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DOI 10.1038/s41598-026-55658-8

Медицинская библиотека · Scientific reports · 2026

Efficient 2D shear-wave velocity subsurface profiling via passive multi-component seismic data.

Dal Moro Giancarlo

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Аннотация

The reconstruction of two-dimensional (2D) subsurface shear-wave velocity (VS) structures remains challenging when relying on surface-based seismic methods, due to limited depth penetration and the intrinsic non-uniqueness associated with the frequent reliance on a single observable. Here we present an efficient technique for the joint acquisition and analysis of multi-component passive seismic data recorded along linear arrays, aimed at obtaining robust subsurface 2D VS models. The method, named 2D SuPPSALA (2D SUbsurface Profiling via Passive Surface-wave data Analysis from Linear Arrays), combines surface-wave dispersion derived from moving subarrays of the deployed array with station-specific spectral ratios within a unified joint inversion framework. The approach can be implemented using either 3-component seismic nodes or traditional cabled systems acquiring vertical and transverse components, provided that sensor response curves are the same. The method is illustrated through a shallow subsurface case study in a perilagoon environment of northeastern Italy, characterized by abrupt lateral variations associated with residual palaeodunes and peat-filled palaeochannels. The resulting 2D VS model clearly images these features, with very low velocities (< 100 m/s) in peat-rich zones and high velocities (> 300 m/s) in stiff sandy deposits. Independent electromagnetic data show good agreement with the seismic profile, providing mutual validation. Compared to conventional refraction or roll-along surface-wave techniques, the proposed methodology provides enhanced depth sensitivity and reduced ambiguity, while relying on simpler field operations that are easily applicable to kilometer-scale profiles.

Для цитирования: Dal Moro Giancarlo. Efficient 2D shear-wave velocity subsurface profiling via passive multi-component seismic data.. Scientific reports. 2026. DOI: 10.1038/s41598-026-55658-8.
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