2015
DOI: 10.1093/gji/ggv339
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Identification of surface wave higher modes using a methodology based on seismic noise and coda waves

Abstract: Dispersion analysis of Rayleigh waves is performed to assess the velocity of complex structures such as sedimentary basins. At short periods several modes of the Rayleigh waves are often exited. To perform a reliable inversion of the velocity structure an identification of these modes is thus required. We propose a novel method to identify the modes of surface waves. We use the spectral ratio of the ground velocity for the horizontal components over the vertical component (H/V) measured on seismic coda. We the… Show more

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Cited by 38 publications
(29 citation statements)
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“…They appear explicitly in formulae (5) and can be selected as desired to obtain theoretical H/V a la carte in order to identify the wave types that are effectively in the data (see Rivet et al 2015).…”
Section: Experimental H/vmentioning
confidence: 99%
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“…They appear explicitly in formulae (5) and can be selected as desired to obtain theoretical H/V a la carte in order to identify the wave types that are effectively in the data (see Rivet et al 2015).…”
Section: Experimental H/vmentioning
confidence: 99%
“…In fact, the H/V ratio considering only the body waves contributions (see figure 4-a) is very similar to the transfer function for vertical S waves, in partial agreement with Nakamura's (1989) interpretation. Finally, when all the wave types are considered (Spica et al 2015;Rivet et al 2015García-Jerez et al 2016, the H/V ratio is usually dominated by surface wave contributions for frequencies higher than the first maximum, whereas it is dominated by body waves below that frequency (see figure 4-a) .…”
Section: Parametric Analysismentioning
confidence: 99%
“…around the maxima of spectrum, ℎ 0 ( ), Shimizu et al, (2002) proposed an excellent tool for experimentally visualizing 15 the shape of multi-fractal spectrum. By extrapolating curves to zero, the width of the spectrum can be defined as…”
Section: Learning the Fractality Of Signal By Mf-dfa 10mentioning
confidence: 99%
“…where the width of the spectrum is zero for a mono-fractal series (Shimizu et al, 2002;Telesca et al, 2004;Telesca et al, 2015). For q = 1, (ℎ) can be interpreted as a fractal dimension, while q = 2 and q = 3 represents the information dimension and the correlation dimension of a time series, respectively.…”
Section: Learning the Fractality Of Signal By Mf-dfa 10mentioning
confidence: 99%
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