Inversion of 2D Magnetotelluric (MT) Data with Axial Anisotropy using Adaptive Particle Swarm Optimization (PSO)

Zhou，Yan1; Gross，Lutz2; Codd，Andrea2

2024-07-01

10.1016/j.jappgeo.2024.105401

Journal of Applied Geophysics   影响因子和分区

0926-9851

In the presence of anisotropic resistivity structures, Magnetotelluric (MT) data inversion based on an isotropic resistivity model will be insufficient. Recent work on anisotropic MT inversions is primarily conducted using gradient-based, deterministic methods which may converge towards local minima and in general, suffer from ill-posedness of the inversion problem. Alternatively, meta-heuristical methods, such as Particle Swarm Optimization (PSO), are able to find the global minima of cost function. At the same time, they are easy to implement and do not require access to the dense Jacobian (and Hessian) matrix as needed by deterministic inversion methods. In this paper we propose PSO inversion for the anisotropic MT inversion problem using an adaptive inertia weights control strategy to balance exploration and exploitation during the PSO search. Higher order differential regularization is introduced with a Gaussian filter, where the conventional first order, Occam-like regularization term is replaced by a variance term. We investigate the performance of the proposed PSO inversion for an isotropic as well as an axial anisotropic synthetic case to demonstrate improvements over an Occam-like regularization. For the COPROD2 benchmark data set, the proposed PSO inversion can not only reproduce the extend of the North American Central Plains (NACP) conductive anomaly, but also to predict an anisotropy ratio of two orders of magnitude, which is in accordance with laboratory findings.

Anisotropy Inversion Magnetotelluric Particle swarm optimization

SCI ; EI

英语

第一 ; 通讯

20242116115210

Cost functions ; Global optimization ; Heuristic algorithms ; Heuristic methods ; Jacobian matrices ; Magnetotellurics ; Particle swarm optimization (PSO)

Geophysics:481.3 ; Computer Software, Data Handling and Applications:723 ; Computer Programming:723.1 ; Algebra:921.1 ; Optimization Techniques:921.5 ; Physical Properties of Gases, Liquids and Solids:931.2

GEOSCIENCES

2-s2.0-85193436842

Scopus

1.Department of Earth and Space Sciences,Southern University of Science and Technology,Shenzhen,China
2.School of Mathematics and Physics,The University of Queensland,Brisbane,Australia

Zhou，Yan,Gross，Lutz,Codd，Andrea. Inversion of 2D Magnetotelluric (MT) Data with Axial Anisotropy using Adaptive Particle Swarm Optimization (PSO)[J]. Journal of Applied Geophysics,2024,226.

Zhou，Yan,Gross，Lutz,&Codd，Andrea.(2024).Inversion of 2D Magnetotelluric (MT) Data with Axial Anisotropy using Adaptive Particle Swarm Optimization (PSO).Journal of Applied Geophysics,226.

Zhou，Yan,et al."Inversion of 2D Magnetotelluric (MT) Data with Axial Anisotropy using Adaptive Particle Swarm Optimization (PSO)".Journal of Applied Geophysics 226(2024).