Application of PSBP method in high-density two-dimensional resistivity inversion

In nonlinear inversion, neural network algorithm has the shortcomings of easy to fall into local minimum, slow convergence and poor inversion accuracy. To overcome these shortcomings, the Particle Swarm Optimization (PSO) is combined with Back Propagation (BP) neural network to achieve inversion (referred as PSBP). The effectiveness of the PSBP is verified by the classical geoelectric model. Compared with the linear inversion and BP neural network inversion methods, the proposed PSBP method has obvious advantages with good inversion result. ©, 2015, Editorial Board of Jilin University. All right reserved.