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 paper 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.

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.

We have developed a scheme for decoupling the induced polarization (IP) effect from time-domain electromagnetic (TDEM) data. This scheme is achieved by simultaneously sampling the resistivity and pseudochargeability in a Bayesian framework. The TDEM and IP responses are simulated separately with the sampled model parameters and then are stacked to fit the IP-affected TDEM data. Thus, the influence of the IP phenomenon is eliminated in the process of recovering the resistivity. To reduce the computational cost brought by the Bayesian sampling, we use a 2D parametrization instead of sampling the full 3D space and we use a linear perturbation approximation for calculating the IP response. The linearized inversion results are used as the initial model, and a multiple proposed points algorithm is used to accelerate the sampling. We validate the proposed method with synthetic and field examples showing that it restores accurate estimates of electrical structures from the TDEM data that are significantly affected by the IP phenomenon. Our method could advance the application of the TDEM method to the scenario in which the IP may affect the TDEM data and mask the underlying geologic targets.

Transient electromagnetic method (TEM) is an important tool for mapping the subsurface resistivity. As the electromagnetic fields with different frequencies reach different depth of the Earth, the resolution of TEM method is closely related to the spectrum properties of its source signal. The pseudorandom binary sequence (PRBS) is a recently applied source signal and is thought to be superior to the conventional square wave for its adjustable frequency range and density. However, to invert the response from this optimized source, the pure secondary field needs to be extracted from the full waveform response in which parts of useful information is lost inevitably. We thus propose to directly invert the full waveform TEM response from the excitation of PRBS using a transdimensional framework. We use the reverse-jump Markov chain Monte Carlo (RJ-MCMC) sampler to get the model ensemble so that the posterior of the model can be obtained. The PRBS source is convolved with the impulse response of the Earth to fit the recorded full waveform response. The 2-D model space is discretized using a two-stage binary tree and updates in parallel, which dramatically improve the sampling efficiency. The synthetic examples compare the results from the conventional time-domain step response and the full waveform response and demonstrate that the proposed method obtains higher resolution and can better resolve the interface in the shallow and moderate depth. Furthermore, the real data example recovers the model structure that is consistent with the geologic inference, providing alternate evidence for the conjecture of the Sanshandao fault.

The land-based controlled-source electromagnetic (CSEM) method is an important tool in mapping subsurface resistivity contrast, especially for conductive target embedded in a resistive environment. For resistive targets on land, choosing an appropriate configuration to a specific field observation is quite confusing, due to the lack of systematic comparisons of different methods. We have conducted a comparison between the broadside and inline time-domain CSEM methods, using the short-offset transient electromagnetic (SOTEM) method and multitransient electromagnetic (MTEM) method as representatives respectively. We first compared the resolution of these methods by analyzing the relative target response and the misfit space of the designed models. We found that the inline MTEM method had advantages over the SOTEM method in resolving the thin resistive layer. We have developed a weighted joint inversion scheme to enhance the vertical resolution of the MTEM method. We then applied the methods to the investigation of a giant molybdenum deposit. The orebody, which is the real target of the exploration, does not have a conductivity contrast with its host. However, it sits on top of the granite porphyry, which is resistive compared with its surroundings, and so the granite porphyry becomes the resistive target for EM exploration. The results indicated that both methods are effective in locating large resistive target, yet the MTEM method outperforms the SOTEM method when a thick conductive overburden is presented.