Retrieving lateral variations from surface wave dispersion curves‡

Surface wave analysis is usually applied as a 1D tool to estimate V_S profiles. Here we evaluate the potential of surface wave analysis for the case of lateral variations. Lateral variations can be characterized by exploiting the data redundancy of the ground roll contained in multifold seismic data. First, an automatic processing procedure is applied that allows stacking dispersion curves obtained from different records and which retrieves experimental uncertainties. This is carried out by sliding a window along a seismic line to obtain an ensemble of dispersion curves associated to a series of spatial coordinates. Then, a laterally constrained inversion algorithm is adopted to handle 2D effects, although a 1D model has been assumed for the forward problem solution. We have conducted different tests on three synthetic data sets to evaluate the effects of the processing parameters and of the constraints on the inversion results. The same procedure, applied to the synthetic data, was then tested on a field case. Both the synthetic and field data show that the proposed approach allows smooth lateral variations to be properly retrieved and that the introduction of lateral constraints improves the final result compared to individual inversions.