Exploration Geophysics - Special Issue: Advances in forward modeling and inversion of geophysical electromagnetic data, 2024

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.

As a relatively common geological disaster, ground collapse often occurs in urban areas. In view of the complex urban environment, and to effectively identify the areas with potential ground collapse, a new detection method was researched for the demand of fine exploration for urban underground hydraulic connection channels. According to the actual situation, the source was flexibly arranged in areas with good grounding, such as flower beds on the ground. An unmanned aerial vehicle (UAV) was adopted to carry the receiver for data collection in the air. This method would less affected by the flight height, and is thus more suitable for urban environments with tall buildings. Then, geological modeling was built based on the real geological conditions of a city, four underground hydraulic connection channels were set, and the method in the paper was used for detection. The apparent resistivity results effectively present the characteristics of the hydraulic connection channel. The method also provides an effective means for the detection of urban underground hydraulic connection, as well as a basis for efficient investigation with potential ground collapse and corresponding prevention and treatment in advance.

The semi-airborne transient electromagnetic method using short-offset has the characteristics of high signal-to-noise ratio and large detection depth, which can adapt to environmental monitoring, groundwater mapping and metal survey in complex terrain. The terrain effects will modulate semi-airborne transient electromagnetic method response. Most terrains effects studies assume that the anomalous body is located below the centre of topography or under the slope, however, in the direction of electromagnetic propagation, several scenarios exist regarding the position of an anomalous body relative to a topography, and different situations will have different anomalous characteristics. In this study, the time-domain finite-element modelling using unstructured mesh is used to investigate the distribution of the electromagnetic response of different time channels of different anomalous bodies in different positions relative to a topography under two conditions: mountains and valleys. The results show that (1) The influence of the relative position of the anomalous body and the topography is similar in the mountain and valley. When the anomalous body is located on the side of the topography far from the transmitter, it is more affected by the topography than when the anomalous body is located on the side of the topography near the transmitter, and (2) in the early stage, the distribution of the electromagnetic response is primarily determined by the topography, in the middle stage, the coupling between anomalous bodies at different locations and the topography results in an extremely complex response distribution, in the late stage, the response distribution primarily originates from the eddy current of the anomalous body, and the effect of the topography is moderate. When using semi-airborne transient electromagnetic method for environmental monitoring and shallow resources survey in complex terrain, data processing and interpretation should be performed based on the position of the anomalous body relative to the topography.

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.

The semi-airborne electromagnetic method (SAEM) has recently gained increased interest in geophysical exploration applications. For SAEM, ground-based transmitters are deployed within the area of interest or in its vicinity, and the induced magnetic is measured airborne. Because of the large footprint of extended transmitters, three-dimensional (3D) effects can have a significant impact on the gathered data and 3D modelling and inversion approaches must be employed for data analysis. Any 3D EM simulation is a resource-consuming task and efficient tools can therefore be useful to add data interpretation. In this study, 3D tomographic inversion of frequency-domain SAEM data was accomplished based on the integral equation (IE) method. The inversion was linearised by approximating the sensitivity matrix. We further employ the quasi-linear approximation to facilitate out quick forward modelling in the inversion which is tractable on field computers. While this approach sacrifices inversion accuracy for efficiency, we guide the inversion by introducing multinary constraints. These constraints impose a priori known conductivity values into the inversion process. Our results from synthetic and field data demonstrate the efficiency of our approach in achieving a coherent geophysical model that is consistent with geological data and findings from other geophysical techniques. This method provides a practical and capable solution for unveiling conductive 3D structures in the field.

3D modelling plays a crucial role in analysing semi-airborne transient electromagnetic fields, how to accurately and efficiently calculate electromagnetic response has become a significant issue. In this paper, a damping factor improved algorithm of the accelerated finite difference time domain (AFDTD) is proposed for semi-airborne transient electromagnetic modelling. Differing from the previous research, we introduce a novel function to redefine the damping factor, allowing for adaptive adjustment and enhancing calculation accuracy within the finite difference time domain (FDTD) iterative process. To verify the effectiveness of our approach, we conduct tests using homogeneous half-space models, which demonstrate that the improved damping factor significantly enhances calculation accuracy without a notable reduction in efficiency. Furthermore, we apply our improvement to typical conductivity models and polarisable conductivity models, and the results indicate that our approach achieves high accuracy in accelerated semi-airborne transient electromagnetic modelling.

Although electromagnetic methods have made significant advances in archaeological exploration, there remains a lack of a method that offers both high operating efficiency and high resolution. This study introduces a novel approach derived from the Controlled Source Radio Magnetotelluric (CSRMT) method. The CSRMT method combines the efficient configuration of the Controlled Source Audio-magnetotelluric (CSAMT) method with enhanced resolution capabilities. To evaluate the efficacy of the new method in archeological exploration, we designed a series of models based on existing references related to ancient city wall remains. Using the 3D contraction integral equation method, we numerically simulated the high-frequency component of the CSRMT method, and then on, the Laterally Constrained Inversion technique is used to invert the data. The effectiveness of the method was assessed qualitatively and quantitatively through analysing the electromagnetic field and apparent resistivity of models with varying widths, heights, top burial depths, and resistivity. Our analysis revealed that models with shallower burial depth and greater height of the underground city wall exhibited higher resolution. The findings demonstrate that the CSRMT method can efficiently and accurately identify buried remains, making it a highly promising tool for archaeological exploration and warranting further development.