Surface wave tomography to retrieve near surface velocity models

Socco, Laura; Boiero, Daniele; Bergamo, Paolo; Garofalo, Flora; Yao, Huajian; Hilst, Robert D. van der; Col, F. Da

doi:10.1190/segam2014-1278.1

Cited by 12 publications

(4 citation statements)

References 20 publications

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“…Beyond this, surface wave tomography (SWT) is an alternative tool for the spatial estimation of both group and phase velocity in a survey area, leading to a quasi‐3D Vs image of the subsurface. It is a well‐established method in global and regional seismological studies, using passive sources (Bensen et al., 2008; Jin & Gaherty, 2015; Ritzwoller & Levshin, 1998; Yao et al., 2008), and in recent years it has become increasingly attractive for use in oil and gas exploration, as well as in mineral exploration, both in active and passive seismic surveys (Da col et al., 2019; Hollis et al., 2018; Ikeda & Tsuji, 2019; Mordret et al., 2013; Ikeda & Tsuji, 2018; Orfanos et al., 2016; Socco et al., 2014).…”

Section: Introductionmentioning

confidence: 99%

Common‐midpoint cross‐correlation stacking tomography: A 3D approach for frequency‐dependent mapping of Rayleigh waves, group and phase velocity throughout an active seismic network

Leontarakis

Orfanos

Αποστολόπουλος

2022

Near Surface Geophysics

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Shear‐wave velocity constitutes an important characterization parameter in terms of engineering properties. Several techniques of surface wave analysis have been widely adopted for building near‐surface 1D, or even 2D, S‐wave velocity models, but comparable 3D approaches, such as the surface wave tomography (SWT) method, are usually limited to global or regional seismological studies. Moreover, a reliable 3D subsurface imaging in a complex and noisy near‐surface environment becomes difficult when using the fully automated processing techniques that are commonly suggested for the SWT method. Here, a new strategy that is well adapted to geotechnical investigations is proposed to accomplish automatically the frequency‐dependent mapping of Rayleigh waves, both for group and phase velocity, throughout an active seismic network. The specific methodology can be implemented in both 2D and 3D active seismic data acquisition schemes involving both uniform and non‐uniform layouts of receivers. It combines the advantages of a newly created common‐midpoint (CMP) cross‐correlation (CC) analysis technique, with the precision of the travel‐time tomography method that is usually used in regional seismological studies. The main analysis is based on partitioning the different wave propagation directions, weighting the CC frequency–velocity analysis around one‐wavelength and stacking the CMP dispersion images. The tomographic inversion is applied to frequency‐dependent virtual travel‐times, produced from the azimuth‐dependent results of the specific analysis, in order to generate, as output, the local dispersion curves. The output of the proposed processing method can be interpreted with any preferred inversion algorithm for group and phase velocity, either individually or jointly. Simple synthetic tests together with a 3D seismic experiment in well‐known conditions, using standard refraction and multichannel analysis of surface waves (MASW) equipment, confirmed the effectiveness of the proposed methodology in detecting both lateral and vertical S‐wave velocity variations. A ‘construction site’ case study finally highlighted the potential of the new tool in a very difficult and noisy environment.

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Section: Introductionmentioning

confidence: 99%

Common‐midpoint cross‐correlation stacking tomography: A 3D approach for frequency‐dependent mapping of Rayleigh waves, group and phase velocity throughout an active seismic network

Leontarakis

Orfanos

Αποστολόπουλος

2022

Near Surface Geophysics

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“…Gouédard et al (2012) applied eikonal tomography to a highresolution exploration dataset acquired in Oman. Socco et al (2014) proposed the application of surface wave tomography to a 2-D active seismic dataset as an alternative to classical MASW, with the aim of imaging an Alpine fault in New Zealand. Rector et al (2015) used surface wave tomography to image voids in an old mine working site in Nevada (USA).…”

Section: Introductionmentioning

confidence: 99%

Tackling Lateral Variability Using Surface Waves: A Tomography-Like Approach

et al. 2021

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Lateral velocity variations in the near-surface reflect the presence of buried geological or anthropic structures, and their identification is of interest for many fields of application. Surface wave tomography (SWT) is a powerful technique for detecting both smooth and sharp lateral velocity variations at very different scales. A surface-wave inversion scheme derived from SWT is here applied to a 2-D active seismic dataset to characterize the shape of an urban waste deposit in an old landfill, located 15 km South of Vienna (Austria). First, the tomography-derived inverse problem for the 2-D case is defined: under the assumption of straight rays at the surface connecting sources and receivers, the forward problem for one frequency reduces to a linear relationship between observed phase differences at adjacent receivers and wavenumbers (from which phase velocities are straightforwardly derived). A norm damping regularization constraint is applied to ensure a smooth solution in space: the choice of the damping parameter is made through a minimization process, by which only phase variations of the order of the average wavelength are modelled. The inverse problem is solved for each frequency with a weighted least-squares approach, to take into account the data error variances. An independent multi-offset phase analysis (MOPA) is performed using the same dataset, for comparison: pseudo-sections from the tomography-derived linear inversion and MOPA are very consistent, with the former giving a more continuous result both in space and frequency and less artefacts. Local dispersion curves are finally depth inverted and a quasi-2-D shear wave velocity section is retrieved: we identify a well-defined low velocity zone and interpret it as the urban waste deposit body. Results are consistent with both electrical and electromagnetic measurements acquired on the same line.

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“…In the context of earthquake seismology, SWT is a well-stablished method for VS reconstruction of the crust and upper mantel (Wespestad et al, 2019;Bao et al, 2015;Boiero, 2009;Yao et al, 2008;Shapiro et al, 2005). Recently, a few authors showed the application of SWT for the near-surface characterization, using active (Da Col et al, 2019;Socco et al, 2014;Khosro Anjom et al, 2021) and passive data (Badal et al, 2013;Picozzi et al, 2009;Colombero et al, 2022).…”

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confidence: 99%

“…The multi-channel processing stage is repeated to estimate DCs at different locations, which are then inverted individually (e.g., fast simulated annealing of Beaty et al, 2002) or simultaneously (e.g., LCI of Socco et al, 2009) to estimate S-wave velocity (VS) model. For SWT, DC are estimated using the two-station processing method, in which the recordings of receiver couples aligned with sources are considered to estimate many path-averaged DCs that are later inverted using a tomographic scheme to estimate directly (Boschi and Ekstrom, 2002;Fang et al, 2015;Boiero, 2009;Socco et al, 2014;Karimpour et al, 2022) or indirectly (Yoshizawa and Kennett, 2004;Shapiro and Ritzwoller, 2002;Yao et al, 2008) Here, we show the application of the three surface-wave methods, (W/D, LCI, and SWT), to estimate both VS and VP models.…”

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confidence: 99%

S- and P-wave velocity model estimation from seismic surface-waves

Anjom

Adler

Socco

2023

Preprint

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Abstract. The surface-waves methods are well-established techniques for subsurface S-wave velocity (VS) reconstruction. Recently, the sensitivity of surface-wave skin depth to Poisson ratio was applied to also estimate P-wave velocity (VP) models from surface-wave records. We use this technique within the framework of three surface-wave methods, the wavelength/depth data transform, the laterally constrained inversion, and surface-wave tomography to estimate both VS and VP models. We apply these methods to a 3-D test data set from a mining site that is characterized by stiff material and by significant elevation contrast. The data were recorded using a regular grid of receivers and an irregular source layout. Pseudo 3D VS and VP models were obtained down to 140 m depth over approximately 900 × 1500 m2 area. The estimated models from the methods well-match the geological information available for the site. Less than 6 % difference is observed between the estimated VS models from the three methods, whereas this value is 7.1 % for the retrieved VP models. The different methods are critically compared in terms of resolution and efficiency.

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Surface wave tomography to retrieve near surface velocity models

Cited by 12 publications

References 20 publications

Common‐midpoint cross‐correlation stacking tomography: A 3D approach for frequency‐dependent mapping of Rayleigh waves, group and phase velocity throughout an active seismic network

Common‐midpoint cross‐correlation stacking tomography: A 3D approach for frequency‐dependent mapping of Rayleigh waves, group and phase velocity throughout an active seismic network

Tackling Lateral Variability Using Surface Waves: A Tomography-Like Approach

S- and P-wave velocity model estimation from seismic surface-waves

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