Three-Dimensional Inversion of Semi-Airborne Transient Electromagnetic Data Based on a Particle Swarm Optimization-Gradient Descent Algorithm

Semi-airborne transient electromagnetics (SATEM) is a geophysical survey tool known for its ability to perform three-dimensional (3D) observations and collect high-density data in large volumes. However, SATEM processing presently restricted 3D model-driven inversion, which not conducive detailed surveys. This paper presents new model- data-driven inversion algorithm using the particle swarm optimization (PSO) gradient descent (GD) algorithms. PSO used suppress multiplicity of solutions associated with inverse problems, GD employed accelerate convergence process. For PSO-GD algorithm, model-updating equation established cosine probability function introduced as weighting term algorithms ensure smooth transition between two iterative The α-trimmed filter regularization constraint model. stability reliability are verified through numerical simulations. Finally, applied measurements Qinshui coal mine Jincheng, Shanxi Province, China.