Inversão de dados no método Mangnetotelúrico 1D utilizando o algoritmo de otimização global Particle Swarm Optimization

Abstract

This study addresses the application of the 1D magnetotelluric method for the inversion of geophysical data and proposes the use of the Particle Swarm Optimization (PSO) algorithm as an efficient approach to enhance the inversion results. The magnetotelluric method is widely used in investigating the subsurface structure of the Earth by estimating the electrical conductivity of materials in that region. The 1D magnetotelluric data inversion involves modeling the subsurface structure as horizontal layers of constant electrical conductivity, aiming to find the values that best fit the observed data. In this work, the PSO algorithm is proposed for optimizing the estimation of the electrical conductivity distribution. PSO, a global optimization method inspired by swarm behavior, efficiently explores the search space to find the best solution. This study aims to contribute to the resolution and interpretation of 1D inverse problems in the magnetotelluric (MT) method, providing an alternative approach based on global optimization.