In a borehole radar (BHR) survey, a steel cable or a metallic drill pipe attached to a BHR can act as a waveguide, and often gives measured radargrams with strong, obliquely striped events. These guided BHR wave events are commonly considered as interference noise for conventional BHR surveys and have not been fully investigated. To better understand these events, a 2-D cylindrical finite-difference time-domain method is used in this paper for simulation and investigation of the guided BHR wave propagation. Snapshots of wavefields and response profiles for different configurations are simulated and analyzed to understand the generation and interaction process of the guided waves with the borehole and the surrounding formation. The simulation results confirm that if a conventional BHR is attached with a conductive waveguide, the BHR wave can be coupled with the waveguide to generate guided BHR waves propagating along the borehole. The backward-looking or forward-looking guided BHR reflections from the strata discontinuities are recorded on BHR profiles. The generation of forward-looking events makes it feasible to image ahead of a drill bit in real time while drilling using a conventional BHR. A simple formula to estimate the location of the interface using the forward-looking events is given. Based on the synthetic data with a BHR 3-7 m away from the interface, it was demonstrated that the location of the interface can be accurately predicted with an error of about 1 cm. Finally, the effect of the length of the waveguide on the guided waves is also discussed.

The integration of ground-penetrating radar (GPR) with unmanned aerial vehicles (UAVs) enables efficient non-contact detection, performing exceptionally well in complex terrains and extreme environments. However, challenges in data processing and interpretation remain significant obstacles to fully utilizing this technology. To mitigate the effects of numerical dispersion, this paper develops a high-order finite-difference time-domain (FDTD(2,4)) three-dimensional code suitable for airborne GPR numerical simulations. The simulation results are compared with traditional FDTD methods, validating the accuracy of the proposed approach. Additionally, a Kirchhoff migration algorithm that considers the influence of the air layer is developed for airborne GPR. Different processing strategies are applied to flat and undulating terrain models, significantly improving the identification of shallowly buried targets. Particularly under undulating terrain conditions, the energy ratio method is introduced, effectively suppressing the interference of surface reflections caused by terrain variations. This innovative approach offers a new technical pathway for efficient GPR data processing in complex terrains. The study provides new insights and methods for the practical application of airborne GPR.

Gravity interface inversion is a critical technique in delineating the substructure of basins, providing essential technological and data support for oil and gas exploration. Traditional gravity inversion approaches often encounter issues such as suboptimal local solutions and limited resolution. Moreover, conventional deep learning inversion methods typically require extensive time for empirical parameter adjustment, hindering the achievement of optimal training outcomes. By utilizing Bouguer gravity anomaly data, this research pioneers the application of the EfficientNetV2 network in predicting 3-D basement relief interfaces and variations in overburden density. The network employs a composite scaling technique to adaptively adjust its width, depth, and input resolution, thereby identifying the most effective network configuration. Concurrently, the innovative Fused-MBconv convolutional module efficiently achieves superior results with a reduced number of network parameters. Specifically, in the Poyang Lake Basin study in Jiangxi Province, China, the EfficientNetV2 model demonstrated enhanced accuracy in predicting density variations of the basement interface and overlying strata compared to traditional methodologies.

Traditional Finite Difference Time Domain (FDTD) approaches face challenges with increased computational demands and errors as terrain complexity and flight altitude rising. This study introduces the Crank-Nicolson-Cycle-Sweep-FDTD (CNCS-FDTD) method, enhancing airborne ground penetrating radar (GPR) simulations over undulating terrains. CNCS-FDTD, as an unconditionally stable implicit algorithm, overcomes these by allowing larger time steps without the constraints of the Courant-Friedrichs-Lewy (CFL) condition. Our research aims to assess how CNCS-FDTD can improve computational efficiency and accuracy in modeling airborne GPR responses across varied terrains. Initial simulations using a three-dimensional graben model indicate that CNCS-FDTD can maintain calculation stability with significantly larger time steps, reducing computational time by 42%. To further verify the reliability of the numerical simulation results, the paper also presents experimental tests of the undulating terrain model. By comparing the numerical and physical simulation results of models under different flight altitudes and terrain conditions, the accuracy of the simulation results is validated.

Geoelectric structures have great influence on the earth surface potential (ESP) induced by ground return currents (GRCs) in high-voltage dc (HVdc) monopolar operations. Traditional ground-detection methods are cumbersome due to the long distances between the grounding electrodes of substations. The airborne transient electromagnetic (ATEM) method has become a popular technique for exploring large-scale geoelectric structures. First, we analyze the influences of different 3D geoelectric models on the fluctuation in GRCs and propose a 3D model to evaluate ATEM simulations. Second, we present an efficient ATEM simulation method based on a finite-element (FE) algorithm to obtain the 3D geoelectric structure used to calculate the ESP. The stability and convergence rate of solving FE systems are improved by using an induced dimension reduction (IDR) solution algorithm. The detectability of the ATEM method is validated by an inversion case based on the Occam algorithm. The numerical results demonstrate that our robust ATEM simulation method is useful for detecting the 3D geoelectric structure used in ESP analysis.