Constrained Inversion of Magnetotelluric Data with Artificial Fish Swarm Optimization Method

Inverse problem of magnetotelluric is nonlinear. It’s easy to fall into local minimum and the non-uniqueness of inversion result becomes more serious if using the linear inversion method. In this paper, the artificial fish swarm algorithm is introduced to geophysical inversion, the nonlinear inversion of magnetotelluric data with artificial fish swarm optimization method is proposed. The calculation of the partial derivative is not needed and the inverted parameters can be constrained, which can reduce non-uniqueness of the inversion result. Meanwhile, the search step is improved, and the artificial fish swarm parameters suitable for magnetotelluric inversion are given. Many synthetic data tests prove that the artificial fish swarm inversion algorithm can be used to find the global optimal solution effectively. The real data test shows that this method can be used to process the field data and a good result can be achieved.