Near-surface S-wave velocities estimated from traffic-induced Love waves using seismic interferometry with double beamforming

Abstract

I use ambient noise, especially traffic noise, to estimate the 2D near-surface S-velocity distribution. Nearsurface velocities are useful for understanding structure, stiffness, porosity, and pore pressure for engineering/environmental purposes and static correction of active-source imaging. I extract Love waves propagating between each receiver pair from 12 h of traffic noise using seismic interferometry with power-normalized crosscorrelation. The receiver array contained three parallel lines, each of which had 100 transverse-component geophones. I apply double beamforming to the correlations at the parallel lines for improving the signal-to-noise ratio of the extracted Love waves to satisfy the stationary phase assumption for seismic interferometry. I use these Love waves for a dispersion analysis to estimate a 2D near-surface S-wave velocity model based on the multichannel analysis of surface waves. To improve the lateral resolution of the velocity model, I sort the extracted waves according to common midpoints (CMPs) and limited the maximum offset of receiver pairs. The dispersion analysis at each CMP is based on the assumption of layered media, and using all CMPs, I can estimate high-resolution 2D velocities down to 80 m depth. The velocity variations are similar to the location of strong reflectors obtained by a previous study. The main features of the velocity model are recovered even from 1 h of continuous traffic-noise data, which means that the proposed technique can be used for efficient 4D surveys.

Fault Zone Imaging With Distributed Acoustic Sensing: Surface‐To‐Surface Wave Scattering

“…It is more appropriate to refer to acausal energy as “spurious arrivals,” as it is not part of the true Green's functions between the receivers. For the 1D scenario here, the spurious arrivals appear when there exists a persistent noise source or a passive scatterer between the receivers (Figures 2c and 2d; Ma et al., 2013; Nakata, 2016). The earlier spurious arrival times in the cross‐correlations are the difference between the travel times of the waves from the active source/scatterer to the two receivers (Figures 2c–2e), and are not symmetrical between the positive and negative sides.…”

“…Secondary signals have been observed in noise cross‐correlations and attributed to a persistent active source or passive scattering from material heterogeneities in the shallow crust (Chang et al., 2016; Ma et al., 2013; Nakata, 2016; Retailleau & Beroza, 2021; Zeng & Ni, 2010; Zhan et al., 2010). The cause of the secondary arrivals in our case of a linear DAS array can be simplified as a 1D scenario.…”

Seismic Attenuation Extraction From Traffic Signals Recorded by a Single Seismic Station

“…In addition, seismic ambient noise data contains information about the subsurface and has been used to resolve the underground physical properties. For example, seismic traffic signals have been used for near‐surface imaging (Nakata, 2016; Dou et al., 2017; Y. Zhang et al., 2019), fault imaging (Brenguier et al., 2019), and shallow subsurface Q‐value estimation (Meng et al., 2021).…”

重合前バイブロサイス記録を用いたノイズ除去と表層付近の速度の推定

“…Before desweeping and stacking, these data contain continuous ambient noise data, whichexist restlessly over all the time of data acquisition. The ambient noise have been used toestimate near-surface velocity models (e.g., Nakata, 2016) .…”