Unexploded ordnance (UXO), which causes many civilian casualties every year, has become a serious environmental problem. To deal with the problem, we have developed a new drone-based transient electromagnetic (TEM) system, which was designed for the UXO detection through very low altitude measurements. Drone-based TEM system uses the rotorcraft equipped with central loop TEM device to realize the UXO detection. The system was more safe and efficient than a ground-based TEM system in UXO detection. Compared with the airborne magnetic method or helicopter-borne TEM system, it has the advantages of low cost, flight safety, and so on. In this letter, the system characteristics are introduced in detail, providing the theoretical analysis of the system in UXO detection and verification of model data. Finally, through the UXO detection in the former weapon test base, the results show that the system is effective and successful in UXO detection.

The rational Krylov subspace method enables the time integration required to calculate responses directly in the time-domain to be computed accurately and more efficiently than by regular time-stepping methods. In this study, the optimal rational Krylov subspace approach is used for the forward modeling of data from the grounded electric source airborne time-domain electromagnetic (GREATEM) method. The space dependence of Maxwell's equations is discretized using a mimetic finite-volume (MFV) technique, which allows strongly discontinuous conductivities to be treated properly. One advantage of an MFV approach is that the initial magnetic problem for the grounded electric source can be solved using the same discrete operators. The optimal rational Krylov subspace approach is then used for the time integration to efficiently model the full spectrum with fewer solutions of a large system of equations. A concise optimization algorithm is presented to select a single repeated pole parameter, which results in convergence under an a priori given error independent of mesh grid and electrical structure. The direct solver ‘PARDISO’ and right preconditioning are used to further accelerate solution performance of solving the large asymmetrical linear system of equations. The accuracy and efficiency advantages are demonstrated by a large conductivity contrasts layered model and in a 3D benchmark model. A deeply buried massive sulfide model was also built up to evaluate the deep detection capability of the GREATEM method, which shows one can expect to detect a significant response from the deep target in the airborne measurements.

The transient electromagnetic (TEM) method is widely used in near-surface geophysical prospecting. The high-precision forward and inversion of large-scale complex models is a challenging problem. It is difficult to solve the large-scale problems using the direct solvers due to the large memory requirements. In this article, we present a restarting polynomial Krylov method for modeling 3-D large-scale TEM responses. The mimetic finite volume method is carried out for spatial discretization. The step-off TEM response then can be expressed as a matrix exponential function. The restarting polynomial Krylov method is used to solve the matrix exponential function. For a given restart subspace dimension, the residual is used to obtain the forward response at any time that meets the given accuracy. This method does not need to solve large-scale linear equations. Furthermore, the memory usage is mainly determined by the number of spatial discrete grids and the restart subspace order. The numerical experiments of large-scale model demonstrated that the method is accurate and uses limited memory.

The semi-airborne transient electromagnetic (SATEM) method has garnered increasing attention and research interest due to its superior detection depth and high efficiency. Theoretically, the SATEM method employs a long straight grounded wire as its transmitter source; however, in practical applications, various source shapes emerge due to terrain constraints. This paper investigates the influence of source shape on SATEM data. A three-dimensional (3D) block model is established, and a model order reduction algorithm is applied to calculate the 3D spatial distribution of electromagnetic fields generated by both an ideal linear source and a curved source. Numerical simulation results reveal that: (1) in the early stage, maximum values of electric and magnetic fields near the source are distributed along the source shape; this influence diminishes with time, and at the late stage, the spatial electromagnetic field distributions generated by linear and curved sources converge, exhibiting similar patterns regardless of the source geometry; (2) the source shape primarily affects early responses in small-offset areas while having minimal influence on late responses in large-offset regions; (3) for deep detection applications conducted in large-offset areas, the influence of the source shape can be disregarded; however, for shallow detection with receivers positioned in small-offset regions, the source shape effects should be taken into consideration.