detection.

Mixed Spectral Element Method for Electromagnetic Secondary Fields in Stratified Inhomogeneous Anisotropic Media

The spectral element method (SEM) is widely used for analyzing high frequency electromagnetic wave propagation and scattering in complex structures. At low frequencies, however, the primary (direct) fields are usually much larger than the secondary fields caused by scattering, thus making it much more difficult to accurately simulate the secondary (scattered) fields because of the source singularity in the primary fields. To more effectively and accurately simulate the low-frequency secondary fields in subsurface structures, in this work the vector Helmholtz equation for the scattered fields is used to directly obtain the secondary field data in inhomogeneous anisotropic media. The computational method for the secondary electromagnetic fields is based on the mixed spectral element method (mixed SEM) for anisotropic objects in a layered anisotropic background medium. The electromagnetic field is separated into the background fields that are evaluated analytically using the dyadic Green's functions (DGFs) of a layered uniaxially anisotropic medium, and the secondary fields caused by anomalous bodies with arbitrary shapes are numerically computed by the mixed SEM. This avoids the source singularity, and allows the transmitters to be located outside the computational domain. By enforcing Gauss' law as the constraint condition, the mixed SEM efficiently eliminates the low frequency breakdown problem. Numerical results verify the proposed method over the traditional SEM in low-frequency scattering from objects in subsurface layered anisotropic media.

DELINEATION OF FAULTS AND CAVITIES USING GRAVITY TECHNIQUES: AN IMPLICATION FOR ROAD CONSTRUCTION, SOUTH-SOUTH NIGERIA

This study was carried out using five digitized aerogravity data to delineate near-surface structural faults, cavities, low-density zones and estimate the mass balance unit in foundations. Qualitative and quantitative analysis were performed in order to examines the depths to anomalous bodies, density/mass and stratigraphic features such as faults and cavities. The techniques employed were: Source parameter imaging (SPI), 3D Euler deconvolution, forward and inverse modeling. The results of the SPI shallow values range from -5.62 to -53.74 m and deep values range from 3.33 to 120 m. The 3D Euler deconvolution results range from -1892.2 to -1278.3 m for obscure and -12264 to 644.6 m for superficial formations. The forward and inverse modeling result shows the values of depth ranging from 2.5 to 4.8 km, density/mass range from (0.7 to 2.4) x 10-3 kg/m3 and (27 to 133) x 1010 kg of three profiles which is the parameter contrast of the gravity surveys. This shows sequential depths and density/mass contrast between the body of interest and the surrounding material which depicts the presents of faults, sedimentary basins and rock bearing minerals of shale/marble which comprises of air, water and sediment-filled formations. The information from this study has revealed the true nature of the subsurface and this will serve as a guide during road construction.

Review of variability of radiogenic heat properties of some rock types as a basis for geothermal characterization in Nigeria

The southwestern part of Nigeria is one of the three known regions in Nigeria with geothermal prospect. It is characterized by distinctly different thermal state and surface thermal manifestations. Although a number of geophysical explorations have been undertaken, but studies on fundamental geothermal theory remain scarce, including a lack of high-quality heat flow determinations and thermal structure studies. Heat production and heat flow properties play a very critical role in the study of thermal structure in a region. In this report, heat production and heat flow data of rock samples from published studies from some localities in Nigeria was compiled. To optimize this data, the rock-type denominations from the original studies was classified. This was used to characterize the thermal structure of the areas for possible geothermal exploration and radiogenic heat production distribution for the different rock types in the region. This gave some useful guidelines to lithospheric thermal modeling. From the heat production data, there is a wide range in values with igneous rocks having a maximum 11.17 µWm-3 and the metamorphic rocks having 131.37 µWm-3 as maximum value. The metamorphic rocks have higher values than the igneous rocks while the heat flow compiled for the country area has a minimum of 29 mWm-2 and a maximum of 130 mWm-2 with a mean value of 80 mWm-2. The high heat flow observed from data of the southwest zones may suggest the existence of anomalous heat source body in crust due to the radiogenic heat of the solid crust. This work is also an appraisal to direct attention to the lack of thermal properties investigations in the southwestern part of Nigeria and the need to improve on the heat flow database of Nigeria. Hence some parts of the study areas could be further explored for geothermal energy using appropriate geophysical techniques.

Application of electrical resistivity imaging to detection of hidden geological structures in a single roadway

Abstract Locating concealed geological structures in coal seams on both sides of a coal mine excavation roadway is of vital importance for safe production. Conventional electrical resistivity imaging methods mostly arrange observation systems on the roadway roof and floor, so they are inevitably deficient when it comes to detecting concealed geological structures in coal seams. According to the electric field distribution characteristics of artificial field sources for electrical resistivity imaging methods and utilizing the shielding of current by roadway cavities, this paper proposes the parallel coal seam detection method that arranges observation systems in coal seams on the roadway side to detect concealed geological structures in coal seams. On the basis of introducing the principles of consequent detection methods, this paper investigates the influence of roadway cavities on observation results and offers a method of correcting the influence of roadway cavities. In view of the geoelectric characteristics of typical concealed geological structures in working faces, this paper establishes numerical models to verify the feasibility of the parallel coal seam detection method. As indicated by the calculation results, the consequent pole–dipole (A-MN) observation system is the most ideal in terms of dividing the geoelectric interfaces of concealed geological structures in working faces, and its detection effect is influenced significantly by the coal seam thickness and the electric differences between surrounding rock and anomalous bodies. Coal seam resistivity slightly influences detection of the consequent pole–dipole system. According to practical application effects, the parallel coal seam detection method can solve the problem of detecting concealed geological structures in “single-roadway” working faces.