Detailed S-wave velocity structure of sediment and crust off Sanriku, Japan by a new analysis method for distributed acoustic sensing data using a seafloor cable and seismic interferometry

Abstract

The S-wave velocity (Vs) structure of sediments and the uppermost crust in the landward slope of a subduction zone are important for determining the dynamics of the overriding plate. Although distributed acoustic sensing (DAS) measurements have improved the horizontal resolution of Vs structure in marine areas, the estimations have been limited to the uppermost sedimentary layers. In the present study, we applied seismic interferometry to DAS data of 13 h duration to image the sedimentary and crustal structure offshore of Sanriku, Japan with a spatial horizontal resolution of 2.5 km and > 3.0 km depth. We grouped the DAS data into 10 km long subarrays with 75% overlaps. We first applied a frequency-wavenumber filter to the DAS data to remove DAS instrumental noise and to allow effective extraction of surface waves from short-time records. We then applied a seismic interferometry method and estimated the phase velocities at each subarray. The estimated phase velocities of the fundamental-mode and first higher-mode Rayleigh waves were then used to determine one-dimensional Vs structures for each subarray. The resultant 2-D Vs structure was interpreted as representing sediments and crust. The upper sedimentary layers thicken seaward, while the entire sedimentary unit shows complex lateral variations in depth. The boundary between the sedimentary layers and the uppermost crust varies in depth from 1.8 to 6.8 km and is the deepest in the middle of the profile. Combining this result with the P-wave velocity (Vp) structure along the nearest survey line, determined in previous studies, allowed us to estimate Vp/Vs = 3.12, on average, for the lower sedimentary layers. Our method of applying seismic interferometry to marine DAS data broadens the techniques for estimating Vs and Vp/Vs structure of sedimentary layers and the upper crust across subduction zones. These results show that application of the frequency-wavenumber filtering and seismic interferometry to marine DAS data can estimate the Vs structure and the Vp/Vs structure, together with standard marine geophysical surveys of sedimentary layers and the upper crust across subduction zones. Graphical Abstract

Development of a simple offshore ground motion prediction equation based on S-net data and residual analysis to reveal site effects

“…5b), a correction term (Ct) was obtained by regressing the distance coe cient with the earthquake type as a dummy variable. (7), where t and ta are regression coe cients. As a result, the following equation is obtained.…”

“…The Pearson correlation coe cients showed < 0.1 at the depths that V S is 600 m/s, 1400 m/s, and 3000 m/s and residuals. Fukushima et al (2022) obtains the detailed shallow V S structures using distributed acoustic sensing off Iwate, with the V S < 0.3 km/s sediment at a depth of 300-500 m below the sea oor in the seaward area (Fig. 9).…”

Using Vehicle‐Induced DAS Signals for Near‐Surface Characterization With High Spatiotemporal Resolution

“…Recent improvements in seismic data processing techniques, such as phase-weighted stacking (PWS) (Sun et al, 2023), continuous wavelet transform noise reduction (Y. Yang et al, 2020), FK (f-k) filtering (Fukushima et al, 2022), and optimal stacking of surface windows (X. Yang et al, 2022), have enhanced the signal-to-noise ratio (SNR) of recorded seismic waves and the clarity of virtual shot gathers.…”

“…Therefore, the method may miss important subsurface information in the high‐frequency range that is relevant for detecting small‐scale and shallow features, such as fractures or cracks. Recent improvements in seismic data processing techniques, such as phase‐weighted stacking (PWS) (Sun et al., 2023), continuous wavelet transform noise reduction (Y. Yang et al., 2020), FK (f‐k) filtering (Fukushima et al., 2022), and optimal stacking of surface windows (X. Yang et al., 2022), have enhanced the signal‐to‐noise ratio (SNR) of recorded seismic waves and the clarity of virtual shot gathers. Nonetheless, these methodologies, developed for “blind” ambient noise interferometry, depend on the analysis of surface waves emanating from undetermined sources.…”

3D VSP Imaging Using DAS Recording of P- and S-Waves in Vertical and Lateral Well Sections in West Texas

“…We noted that S-waves have particle motions along the fiber's sensitivity axis for certain arrival angles and, with shorter wavelengths, may provide higher resolution and attendant shorter gauge length processing. In addition, DAS generally records lower frequencies, allowing broader band assessments [11,12]. Since the incidence angle depends on the shot location and rock velocity, the directly arriving P-wave at the top few receivers is often largely perpendicular, so there is little direct P-wave arrival observed regardless of shot location.…”