Enhanced multi-offset phase analysis of surface wave data for detection of lateral heterogeneities

Surface wave methods are based on the inversion of observed Rayleigh wave phase-velocity dispersion curves. The goal is to estimate mainly the shear-wave velocity profile of the investigated site. The model used for the interpretation is 1D, hence results obtained wherever lateral variations are present cannot be considered reliable. In this paper, we consider synthetic models having a lateral heterogeneity. When we process the entire corresponding seismogram with a traditional f-k approach, the resulting 1D profile is representative only of the subsurface structure of the largest part of the considered model. This result shows that classical analysis disregards evidences of sharp lateral velocity changes even when they show up in the raw seismograms. In our research, we implemented a novel robust automated method to check the appropriateness of the 1D model assumption and locate the discontinuities. The method has been tested over synthetic models. This new approach is a development of the recent Multi- Offset Phase Analysis (MOPA) with the advantages that it does not need a-priori noise evaluation nor more than one shot. Only once the discontinuities are clearly identified, we confidently perform classical f-k dispersion curve extraction and inversion separately on either side of the discontinuity. Thus the final result, obtained by putting side by side the 1D profiles, is a correct 2D reconstruction of the discontinuous S-wave distribution, with no need for additional ad-hoc hypotheses.