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The grid chosen for marine controlled-source electromagnetic forward modeling and inversion is important because it affects the accuracy and efficiency of the latter. Providing these kinds of results is particularly difficult for offshore exploration. In this study, we compared a structured and unstructured grid using three models. Complex geometry, accuracy, and convergence central processing unit (CPU) time were considered to compare the different grids based on the inversion results. These showed that the structured grid provided an accurate resistivity model and a complex geometry model no worse than the unstructured grid. Furthermore, if the number of the iterations was the same CPU calculations took less time using the structured grid. Sometimes, the structured grid sometimes needed more iterations than the unstructured grid, but the CPU time costs still less than the unstructured grid. These results show that the structured grid is a better choice to invert marine controlled source electromagnetic data for offshore exploration.

A self-powered 3D activity inertial sensor (3DAIS) is proposed for multi-axis acceleration and rotation inertial sensing. The 3DAIS consists of magnetic buckyballs encapsulated inside a 3D–printed spherical shell, with multi-layers of PTFE, PVDF and Al films fabricated on the inner walls of the shell and wire coils winded on the outside. The device demonstrated good performance in hand motion recognition and human activity state monitoring application. When operating as a 6-axis inertial sensor, the 3DAIS is able to sense X, Y and Z-acceleration during linear motion as well as detect roll, pitch and yaw angular velocity during rotational motion. The device possesses self-powering ability as well and is able to harvest energy through hybrid mechanisms of piezoelectric, electromagnetic and triboelectric from various energy sources such as 3D vibration, rotation and human motion, etc. The proposed 3DAIS can potentially pave the way to an advance motion sensing system with self-powering capability for wearables and healthcare telemedicine applications.

Electromagnetic forward modeling is the cornerstone of geophysical electromagnetic inversion. During the last 50 years, numerical simulation methods have been rapidly developed and widely used in geophysical area as the computational capacity continued to increase, such as from single-core to the most modern multi-core processing cards. This paper reviews the literature of electromagnetic fields simulation, particularly focusing on the forward modeling methods include finite difference method , finite element method, integral equation method, and several hybrid methods. We also discuss the possibility of deep learning methods for EM modeling. By sorting out the work done by the predecessors, this review briefly introduces the basic principles and traces back the development of these methods. We propose a Qualitative Evaluation Model named STAMP Model and some criterias of qualitative evaluation on these methods will be discussed in this model.

The major disadvantage of using traditional linear or quasi-linear methods to perform magnetotelluric data inversion is that these methods heavily depend on the initial models. If a selected initial model is not suitable, these inversion algorithms may fall into a local minimum or diverge during the iterations. Meanwhile, in most geophysical inversions, it is difficult to obtain a proper initial model because of the lack of sufficient prior information. To solve this problem, a hybrid inversion algorithm based on the combined particle swarm optimization and regularized least squares is proposed to invert magnetotelluric data. Particle swarm optimization algorithms have good performances in global searching. More importantly, these algorithms are not sensitive to the initial models. Therefore, this approach can be used to preliminary search the model parameter space. Then, the searched results are used as an initial model for iterations of inversion based on the least square regularization. Both synthetic data and field data tests demonstrated that the hybrid inversion has a good performance. The numerical experiments show that by utilizing the reliable initial model generated from the particle swarm optimization, the search results of hybrid inversion are greatly refined. The hybrid algorithm offers a significant improvement in both inversion efficiency and accuracy. In particular, this algorithm is suitable for the situations that lack initial information while inverting the field magnetotelluric data.

Electromagnetic methods play an important role in mineral exploration and are widely used in the search for metallic resources such as copper, molybdenum, lead-zinc, bauxite, uranium, etc. In this paper, we focus on reviewing the application and development of electromagnetic methods, such as magnetotelluric (MT), audio magnetotelluric (AMT), controlled-source audio magnetotelluric (CSAMT), and transient electromagnetic (TEM), respectively. This paper also presents examples of electromagnetic methods applied to the exploration of metal deposits on land, airborne and in the marine environment. Furthermore, we discuss the future development of electromagnetic prospecting tools, the data processing, modeling and inversion, interpretation, and their application in complex geological environments. The future of successful mineral exploration using EM methods will be focused on concealed and deep target exploration, and possibly one day on resources on the seafloor.

Based on fault initial angle and transition resistance, a novel ultra-high-speed distributed unit transient protection algorithm is established to protect a busbar and a connected transmission line simultaneously for EHV (extra high voltage) substation through analysing the direction and instantaneous amplitude of the fault-generated high-frequency transient current by utilizing SVM (support vector machine). The fault direction was first judged during the process, and then the fault location was determined by employing different trained SVMs. In addition, the fault initial angle and transition resistance are imported into the input vector of SVMs, through which their adverse effects on the protection performance can be significantly eliminated. Moreover, the proposed algorithm extracts the fault transient information just relying on one transmission line connected to the busbar rather than overall feeders, thus simplifying the process while ensuring high reliability. Further, only typical fault samples instead of all samples are needed during the SVM training procedure, which makes it quite appropriate for practical projects. According to massive simulation results on a typical EHV transmission system on ATPDraw platform, the proposed algorithm can precisely determine whether the fault occurs within the protected busbar or on the protected line or outside the protected area.

In the paper, a new non-unit transient protection method suitable for single-phase faults of EHV power transmission lines was proposed based on the analysis of the propagation characteristics induced by fault transient current, the transition resistance and the fault angle on corresponding energy values of high-frequency transient current in extra high voltage (EHV) network. In the procedure, the transient current energy values from both sides of the bus were primarily normalized on the basis of transition resistance and fault angle, and then the characteristic value with functions of direction judge and value comparison was obtained by calculating their difference. By utilizing the characteristic value, the methodology came into being, by which the impacts of both transition resistance and fault angle were eliminated. The overall design has a high reliability level and owns twice the scope of the conventional protection. Simulations were performed and analyzed upon a three-phase 500 kV power system by utilizing ATP/EMTP, with various kinds of typical faults being taken into account. Plenty of results verify the feasibility of the algorithm for ultra-high speed protection of EHV power transmission lines.