Preprints
https://doi.org/10.5194/egusphere-2023-78
https://doi.org/10.5194/egusphere-2023-78
06 Feb 2023
 | 06 Feb 2023
Status: this preprint is open for discussion.

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

Farbod Khosro Anjom, Frank Adler, and Laura Valentina Socco

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.

Farbod Khosro Anjom et al.

Status: open (until 31 Mar 2023)

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Farbod Khosro Anjom et al.

Farbod Khosro Anjom et al.

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Short summary
Seismic surface-waves travel near the free surface and are usually dominant in the records. As a result, they are good candidates for near-surface reconstruction. Most surface wave techniques focus on estimating the S-wave velocity (VS) model and consider the P-wave velocity (VP) model as prior information in the inversion step. Here, we show the application of three surface-wave methods to estimate both VS and VP models. We compare in detail the outcomes and performances of the methods.