Inversão de dados Gravimétricos usando algoritmo de otimização local Levenberg-Marquardt

Abstract

The Levenberg-Marquardt least squares method is a widely used tool for the iterative solution of nonlinear problems. In this work, we will solve a simple gravimetric inverse problem using the Levenberg-Marquardt method. The algorithm will be implemented, and the inversions will be performed using synthetic data with different types of noise. The results showed that the Levenberg-Marquardt algorithm was effective in converging to stable solutions, even in scenarios with significant levels of noise. The final analysis revealed that the results obtained were consistent and reliable, demonstrating the robustness of the method applied to gravimetry problems