Transient Electromagnetic Method Data Research Articles

Three-Dimensional Forward Modeling of Transient Electromagnetic Method Considering Induced Polarization Effect Based on Spectral Element Method

The transient electromagnetic method (TEM) is widely used in the exploration of mineral, petroleum, and geothermal resources due to its sensitivity to low-resistivity bodies, limited site constraints, and strong resistance to interference. In practical applications, the TEM often uses a long wire source instead of an idealized horizontal electric dipole (HED) source as the excitation source. This is due to the complex external conditions and the relatively large distance between the receiving zone and the transmitter source. Compared to the HED, the long wire source can provide a larger excitation current, generating stronger signals to meet the requirements of a higher signal-to-noise ratio or deeper exploration. It also produces longer-duration signals, thereby providing better resolution. Additionally, for the interpretation of TEM data, three-dimensional forward modeling plays a crucial role. However, the mature traditional TEM forward method is based on a simple, sometimes inappropriate model, as it is well established that the induced polarization (IP) effect is widely present in the deep earth, especially in oil and gas reservoirs. The presence of the IP effect results in negative responses in field data that do not conform to the traditional theoretical decay law of TEM, which can significantly impact data processing and inversion results. To address this issue, a TEM forward modeling method considering the IP effect based on the spectral element method (SEM) has been developed in this study. Firstly, starting from the Helmholtz equation satisfied by the time domain electric field, we introduce the Debye model with polarization information into the forward modeling by utilizing the differential form of Ohm’s law. As a result, we derive the boundary value problem for the time domain electric field that considers the induced polarization effect. Using Gauss–Lobatto–Legendre (GLL) polynomials as the basis functions, the SEM is employed to discretize the governing equations at each time step and obtain spectral element discretization equations. Then, temporal discretization equations are derived using the second-order backward Euler formula, and the linear system of equations is solved using the Pardiso direct solver. Finally, the electromagnetic responses at any time channel are obtained via SEM interpolation and numerical integration, thereby achieving three-dimensional TEM forward modeling considering the IP effect. The results indicate that this method can effectively reflect the spatial distribution of polarizable subsurface media. It provides valuable references for studying the polarization parameters of subsurface media and performing a three-dimensional inversion of TEM data considering the induced polarization effect.

3D Inversion of Transient Electromagnetic Data for Concealed Karst Cavern Detection

The karst cavern is common undesirable geological body in limestone areas, which can bring great safety hazards to the construction and operation of tunnels, bridges and highways. Transient electromagnetic method (TEM) can effectively detect hidden karst structures based on the difference in electrical property between the karst cavern and the surroundings. Traditionally, 1D inversion is commonly used for the interpretation of TEM data due to its high efficiency. However, this may lead to artifacts due to 2D or 3D effects in practical surveys. In this study, we present a Gaussian-Newton approach to 3D inversion of TEM data for karst cavern detection. The numerical test on synthetic TEM data demonstrates that 3D inversion can effectively delineate the location and geometry of concealed karst cavern compared to the 1D inversion results.

CG-DAE: a noise suppression method for two-dimensional transient electromagnetic data based on deep learning

Abstract The transient electromagnetic method (TEM) is a geophysical exploration method that can efficiently acquire subsurface electrical parameters. For airborne, towed and other mobile platforms, TEM systems, large data volumes and the traditional one-dimensional denoising method with low efficiency and low signal-to-noise ratio (SNR) of late-time are the main bottlenecks limiting its reliable application. To address this problem, this paper proposes a neural network structure suitable for two-dimensional (2D) TEM data processing. The proposed structure combines a classical convolutional neural network denoising autoencoder with a gated recurrent neural network autoencoder, called the CNN-GRU dual autoencoder (CG-DAE). This method can directly input 2D TEM response data as images into the network for processing, which greatly improves data processing efficiency compared to single-time-channel processing. The simulation experiments verified the effectiveness of CG-DAE. After using CG-DAE denoising, the SNR of late-time (0.2–1 ms) signals is improved to nearly 29 dB, the 2D anomaly layer position is clear and the relative error (RE) between the denoised data and the corresponding clean data is <1.41%, while the RE of the late-time signals can be reduced to 3.68%. The proposed method can lay the foundation for fast processing of TEM data based on mobile platforms such as those that are airborne and/or towed.

S-Inversion of electrical source semi-airborne TEM data to determine the electric interface underground

A new S-inversion approximate interpretation approach was developed to reflect electric interface underground from multi-source semi-airborne Transient electromagnetic method (TEM) data. This method starts with electrical source TEM S-inversion according to the second derivative of the conductivity parameter based on the moving thin sheet approach, and then the superposition principle was adopted, which could effectively avoid the random noise, introduced by the differential and highlight the abnormal information in the depth. In this article, the method of second derivative of apparent longitudinal conductivity, which is designed for semi-airborne TEM interpretation, the theoretical analyses and the numerical method are also studied in detail. Finally, a real semi-airborne data is studied with the approach, and result shows that the proposed method is effective and successful for exploring unfavorable geology for semi-airborne TEM.

Born approximation imaging technique for electrical source multi-component TEM

Abstract In this study, to obtain higher-resolution geoinformation in the electrical source transient electromagnetic method (TEM) interpretation, the pseudo-seismic Born approximation imaging method is applied to the vertical magnetic induction intensity ${B_z}$ and the horizontal electric field ${E_y}$, which is paralleled to the source. First, the differences between the two components are compared, and the results reveal that different components can reflect varied geological information. ${E_y}$ has a stronger signal and is more sensitive to the high-resistivity layer at a long offset, whereas ${B_z}$ has a greater relative difference in the low-resistivity layer at a short offset. The TEM field is then transformed into the pseudo-wavefield using the wavefield transformation method and the Born approximation pseudo-seismic imaging method is adopted to locate the electrical interface. After calculating the 3D model, the results indicate that the multi-component Born approximate imaging can intuitively and effectively locate the depth of the geological interface. Furthermore, the imaging results of a coal mine located in Gansu Province, China, proves that the proposed method can pinpoint the buried location of the coal goaf as well as the stratum trend. In general, the multi-component pseudo-seismic imaging technique plays a significant role in interpreting the electrical source TEM data.

Mapping coal water-filled zones using multi-radiation source transient electromagnetic pseudo-seismic Born approximation imaging and apparent resistivity imaging in Gansu, China

The coal water-filled zones have become a growing safety hazard, so effective detection techniques and accurate interpretation methods are of great concern. In this paper, we adopt multi-radiation source transient electromagnetic method (TEM) in the data collection, and employ joint imaging method in the data interpretation. A single-radiation source can only be coupled with the geological body from one side, making holographic photography problematic, but multi-radiation source can suppress random noise, improve the signal-to-noise ratio, and reduce the volume effect. Typically, the apparent resistivity method can reflect the electrical distribution characteristics, while the pseudo-seismic imaging method (PSI) can quickly locate the position and shape of the geological structure, so the two imaging methods can be combined. Therefore, firstly using multi-window time-sweep wavefield inverse transformation technology converts the TEM data into the multi-resolution pseudo-wave, then utilizing the joint interpretation method obtains the underground electrical distribution characteristics, the location of the water-filled zones and stratum's continuous undulations. In this paper, through the calculation of the theoretical model, the results verify the effectiveness of the proposed method. Through processing the field data in Gansu, China, the results demonstrate that the joint interpretation method can map the coal water-filled zones and reflect the geological structures.

The processing workflow of semi-airborne transient electromagnetic data using geological modeling and three-dimensional numerical simulation – A case history in Yunnan, China

To overcome the limitations including the topography in survey area and the complex geometry of the target on conventional transient electromagnetic method (TEM) interpretation, we extend in this paper a workflow for processing semi-airborne TEM data. Based on the digital topography data, geologic sections and well logs, a 3D geologic model was built for numerical simulation. After mapping the geologic model to resistivity mesh, a mimetic finite volume with Krylov subspace method was used for calculating the influence coefficient of topography. This processing workflow was applied on a semi-airborne TEM survey for determining the thickness of cover layer on a hillside in Yunnan, China. The thickness of the cover layer inferred from the processed TEM data is consistent with the local geological sections. This workflow can not only process measured data, but also perform numerical simulation on the target area with complex topography and stratum structure.

Using Wavelet Packet Denoising and a Regularized ELM Algorithm Based on the LOO Approach for Transient Electromagnetic Inversion

Transient electromagnetic method (TEM) inversion is a complex nonlinear problem with high dimensionality and ill-posedness. Using traditional neural networks based on a gradient algorithm to solve the TEM inversion problem might result in a slow convergence where the model falls easily into local minima. To solve these problems, a wavelet packet denoising (WPD) technology and a regularized extreme learning machine (ELM) algorithm based on the leave-one-out cross-validation (LOO) approach are proposed in this article. First, the WPD method is based on the hard threshold, the Shannon entropy with a Sym15 wavelet, which is provided to suppress the noise from the TEM data. Moreover, the learning process of the ELM model is optimized by randomly setting the hidden layer parameters instead of updating based on the gradient algorithm, which accelerates the learning speed. Finally, the LOO methodology is introduced to optimize the regularization factor of the ELM to improve the prediction accuracy and generalization ability of the approach. The inversion results of two typical TEM layered geoelectric models, two anomalous body models, and one field example are provided to prove the validity and feasibility of the proposed approach. In addition, compared with other traditional methods [ELM, backpropagation (BP), radial basis function (RBF), and linear support vector machine (LSVM)], the introduced method achieves higher inversion accuracy, better stability, and stronger forward data fitting ability, enabling it to effectively solve the TEM inversion problem.

Transient Electromagnetic Inversion: An ICDE-Trained Kernel Principal Component OSELM Approach

The traditional extreme learning machine (ELM) inversion of transient electromagnetic method (TEM) based on random initial weights is known to be inept for its low-computational efficiency and poor generalization performance. To solve these problems, a kernel principal component online sequential extreme learning machine (KPCOSELM) trained by an improved chaotic differential evolution (ICDE) method is proposed. An additional kernel principal component (KPC) layer is used, which reduces the dimension of TEM data and enhances the computational efficiency of online sequential extreme learning machine (OSELM). Moreover, a novel ICDE algorithm is presented for improving the learning ability and generalization performance of OSELM inversion. In the proposed ICDE, the tent chaotic sequence is adopted to enhance the global exploitation ability, and a constraint factor is added to ensure better convergence. The feasibility and effectiveness of the proposed inversion method are evaluated via four groups of experiments. The inversion results of the synthetic and field examples show that the proposed approach outperformed other methods in terms of computational efficiency and prediction accuracy, and realized satisfactory performance in TEM inversion, which provides a new strategy for the application of neural networks in TEM inversion.

Fast transdimensional Bayesian transient electromagnetic imaging for urban underground space detection

The transient electromagnetic method (TEM) is one of the most effective geophysical methods for detecting urban underground space. The underground resistivity distribution obtained by this imaging technique is important for engineers in urban construction and planning. The conventional transdimensional Bayesian (Trans-Bayes) imaging method gives the credible interval of the data model and quantifies the uncertainty in the imaging results. However, due to the large number of calculations needed and the slow speed of TEM forward modelling, the engineering practicality of Trans-Bayes method is poor. To solve this problem, we propose a fast Trans-Bayes imaging approach based on the Bayesian information criterion (BIC) and the adaptive Metropolis (AM) algorithm. Our simulation and field experiments show that this BIC-AM approach can greatly improve Trans-Bayes imaging efficiency while ensuring imaging accuracy. This method may provide fast uncertainty estimates for urban TEM data.

Shallow velocity model from the transient electromagnetic method data: results of application in Eastern and Western Siberia

The geological section of Eastern and Western Siberia is an extremely complex object for a seismic exploration. The reason for this is the extremely high variability of the upper part of the section lithology, rough terrain, and permafrost rocks. This paper delivers an alternative approach to predicting the velocity model of the upper part of the section. The approach based on the original method of restoring the elastic-velocity characteristics from the data of transient electromagnetic method (TEM) in the near field zone. Research devoted to test the methodology of the shallow section velocity model calculation based on TEM data in a number of fields in Eastern and Western Siberia. Derived results aimed to improve the accuracy of the geological model building and the reliability of the hydrocarbon plays prediction. Synthetic modeling and field data confirm the high level of the proposed methodology effectiveness. It was shown that for the Eastern Siberia settings, an improvement in the quality of processing of seismic data consists in a significant increase in the dynamics and coherence of seismic recordings. In Western Siberia, it is possible to take into account the velocity anomalies associated with the permafrost rocks and zones of transit from the onshore part of the survey area to the sea. The main features of the study are useful in oil & gas companies and scientific institutions dealing with seismic data processing and interpretation to optimize expenses and improve blocks geology understanding.

Quasi-3D TEM inversion based on lateral constraint

Quasi-2D inversion based on a lateral constraint is an effective technique for the interpretation of the survey data of transient electromagnetic method (TEM). In this paper, the principle of the lateral constraint is introduced to construct a quasi-3D TEM inversion. Considering that the 3D measuring grid is often not strictly regular, the quasi-3D TEM inversion is constructed using the distance-weighted adjacent stations’ lateral constraint, which can suppress the irrational model mutation generated by single-station 1D inversion, and has no requirement concerning the regularity of the 3D measuring grid. The application in the inversion of field TEM data had verified the effectiveness of this method.

Accelerated Bayesian Inversion of Transient Electromagnetic Data Using MCMC Subposteriors

Transient electromagnetic method (TEM) is one of the major tools to image the subsurface resistivity. The gradient-based inversion of TEM data only provides a unique solution using a subjectively defined regularization penalty, leaving the uncertainty of the solution unaddressed. The Bayesian method can be used to estimate the model parameters, as well as quantify their uncertainty. However, it requires far higher computational costs than gradient-based inversion, which limits the Bayesian inversion of TEM data to 1-D assumptions. We propose an accelerated Bayesian method based on Markov chain Monte Carlo (MCMC) subposteriors to perform full 2-D inversion of TEM data. A robust scheme is designed to divide the model space of a TEM profile into subspaces so that independent MCMC chains can be used to update the parameters in each subspace in parallel. The division is based on the coverage of the source loops using a cumulative sensitivity matrix. Then, the subposteriors obtained at each subspace are merged to approximate the full posterior of the model space using a weighting strategy. A numerical test of a 2-D valley model is used to validate the proposed method. The Bayesian inversion successfully obtained posterior that converges to the true model. The median model makes a good inference of the model parameters, while the probability density function gives their uncertainty estimates. The statistical model of interest can be further extracted from the model ensemble. The proposed method provides an effective framework for Bayesian inversion of TEM data with a multidimensional forward operator.

Full Waveform Inversions of Borehole Transient Electromagnetic Virtual Wave Fields and Potential Applications

The transient electromagnetic method (TEM) for boreholes uses fixed source loops to launch at excavation faces, and is able to realize the mobile reception of secondary fields in the boreholes and detections of low-resistance hazards. This method is known as high detection accuracy, due to the fact that the receiving points are close to the anomalies. However, the interpretation method for this device has not yet been perfected. The present study's goal was to realize the interpretations of boreholes TEM based on inverse transform algorithms of the TEM wave-fields and full waveform inversions. It was found that under the conditions of transient electromagnetic virtual wave-fields, the characteristics of the virtual wave-field time-distance curves of the two-dimensional device could be examined, and a corresponding dynamic correction algorithm was successfully obtained. The wave-field velocities were analyzed using an equivalent conductive plane method. Additionally, the pseudo-seismic inversions of the tunnel-borehole TEM data were realized using full waveform inversion technology. Then, the inversion results of the three-dimensional numerical simulations, flume physical simulations, and downhole field simulations were calculated. It was observed that good imaging results had been obtained for small-scale borehole radial anomalies. Finally, the proposed method was applied to the engineering practices in an underground coal mine in Shanxi Province. The practicability and effectiveness of the proposed method in the fine detection of the properties, forms, and scale of water-logged goaf roadways were successfully tested in the field. The research results indicated that the roadway-borehole transient electromagnetic detection method was complementary to the underground geophysical exploration and drilling, and could be effectively applied in the detection of water-logged goaf roadways.

A metal interference correction method of tunnel transient electromagnetic advanced detection

Abstract Water inrush during tunnel excavation severally threatens the mining safety as blind water-bearing structures may develop in front of the working face. The transient electromagnetic method (TEM) has been widely applied in the advanced detection of tunnel water-bearing structures. However, the metal interference of both supports and tools in the tunnel has become a bottleneck that reduces the forecast accuracy of this method. In this paper, we analyse the effect of metal interference on TEM data and propose a novel set of an observation and correction method under metal interference based on the ratio of anomalous and background apparent resistivity. Flume model experiments both with and without metal interference are carried out, showing that this interference can affect TEM measurements significantly and result in false anomalies, and that our proposed method can remove this ambient noise caused by metal interference appropriately. The practical application further proves that this method can effectively reduce low-resistivity interference introduced by the support and other metal tools inside the tunnel. By applying this correction method, the location of water-rich anomalies can be detected more precisely during the excavation process of the same tunnel, which is of high application value of reducing exploration difficulty and tunneling risk.

Development of the Inversion Method for Transient Electromagnetic Data

Transient electromagnetic method (TEM) is a geophysical tool to obtain resistivity distribution in the subsurface. Combining with the resistivity property of typical rocks, the TEM method can make inferences of the geological maps underground. The inversion method is the main technique to extract resistivity form the recorded TEM data. There are various inversion methods that have been applied to TEM data, each of which favors different model structures. It is essential to choose the optimal inversion algorithm for a TEM survey in a given geological setting. Thus, this article presents a systematic summary of recent developments of inversion methods for TEM data. We first summarize the basic concept of the TEM inversion theory. Then, the recent developments TEM inverse method are divided into deterministic inversion and stochastic inversion. For the deterministic method, we present the development of constrained inversion and joint inversion. For the stochastic method, we analyze the particle swarm optimization, Bayesian inversion, and TEM pseudo-seismic imaging. Thereafter, we prospect the future research direction of the TEM method.

Magnetic Viscosity Effect on Grounded-Wire TEM Responses and Its Physical Mechanism

Magnetic viscosity (MV) effect is a disturbance to the transient electromagnetic method (TEM). This effect will cause slow decay at the intermediate-late time of the TEM responses, leading to erroneous interpretation. Although there are extensive researches on the MV distortion to TEM data, they are focused on conventional loop source configuration, while little has been studied for grounded-wire source configuration that has become the essential role for relatively deep-buried targets. Hence, we present the study of MV effect on the grounded-wire source TEM data. We first derived the formulas for calculating the secondary field due to MV effect, based on the Chikazumi model. The dependence of the MV effect on model parameters, such as resistivity, susceptibility, offset and geometry of the superparamagnetic layer, is then examined to illustrate the intrinsic physical mechanism of MV effect. We find that the MV effect on the grounded-wire source TEM data can be suppressed by adjusting the parameters of the survey design. Thereafter, we propose the method to quantify the MV effect when estimates of resistivity and susceptibility are available. Finally, the method for choosing the optimal offset to suppress the MV effect is proposed, which can be used as a guide for the installation of fieldwork of grounded-wire TEM survey.

Design of Wind and PV-Solar Hybrid System for Tem Equipment in Geophysical Exploration for Geothermal Energy

The research was tailored to optimize the design of a hybrid system that is powered by wind and solar energy in sustaining the power requirements of the Transient Electromagnetic Method (TEM) instrumentation. The issue addressed by the research was the unsustainability aspect of the batteries during TEM data collection. Therefore, the research tried to come up with an alternative that involved making power from wind and solar resources to power the TEM equipment. The research design began by doing a quantification analysis of both wind and solar resources in the geothermal area. In addition, a terrain and security analysis was done. Lastly, a hybrid system was designed considering its component specification that was governed by the wind and solar characteristics of the geothermal area under study. The sole aim was to solve issues faced with one form of green energy, geothermal energy, with other forms of green energy, wind and solar energy. The end result was the design of a revised final hybrid system that was able to sustain the power requirements of the TEM equipment during data collection in a geophysical survey with the available natural wind and solar resources in the Olkaria Geothermal field. From the analysis, it was evident that design of the hybrid system will primarily depend on the availability of the wind and solar resources in the area under study and the power requirements of the application being powered by the hybrid system.

TEM Pseudo-Wave Field Extractions Using a Modified Algorithm

The migration of the transient electromagnetic method (TEM) has been a research topic for decades. The method, which uses the mathematical q transform to perform imaging in the wave domain, has proved its validity in some circumstances. One of the crucial steps of this kind of method is the inverse q transform, which extracts the pseudo-wave field that satisfies the wave equation from the TEM data. Conventionally, the time range of the q integral is divided into several windows and the transformation result is recovered using a regularization method, in which each window is summed up to get the final wave field. Although the recovered wave field demonstrates the key features as is indicated in the wave equation and the corresponding imaging techniques have proved to be useful, the accuracy of the extraction of these wave fields hampered the development of more accurate migration techniques. This paper will focus on the extraction of the wave field from the TEM data. A novel correlation stacking method was proposed and compared with singular value decomposition (SVD) and the pre-conditioned regularization conjugate gradient method. The comparison of the results from these methods demonstrates that the extraction results of the proposed correlation stacking method were more accurate and stable. The pseudo-seismic wave field extraction results of the actual measured TEM data showed that the correlation stacking method was the optimal method for the pseudo-seismic wave field extraction of TEM data. [Figure: see text]

Modern information technologies in organization of geophysical studies

The features of geo-electrical surveying on permanent geophysical stations and in field conditions are described in this article. Modern approaches to geophysical study with IT-technology application, which require an automatic or semiautomatic data recording, express analysis of current experimental results, in a on-line or off-line mode, automatic data acquisition and transmission by GSM net are represented. Described approaches are realized using ftp-server with appropriate settings on a base of standard server’s tools i. e. LAMPP (Linux, Apache, MySQL, PHP, Python) and web techniques: HTML, CGI, SSI, JavaScript, DHTML, CSS. The described approaches were tested on the permanent geophysical station “Nyzhne Selyshche” (Zakarpatska oblast) for a natural electrical field variations monitoring study and during in field study of the shallow layers resistivity by the transient electromagnetic method (TEM). The express analysis of experimental TEM data is shown and illustrated by screenshots demonstrating the operation of program modules developed and handled by OS Windows. Such application can also be used for any other data as where the mobile Internet is available as well as the off-line mode is possible too.