关键词: 瞬变电磁法, 非线性优化算法, 粒子群优化算法, 萤火虫算法, 反演

Abstract:

Transient electromagnetic method(TEM) is a type of time-domain electromagnetic detection method, which is widely used in mineral resource exploration, coal mine, water and mud inrush investigation, karst investigation, and other issues. In conventional TEM data inversion，smoke-ring fast imaging and linear iterative inversion methods are used, which have the disadvantages of low accuracy, easy to fall into local minimum, and large calculation amount of sensitivity matrix. In this paper, a nonlinear optimization algorithm is proposed for transient electromagnetic data inversion, and the particle swarm optimization (PSO) algorithm and firefly algorithm are used for comparative analysis.  Typical three-layer and four-layer geoelectric models are established, and the convergence and anti-noise characteristics of the two methods are analyzed. The research results show that the PSO algorithm has high computational efficiency, however the data processing accuracy is low and the anti-noise ability is poor. The firefly algorithm has great advantages over the PSO algorithm in terms of noise resistance and data processing accuracy. We processed the measured data by using the two methods and compared the results, the above conclusions are verified.

Key words: transient electromagnetic method, nonlinear optimization algorithm, particle swarm optimization algorithm, firefly algorithm, inversion