Interface-wave dispersion curves inversion based on nonlinear Bayesian theory

This paper applies a dataset of ocean ambient noise data to extract interface-wave dispersion curves using time-frequency analysis.The nonlinear Bayesian inversion is applied to estimate seabed sediment parameters such as thickness,shear-wave velocity,compression wave velocity and density,and their uncertainties from interface-wave dispersion curves.The maximum a posterior (MAP) model and marginal probability distributions of parameters are estimated using posterior probability densities computed by adaptive simplex simulated annealing and Metropolis-Hastings sampling methods.The Bayesian information criterion is applied to determine the optimal model that fully explains the observed data by the different parameterizations.The inversion results indicate that 3-uniform-layer model is chosen as the preferred parameterization.The resolution of inversion is up to 800 m-depth.The shear-wave velocity and layer thickness have fewer uncertainties and are more sensitive to the interface wave dispersion than the compression wave velocity and density.