Abstract

Inversion of pre- and post-stack seismic data for acoustic and shear impedance is highly non-linear and ill-posed. A deterministic inversion of band-limited seismic data produces smooth models which are devoid of high frequency variations observed in well logs. Stochastic inversion methods often based on Gaussian priors can produce high frequencies in the desired model. In this paper we report on the application of two new global optimization schemes, namely, Particle Swarm Optimization (PSO) and Differential Evolution (DE) to the problem of stochastic inversion of post-stack seismic data.