Shear velocity inversion from ambient seismic noise using RR-PSO: a case study of Nusa Tenggara Island

Abstract

Ridge regression particle swarm optimization (RR-PSO) is an optimization technique based on the simulation of social behavior of some animal swarm that has been successfully used in many different engineering fields. In this study, RR-PSO was used to invert Rayleigh wave phase velocity curves that extracted from ambient seismic noise records to obtain the shear velocity (Vs) profile. The optimization algorithm is relatively faster, stable and the important aspect is that can provide uncertainty information of the inversion results. In order to determine the capabilities of the RR-PSO algorithm, the synthetic simulation was carried out using both noise-free and noise-contaminated data. The validity test includes the calculation of similarity index and estimation of the model uncertainty using their standard deviation. Based on the resulted model, the convergence of RR-PSO algorithm is relatively faster, stable and adaptable to some level of noise and can provide good model estimation of the subsurface. The application of RR-PSO to the real dispersion curve data is carried out in order to determine the seismic crustal structure beneath Nusa Tenggara islands.