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Velocity spectra and seismic‐signal identification for surface‐wave analysis
Author(s) -
Dal Moro G.,
Forte E.,
Pipan M.,
Sugan M.
Publication year - 2006
Publication title -
near surface geophysics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.639
H-Index - 39
eISSN - 1873-0604
pISSN - 1569-4445
DOI - 10.3997/1873-0604.2005048
Subject(s) - geology , rayleigh wave , dispersion (optics) , surface wave , synthetic data , frequency domain , group velocity , geophysics , computational physics , seismology , mathematical analysis , physics , optics , algorithm , mathematics
Rayleigh‐wave dispersion is observed every time acoustic‐impedance stratification occurs, and its analysis is suitable for vertical shear‐wave profile reconstruction. Accurate dispersion‐curve identification is essential in order to properly determine the shear‐wave velocity distribution of a medium. Data sets characterized by several events generate complex velocity spectra that can lead to possible misinterpretations. We analyse a real data set by taking into account theoretical dispersion curves and synthetic data obtained from numerical simulations in order to avoid possible pitfalls that could arise from the complex trends exhibited in the f − k (frequency–wavenumber) and v − f (velocity–frequency) domains. In the v − f domain in particular, we show that reflection events and their multiples generate coherences that could be misinterpreted because of their similarity to typical higher‐mode dispersion curves. Another observed signal is interpreted in terms of guided waves and related phenomena. The results of the fundamental‐mode dispersion curve inversion performed via genetic algorithms indicate a sedimentary cover stratification that simple reflection analysis cannot reveal. The present case study highlights the importance of a synergic approach, based on integrated synthetic and field data analysis, for correct interpretation of all the wavefield components in the velocity spectrum.