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• W2330891910 abstract "This study presents a depth inversion of Scholte wave group and phase velocity maps obtained from cross-correlation of 6.5 hr of noise data from the Valhall Life of Field Seismic network. More than 2 600 000 vertical–vertical component cross-correlations are computed from the 2320 available sensors, turning each sensor into a virtual source emitting Scholte waves. We used a traditional straight-ray surface wave tomography to compute the group velocity map. The phase velocity maps have been computed using the Eikonal tomography method. The inversion of these maps in depth are done with the Neighbourhood Algorithm. To reduce the number of free parameters to invert, geological a priori information are used to propose a power-law 1-D velocity profile parametrization extended with a gaussian high-velocity layer where needed. These parametrizations allowed us to create a high-resolution 3-D S-wave model of the first 600 m of the Valhall subsurface and to precise the locations of geological structures at depth. These results would have important implication for shear wave statics and monitoring of seafloor subsidence due to oil extraction. The 3-D model could also be a good candidate for a starting model used in full-waveform inversions." @default.
• W2330891910 created "2016-06-24" @default.
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• W2330891910 date "2014-07-11" @default.
• W2330891910 modified "2023-10-13" @default.
• W2330891910 title "Ambient noise surface wave tomography to determine the shallow shear velocity structure at Valhall: depth inversion with a Neighbourhood Algorithm" @default.
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• W2330891910 doi "https://doi.org/10.1093/gji/ggu217" @default.
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