Transient Electromagnetic Method Research Articles

A new combined transient electromagnetic noise reduction method of VMD-SVD-WTD based on improved dung beetle optimization algorithm with multi-strategy fusion

Abstract The transient electromagnetic method (TEM) is now commonly used in the detection of coal mined-out areas, but it is susceptible to various sources of noise during field site probing, significantly impacting the accuracy of detection. Variational mode decomposition (VMD) has gained widespread adoption for eliminating noise in TEM signals. However, a single VMD may not effectively address both full-band noise and residual Gaussian white noise. To address this limitation, the singular value decomposition (SVD) and wavelet threshold denoising (WTD) are introduced correspondingly. Furthermore, this paper tackles challenges related to parameters selection in VMD and traditional optimization algorithms by proposing the integration of dung beetle optimization (DBO) enhanced with circle chaotic mapping, random walk strategy, and crisscross optimization algorithm (CRCDBO). Consequently, a new combined TEM noise reduction method, VMD-SVD-WTD based on CRCDBO is presented. Through comprehensive simulation tests and comparative analyses, the signal-to-noise ratio of this method is improved by 12.79% compared with VMD and the RMSE is 0.0011, which demonstrate the superiority and effectiveness of VMD-SVD-WTD based on CRCDBO in noise reduction. Meanwhile, this method is applied to an iron ore mine in Shanxi, which can accurately monitor the location of the mined-out area and has good application value.

Application of the opposing-coils transient electromagnetic method combined with ground-penetrating radar for the identification of shallow geohazards: a case study in Xiacun Town, Xinyu City, China

Application of the opposing-coils transient electromagnetic method combined with ground-penetrating radar for the identification of shallow geohazards: a case study in Xiacun Town, Xinyu City, China

Deep Learning Transient Electromagnetic Inversion for Seawater Intrusion

Abstract To enhance the capability of transient electromagnetic method(TEM) in detecting seawater intrusion and delineating the boundaries in coastal areas, we developed a deep learning inversion method for TEM data based on the Swin Transformer model in this study. First many standardized resistivity models were designed and generated to describe t the subsurface resistivity structures associated with seawater intrusion in coastal areas .Then, TEM forward modelling was performed to compute the corresponding TEM responses, thereby constructing a seawater intrusion-oriented training dataset. Then, the robust Swin Transformer model was employed as the backbone network to build a deep learning inversion model, named SITEMNet, to derive a direct nonlinear transformation that maps TEM responses to subsurface resistivity models. The proposed SITEMNet inversion technique was validated using simulated data scenarios and actual field TEM measurements, showing great promise in accurately identifying seawater intrusion interface and geological formations.

Research progress in three-dimensional forward modeling for transient electromagnetic method

Research progress in three-dimensional forward modeling for transient electromagnetic method

Research and application of joint-constrained inversion of transient electromagnetic multivariate parameter

Due to the phenomena of stratigraphic inclination, complex structure, and lateral discontinuity of resistivity or layer thickness in most of the coal seams, the traditional one-dimensional transient electromagnetic inversion method has limitations in interpretation accuracy. In addition, two- and three-dimensional inversion and artificial intelligence inversion have problems of large computation and large sample size, respectively, which limit their application in small- and medium-sized engineering exploration. To improve the inversion effect, this study proposes a method of joint-constrained inversion of transient electromagnetic multivariate parameters. This method achieves the joint constraint inversion of the transient electromagnetic multi-parameter by making full use of the geological data and a priori information to construct the initial model and adding the constraints such as the resistivity, the thickness, and the layer interface of each layer in the inversion objective function, and at the same time, taking into account the spatial correlation of the stratigraphic structure between the neighboring measurement points, as well as the transverse and vertical constraints between the measurement points along the direction of the survey line and perpendicular to the survey line. First, a series of typical geoelectric models are established and numerically simulated, and the results are compared with those of the traditional inversion method to verify the applicability and effectiveness of the method. Then, the constrained inversion is carried out on the physical simulation and measured data, and the results are in good agreement with the actual geological conditions. The numerical simulation, physical simulation and measured data inversion results consistently prove that this method can effectively reduce the uncertainty of the inversion at the isolated measuring points, improve the spatial continuity of the formation boundary, and better reflect the actual geoelectric characteristics of the formation.

Effect of salinity-clay variation on the transient magnetic field in the Quaternary aquifer, theoretically and practically

This study focuses on understanding the physical foundations of the transient electromagnetic method, such as the transition from a simple basic principle to a more complex principle, starting from the Biot-Savart law until the current concept. It calculates the steady and transient magnetic fields around any electrical wire system. Accordingly, this law will be used to determine the magnetic field around the square loop configuration, which matches the magnetic field arising from the circular loop configuration. The square loop equation was derived and extended to include changes in the half-space, which allows us to understand how the electromagnetic waves travel in the subsurface and the farthest point, that can record the TEM response from the TEM loop, according to the loop size and loop current. Accordingly, the deduced equations were applied to predict the transient magnetic field curves of the Quaternary aquifer in three different water zones along the Nile delta, depending on the values of resistivity and chargeability caused by the variations in salinity and clay contents. The calculated transient magnetic curves were then compared with other measured field curves to confirm the validity of the derived equations. Therefore, these curves are expected to be used as guide curves for the transient magnetic field response in this aquifer. Also, these curves are important in estimating the hydro-geophysical characteristics of the main groundwater aquifer in the selected area and in other areas with the same geologic and hydrogeologic settings. Also, a common model is presented for any delta environment in the world in measured and calculated data.

A Geophysical-Drilling-Hydrochemical Coupled Method for Accurate Detection of Concealed Water-Conducting Faults in Coal Mines

The detection of concealed water-conducting structures is essential for preventing water inrush disasters. Aiming to mitigate the limitations inherent in using any single technique, a comprehensive approach that combines integrated mining geophysical exploration, hydrogeological drilling, and hydrochemical exploration (GDH) is proposed for the exploration of concealed water-conducting structures. By conducting a thorough analysis of the background geological data obtained through surface exploration, potentially concealed water-conducting structures can be predicted. Then, a combination of the seismic reflection method (SRM) and mine transient electromagnetic method (MTEM) can be used to detect the location and water-bearing properties of the target structures. Afterwards, the target drilling areas are defined by the anomalies detected by the integrated mine geophysical technique, and the drilling method can directly acquire the hydrogeological information of water-conducting structures and verify the results of the geophysical methods. By means of hydrochemical analysis, inrush water sources and their runoff conditions can be identified, and the spatial relationship betweenof the source aquifers and mining space can be determined; hence, the properties, scale, and configuration of the water-conducting structures can finally be evaluated. Employing a water-conducting fault in a mine as a case study, we verified that the integrated method overcomes the limitations and possible biases of each method, providing a multiple-method solution that can accurately detect concealed water-conducting structures to help prevent water inrush disasters.

Transient Electromagnetic Field Response Analysis Considering Dam Boundary Conditions

Abstract The transient electromagnetic (TEM) method has outstanding advantages in detecting depth and response information and can be used to detect anomalies hidden deep inside dams. However, the current data analysis method based on geological exploration is inapplicable to the interpretation of dam detection data, the main reason being the lack of consideration of the influence of dam boundary conditions on the diffusion of the TEM field. In this work, by establishing a numerical model of a dam for TEM detection, the effects of the dam slope ratio, upstream water body, overburden, and other dam boundary conditions on the TEM field were studied. The results showed that the slope ratio made the propagating TEM field to exhibit a constraining behavior, and a negative deviation could be seen in the attenuation curve, indicating a false high-resistance anomaly. The upstream water body distorted the diffusion of the electromagnetic field, and the low-resistance covering layer caused a low-retardation retention phenomenon in the magnetic field, leading to a positive deviation in the attenuation curve, indicating a false low-resistance anomaly. The influence of the boundary conditions was present throughout the entire observation window in which the detection was performed, and the sensitivity of the magnetic field to these boundary conditions was significantly higher than that of the change rate of the magnetic field. With the increase in the observation time, the main influencing factors were the slope ratio, overburden layer, and upstream water body.

A rapid imaging approach for transient electromagnetic data based on gradient features

ABSTRACT Data processing techniques in transient electromagnetic (TEM) methods face numerous challenges, such as the problem of 3-D imaging and the demand for new data processing techniques arising from the development of small-loop TEM devices. We have developed an imaging algorithm based on gradient features derived from TEM data to address these challenges. We found that normalising the gradient field of TEM responses under appropriate background conditions enables imaging of the target. Numerical experiments conducted under theoretical models have validated the feasibility of this approach and highlighted the significance of background fields. We further designed more complex models and achieved 3-D imaging of synthetic data within seconds, demonstrating the method's high efficiency and applicability to high-dimensional data. Subsequently, we applied the algorithm to challenging small-loop TEM data and demonstrated its superior performance compared to the inversion method, which presents a novel approach for processing data from small-loop TEM devices. This study demonstrates that the algorithm possesses characteristics of high efficiency and wide applicability, suitable for TEM data from various dimensions and types of devices. Furthermore, it holds promising potential in assisting the enhancement of the efficiency of the three-dimensional inversion of TEM data.

A Deep Learning Estimation for Probing Depth of Transient Electromagnetic Observation

The probing depth of the transient electromagnetic method (TEM) refers to the depth range at which the underground conductivity changes can be effectively detected. It typically ranges from tens of meters to several kilometers and is influenced by factors such as instrument parameters and the conductivity of the subsurface structure. Rapid and accurate probing depth is useful for the selection of appropriate inversion parameters and improving survey accuracy. However, mainstream methods suffer from issues such as low computational precision, large uncertainties, or high computational requirements, making them unsuitable for processing massive airborne electromagnetic data. In this study, we propose a prediction model based on deep learning that can directly compute the probing depth from the TEM responses, and its effectiveness and accuracy are validated through synthetic models and field measurements. We compared the performance of classic deep learning models, including CNN, RESNET, and RNN, and found that RNN performed the best overall on both synthetic and field data. Furthermore, we apply this algorithm to deep learning-based ATEM inversion by constraining the one-dimensional resistivity model depths in the training set, to reduce the non-uniqueness of the inversion, accelerate the convergence, and improve its prediction accuracy.

Design and Development of A Semi-airborne Transient Electromagnetic System

The semi-airborne transient electromagnetic method (SATEM) is a geophysical method that combines the advantages of high-power ground-based transmitting and efficient airborne observation. In recent years, the threshold for SATEM application significantly reduced through the integration of the multi-rotor UAVs and the systems obtained by simple redevelopment of existing ground-based systems. However, it is still difficult to obtain good detection results with such systems for the following specific reasons: in terms of system design, there is a lack of method for estimating the key parameters of the system, resulting in the designed system being unable to effectively meet the requirements of the SATEM method and observation scenarios; in terms of technology, there is a lack of effective means of ensuring a high signal-to-noise ratio (high-current transmitting and effective suppression of major external noise) while meeting the demand for distortion-free observation. In response to these issues, a system bandwidth estimation method based on the analysis of information-carrying capacity is proposed. On this basis, the solutions for large current and fast turn-off transmitter and for overcoming major external noise. Through a survey located in a karst landform area, and the overall application performance of the system is discussed based on the inversion results.

Study on stability evaluation of goaf based on AHP and EWM—taking the northern new district of Liaoyuan city as an example

Throughout the history of coal mining in all countries of the world, large areas of goaf have been left behind, and sudden collapses and surface subsidence of large areas of goaf may occur, especially for mining areas with long mining cycles. The northern new district of the Liaoyuan mining area has been subjected to nearly half a century of mining activities, accompanied by a gradual accumulation of disasters, which have occurred frequently in recent years. In order to assess the stability of the goaf in the study area, this paper proposes a hybrid decision-making multi-factor integrated evaluation method. The distribution of underground goafs was determined using geophysical exploration techniques (seismic survey and transient electromagnetic method) and geological drilling exploration. First, an evaluation index system was established based on the specifications of the goaf, the ecological and geological environment, and the mining conditions; the system included 14 indicators. Two weight calculation methods, AHP-EWM, were employed to determine the comprehensive weight of each indicator by combining subjective and objective weights on the basis of improved game theory. Subsequently, the fuzzy comprehensive evaluation method was utilised to complete the stability rating of each block in the study area, and MapGIS and ArcGIS were employed to complete the drawing of the stability zoning map of the northern new district goaf. The study area was divided into three zones of stability, basic stability and instability, according to the critical value. These zones accounted for 23.03%, 36.45% and 40.52% of the total area of the study area, respectively. The comprehensive on-site investigation revealed a decrease in the size and number of collapse pits and the rate of damage to the houses from the unstable zone to the stable zone. This indicates that the results of the division are consistent with the actual situation. The classification results are consistent with the actual ground disaster situation, thus verifying the rationality and validity of the evaluation method. The results indicate that the stability of the study area is generally at the lower middle level.

Transient electromagnetic inversion to image the shallow subsurface based on convolutional bidirectional long short-term memory neural networks

SUMMARY The conventional transient electromagnetic inversion method has a low calculation speed and precision and is susceptible to falling into local minima, which does not meet the fine detection requirements of urban underground space. In this study, we proposed a novel inversion method based on convolutional bidirectional long short-term memory neural networks for shallow subsurface transient electromagnetic inversion. This network structure possessed strong spatial feature extraction capabilities and a proficient understanding of sequential data, thereby addressing the issues of slow conventional inversion computations and inadequate inversion accuracy. Utilizing the apparent resistivity from a three-layer model as the sample input and the real model as the target, the network was trained using batch normalization and dropout techniques to accelerate the convergence rate. The resulting model achieved real-time inversion speeds and high accuracy, with robust generalization capabilities and adaptability to new data. To assess the inversion performance, we used a novel 1-D inversion error calculation index, the correlation area loss error, for a more accurate measurement. Numerical simulation experiments showed that the proposed method required only 2.121 s to invert data from 100 observation points. The inversion efficiency was significantly superior to the conventional methods, maintaining excellent accuracy while effectively discerning subsurface electrical stratification in geophysics. Applying convolutional bidirectional long short-term memory neural networks to multidimensional and field data yielded results superior to those of conventional inversion, demonstrating the promising applicability and generalization of this approach. This study offers an efficient solution for shallow subsurface transient electromagnetic exploration and holds potential for application in other areas.

Joint Inversion of DC and TEM Methods for Geological Imaging

In this study, we present a new methodology for 2D joint inversion, or data fusion, of DC electro-resistivity and Transient Electromagnetic methods. These geophysical techniques have traditionally been used separately, but by combining them, we aim to decrease ambiguities and increase the robustness of the resulting subsurface model. The inversion process was conducted using the classical Occam method with smooth models and synthetic studies were also conducted to understand the limitations and advantages of the method. We also applied the algorithm to data obtained in groundwater exploration in Brazil, and the results showed that the 2D joint inversion is promising in increasing accuracy and reducing ambiguity in subsurface imaging.

Application of opposing coils transient electromagnetic method in urban area with metal interference

Opposing coils transient electromagnetic method (OCTEM) adopts small and weak-coupling transmitting-receiving coils configuration, which helps to reduce side effect and improve the detection resolution. With such advantages, it has been widely used for shallow sub-surface target detection. However, when the method is used in urban area, measured data may be distorted by electromagnetic (EM) interference from nearby metal objects. In practical application, it is necessary to perform modelling to provide guidance for measuring data analysis. Two OCTEM application cases in detecting shallow sub-surface karst caves in urban area with metal objects nearby are presented in this paper. Corresponding modelling are carried out to study the interference effect of the nearby metal objects. The first application case is about the EM interference of a vertical steel tower, of which the influence distance reaches up to 9 m by modelling. The second application case is about the EM interference of a thin aluminum fence, of which the influence distance reaches up to 6 m by modelling. Only when the observation is outside the influence zone, the metal influence can be ignored. When the measurement is inside the influence zone, the metal influence cannot be ignored. However, as the nearby metal objects mainly affects the early data, the subsurface target may also be detected in condition that the target response is stronger than the metal interference, or the target response time window is wider than that of the metal interference.

Detection of Underground Utility Pole Base for Distribution Transmission Network Based on Transient Electromagnetic Method

In the construction of overhead distribution network lines, ensuring the stability and construction quality of utility pole foundations is crucial. Traditionally, this process may involve excavation and direct inspection, which is not only time-consuming but may also cause environmental damage. The non-destructive detection scheme proposed in this paper, based on the transient electromagnetic method (TEM), offers an efficient and non-intrusive method for detecting the burial conditions of utility pole bases, pulls, and chucks. The transient electromagnetic method is a geophysical exploration technique that uses the principle of electromagnetic induction to detect the distribution of underground materials. When detecting utility pole bases, this method analyzes the electromagnetic response generated by underground metallic structures to obtain information. However, traditional TEM has a blind zone problem in shallow metal detection, which limits its application in utility pole base inspection. To address this issue, the scheme proposed in this paper introduces a decoupling coil to eliminate interference caused by the primary magnetic field. This decoupling technology significantly improves the detection discrimination, allowing for a more accurate determination of the burial depth and condition of bases, pulls, and chucks. Finite element numerical analysis using COMSOL 5.4 is adopted to examine the underground magnetic field distribution and optimize coil parameters. This analysis helps to understand the interaction between the electromagnetic field and underground structures, guiding the design of coils and the development of detection strategies. The prototype experimental platform built further validates the effectiveness of the scheme. Experimental results include measured data of magnetic field variations, assessments of detection depth and resolution. These experimental results are crucial for verifying the practical application potential of the non-destructive detection scheme.

Airborne transient electromagnetic imaging method based on wavelet neural network

The airborne transient electromagnetic method is a crucial technique for near-surface exploration in rugged terrains. In this study, we introduce a multi-input, single-output double-hidden wavelet neural network design for airborne transient electromagnetic pseudo-resistivity imaging. We construct uniform half-space, stratified stratum, and three-dimensional geoelectric models. By evaluating various performance indicators of neural networks that employ different wavelet basis functions as activation functions, we identify the most suitable wavelet basis functions. The quasi-resistivity is computed using both the wavelet neural network and the backpropagation neural network and then juxtaposed with traditional apparent resistivity. Our findings indicate that the wavelet neural network's quasi-resistivity aligns more closely with the resistivity of the real model. It is also more responsive to low resistivity anomalies than the conventional apparent resistivity translation algorithm. The wavelet approach moderates the undershoot or overshoot occurrences during abrupt stratum changes, offering a more accurate representation of subterranean electrical properties. When compared to the backpropagation neural network, the wavelet neural network provides a superior fit for the model, rendering a smoother quasi-resistivity depth curve. Therefore, it stands out as an improved method for pseudo-resistivity imaging. By processing survey data via the trained wavelet neural network, we find that the all-time apparent resistivity and quasi-resistivity align well with real-world situations. The wavelet neural network prominently showcases the low-resistance calculation results, offering a broader resistivity range. This clarity enhances anomaly detection, confirming the wavelet neural network's applicability and practicality for airborne transient electromagnetic imaging.

3D modelling of ground magnetic-source airborne TEM data for anisotropic media based on the rational Krylov method

With the rapid development of the transient electromagnetic method (TEM), the numerical simulations of three-dimensional anisotropic media have garnered attention. This study used the rational Krylov method to realise the three-dimensional modelling of the ground magnetic-source airborne transient electromagnetic data for arbitrary anisotropic media. First, based on Maxwell's equations, a time-domain electromagnetic equation was derived for anisotropic media. The finite difference method was employed to discretise the equation, and the electromagnetic field was then expressed as the product of an exponential matrix and a vector related to the source. Subsequently, the rational Arnoldi algorithm was adopted to construct the rational Krylov subspace orthogonal basis vectors, and the electromagnetic fields at different times were obtained based on a model reduction strategy. The accuracy of the proposed algorithm was verified through the comparisons of its results with those of other software packages. We calculated the response for different anisotropic parameters of the typical three-dimensional anisotropic models, and analysed the influence of the anisotropic media on the ground magnetic-source airborne transient electromagnetic data. The proposed three-dimensional forward TEM algorithm provides important technical support for identifying the anisotropic geological bodies and lays the foundation for further inversion research.

Effects of base frequency, duty cycle, and waveform repetition on transient electromagnetic responses: Insights from models of a deep-buried conductor

In transient electromagnetic (TEM) methods, the recorded data for the magnetic field and its time derivative are influenced by the waveforms of the transmitting current. These waveforms are characterized by parameters such as the durations of the turn-on, steady, and turn-off stages as well as the base frequency, duty cycle, and waveform repetition. The full-waveform effects encompass all counteracting effects observed in TEM responses that arise from using a waveform other than a step-off or step-on waveform. To address these complexities, a 3D forward-modeling solver is developed for TEM methods, capable of calculating TEM responses while considering realistic waveforms with considerations for base frequency, duty cycle, and waveform repetition. The effects of these parameters on the magnetic field and its time derivative are investigated through numerical experiments using models involving deep-buried horizontal and vertical conductors. The results indicate that as the waveform period increases, there is a significant improvement in the detection and discrimination capability of the magnetic field for perfect conductors with a conductivity of 1000 S/m or higher in the models presented in this study. However, the improvement in the time derivative of the magnetic field is minimal. Interestingly, the improvement in the magnetic field and its time derivative does not indicate a consistent trend as the conductor conductivity increases. In addition, a novel equivalence phenomenon is uncovered in the magnetic field and its time derivative data. The results also suggest that as the number of waveform repetitions increases or the duty cycle decreases, the discrepancies between the recorded TEM responses at the two off-time stages within a single period gradually diminish. However, the influence of the full waveform on the TEM responses becomes more pronounced with an increasing number of waveform repetitions or a decrease in the duty cycle, especially in terms of the magnetic field.

Highway tunnel crossing fault zones with water-rich highly weathered granite

This study focuses on the Tianshengqiao Tunnel on the Linshuang Expressway in Lincang City, Yunnan Province, China. By combining the transient electromagnetic method, and geological radar geophysical exploration methods, joint fissures and water abundance in the surrounding rock of the tunnel were predicted. Simultaneously, combined with engineering disasters, such as water inrush and seepage in the surrounding rock during engineering practice, a numerical calculation model for the grouting reinforcement of granite mixed-rock tunnels considering the construction process was established using finite element software. The results indicated that the joint fissures in the tunnel were well-developed and exhibited a disorderly trend, showing an open shape. Accompanied by high humidity in the excavated rock mass, the overall water outflow is mainly as strands, with a large amount of water outflow, especially at the arch crown or left arch waist. The difference in the settlement values of the surrounding rocks at different depths within the grouting circle of the tunnel was relatively small, whereas that outside the grouting circle was significant. The larger the scope of the tunnel grouting circle, the smaller the overall deformation of the surrounding rock after the closure of the tunnel support structure.