Magnetic data inversion based on particle swarm optimization

This paper proposes a new inversion algorithm based on particle swarm optimization with impact constrain in order to avoid the dependency of initial model and local solution of the traditional linear iterative inversion. This algorithm is applied to the inversion of the magnetic data of horizon and vertical tabular body, and yields consistent results with the models. When it is applied to the stepped tabular body inversion, the results remain fairly good. Numerical experiment results demonstrate that this particle swarm optimization inversion algorithm has advantages of independent of initial models, no need for gradient of objective function, and capable of global optimization. It is an effective method for the magnetic data inversion.