The superparamagnetic effect arises from the superparamagnetism exhibited by a multitude of nano-sized magnetic mineral particles under an external electric field. This phenomenon manifests in transient electromagnetic data primarily as a deceleration in the attenuation rate of late-stage signals, a characteristic difficult to discern directly from airborne transient electromagnetic signals, consequently leading to significant misinterpretations of subterranean electrical structures. This study embarks on 3D forward modeling of airborne electromagnetic responses in the frequency domain, accounting for the superparamagnetic effect, utilizing an unstructured finite element method. Superparamagnetic responses in the time domain were obtained through frequency-time conversion. This investigation explores the influence of various parameters—such as magnetic susceptibility, time constants, and flight altitude—on the superparamagnetic effect by examining the response characteristics of typical targets. Findings indicate that in its late stages, the superparamagnetic effect can induce a relative anomaly of up to 300%. There is a positive correlation between magnetic susceptibility and the strength of the superparamagnetic effect. The influence of the time constant’s upper and lower limits on the superparamagnetic effect is minimal; however, the range between these limits significantly affects the effect, showing a negative correlation with its intensity. Higher flight altitudes weaken the superparamagnetic signal. The impact is most pronounced when superparamagnetic minerals are shallowly buried, effectively shielding the underlying geology with the characteristics of a good conductivity anomaly, but this effect diminishes with greater depth. The insights from this study provide a theoretical framework for a deeper understanding of the superparamagnetic effect in transient electromagnetic signals and for more accurate interpretations of subterranean geological and electrical structures.

Unmanned aerial vehicle transient electromagnetic (UAV-TEM) is a novel airborne exploration method that offers advantages such as low cost, simple operation, high exploration efficiency and suitability for near-surface exploration in complex terrain areas. To improve the accuracy of data interpretation in this method, the authors conducted a systematic three-dimensional (3D) forward modeling and inversion of the UAV-TEM. This study utilized the finite element method based on unstructured tetrahedral elements and employed the second-order backward Euler method for time discretization. This allowed for accurate 3D modeling and accounted for the effects of complex terrain. Based on these, the influence characteristics of flight altitudes and the sizes, burial depths, and resistivities of anomalies are compared and analyzed to explore the UAV-TEM systems’ exploration capability. Lastly, four typical geoelectrical models of landslides are designed, and the inversion method based on the Gauss-Newton optimization method is used to image the landslide models and analyze the imaging effect of the UAV-TEM method on landslide geohazards. Numerical results showed that UAV-TEM could have better exploration resolution and fine imaging of nearsurface structures, providing important technical support for monitoring, early warning, and preventing landslides and other geological hazards.

Different geophysical exploration methods have significant differences in terms of exploration depth, especially in frequency domain electromagnetic (EM) exploration. According to the definition of skin depth, this difference will increase with the effective detection frequency of the method. As a result, when performing three-dimensional inversion on single type of EM data, it is not possible to effectively distinguish the subsurface geoelectric structure at the full scale. Therefore, it is necessary to perform joint inversion on different type of EM data. In this paper we combine the magnetotelluric method (MT) with the controlled-source audio-magnetotelluric method (CSAMT) to study the frequency-domain three-dimensional (3D) joint inversions, and we use the unstructured finite-element method to do the forward modeling for them, so that the numerical simulation accuracies of different electromagnetic methods can be satisfied. By combining the two sets of data, we can obtain the sensitivity of the electrical structure at different depths, and depict the full-scale subsurface geoelectric structures. In actual mineral exploration, the 3D joint inversion is more useful for identifying subsurface veins in the shallow part and blind mines in the deep part. It can delineate the morphological distribution of ore bodies more completely and provide reliable EM interpretations to guide the mining of minerals.

In this paper, the authors propose a method of three-dimensional (3D) magnetotelluric (MT) forward modeling algorithm based on the meshfree and finite element coupling method. The model is discretized by regular nodes in the central area, and the radial point interpolation method (RPIM) based on the global weakness is utilized to construct the meshfree shape function. The Governing equations in each background gird are solved by Gaussian integration. In the extended area where the points are sparsely distributed, to avoid the instability of the meshfree method, finite element method (FEM) with regular grids is used to solve the governing equation. Finally, the meshfree and finite element governing equations are coupled by the continuity of the field at the interfaces, and the direct solution technique is used to realize the 3D MT forward modeling. Numerical experiments of several typical electrical models are used to verify the effectiveness of the method.