Fast Near-Surface Investigation With Surface-Wave Attributes

Papadopoulou, Myrto; Colombero, Chiara; Staring, Myrna; Singer, Julian M.; Eddies, R.; Fliedner, Moritz M.; Janod, F.; Socco, Laura

doi:10.3997/2214-4609.202120128

Cited by 2 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The 50,941 first breaks picked from P2 are plotted in Figure 3b. To extract the surface-wave dispersion curves, we used the automatic algorithm developed by Papadopoulou et al (2021), which applies a moving spatial window on the data and, at each window position, picks a local dispersion curve as the maxima of the dispersion image computed according to Park et al (1998). The code uses automatic data-driven quality control to clean each of the picked curves from noisy data points.…”

Section: First-break and Dispersion-curve Pickingmentioning

confidence: 99%

“…To extract the surface‐wave dispersion curves, we used the automatic algorithm developed by Papadopoulou et al. (2021), which applies a moving spatial window on the data and, at each window position, picks a local dispersion curve as the maxima of the dispersion image computed according to Park et al. (1998).…”

Section: First‐break and Dispersion‐curve Pickingmentioning

confidence: 99%

See 1 more Smart Citation

High‐resolution P‐ and S‐wavefield seismic investigations of a quick‐clay site in southwest of Sweden

Myrto,

Alireza,

Magdalena

et al. 2023

Near Surface Geophysics

View full text Add to dashboard Cite

Seismic investigations were performed at a site in the southwest of Sweden where major quick‐clay landslides have occurred in the past. Given the potential high risk of the area and the presence of medium‐sized infrastructures, the site posed a need for detailed investigations in a wide depth range and in high resolution. A high‐fold seismic survey was designed and conducted along two profiles using 1–2 m receiver and shot spacing in order to retrieve both P‐ and S‐wavefield seismic images from vertical component data. The data were analyzed combining first‐break traveltime tomography and surface‐wave analysis as well as P‐ and S‐wavefield reflection seismic imaging. Using the first breaks, P‐wave velocity (VP) models were estimated, indicating the bedrock topography along the profiles and the sediment characteristics. The S‐wave velocity (Vs) models were estimated from the surface waves and indicated areas of low shear strength. Combined with VP and Vs models, this permits the estimation of VP/VS, a parameter that can indicate areas with high water content, significant for the detection of quick clays and possible liquefaction issues. The results are integrated with the P‐ and S‐wave reflection seismic images and compared with other geophysical investigations such as magnetic and gravity data that were collected along the profiles.This article is protected by copyright. All rights reserved

show abstract

Section: First-break and Dispersion-curve Pickingmentioning

confidence: 99%

Section: First‐break and Dispersion‐curve Pickingmentioning

confidence: 99%

High‐resolution P‐ and S‐wavefield seismic investigations of a quick‐clay site in southwest of Sweden

Myrto,

Alireza,

Magdalena

et al. 2023

Near Surface Geophysics

View full text Add to dashboard Cite

show abstract

Fast and semi-automatic S-wave and P-wave velocity estimations from landstreamer data: a field case from the Middle East

Pace,

Khosro Anjom,

Karimpour

et al. 2024

Front. Earth Sci.

View full text Add to dashboard Cite

Seismic surface and body wave analyses are powerful tools for the geotechnical characterization of sites. The use of landstreamers facilitates the acquisition of dense data sets over large areas. However, efficient processing workflows are needed to estimate 3D velocity models from these massive data sets. For surface wave analysis, the manual picking of dispersion curves (DCs) of large data sets is very time-consuming, whereas the accuracy can be biased by operator choices. We apply a semi-automatic workflow for the analysis, processing, and interpretation of a large-scale landstreamer data set acquired for engineering purposes in the Middle East. The workflow involves the application of a validated automatic DC picking algorithm, and the transformation of the DCs into S- and P-wave velocity models through the wavelength-depth technique. The method has a high level of automation, is data driven and does not require extensive data inversion. Another remarkable benefit is that the auto-picking is more than 1,000 times more efficient than standard manual picking and the estimated velocities are in good agreement with available geotechnical and geophysical information. We conclude that the semi-automatic approach may represent a fast and straightforward method suitable for both research and industrial projects, thus enhancing further collaborations and developments.

show abstract

Fast Near-Surface Investigation With Surface-Wave Attributes

Cited by 2 publications

References 0 publications

High‐resolution P‐ and S‐wavefield seismic investigations of a quick‐clay site in southwest of Sweden

High‐resolution P‐ and S‐wavefield seismic investigations of a quick‐clay site in southwest of Sweden

Fast and semi-automatic S-wave and P-wave velocity estimations from landstreamer data: a field case from the Middle East

Contact Info

Product

Resources

About