Joint inversion of the first overtone and fundamental mode for deep imaging at the Valhall oil field using ambient noise - Archive ouverte HAL Access content directly
Journal Articles Geophysical Journal International Year : 2018

Joint inversion of the first overtone and fundamental mode for deep imaging at the Valhall oil field using ambient noise

(1) , (1) , (2) , (1) , (1) , (1)
1
2

Abstract

Surface waves derived from ambient noise data are composed of fundamental and higher modes. The first overtone is sensitive to structure from the surface down to a greater depth than the fundamental mode. We use 6.5 hr of continuous recording of noise on 2320 ocean bottom cable sensors from the Valhall Life of Field Seismic and we compute the intersensor cross-correlation functions for the vertical and radial components. We observe that the vertical component is dominated by the fundamental mode whereas on the radial component, the first overtone is stronger than the fundamental mode. Forward modelling demonstrates that a few hundred metres of low velocity sediments along with the water layer plays an important role for the generation of stronger first overtone signal on radial component. When we invert only the fundamental mode phase velocity data, the S-wave velocity model has vertical resolution down to 600 m depth. Combining the fundamental mode and the first overtone enables to image deeper structure down to 1 km depth, highlighting the presence of a low velocity zone.
Fichier principal
Vignette du fichier
ggy122.pdf (8.41 Mo) Télécharger le fichier
Origin : Publisher files allowed on an open archive
Loading...

Dates and versions

insu-02274784 , version 1 (30-08-2019)

Identifiers

Cite

Gaurav Tomar, Eléonore Stutzmann, Aurélien Mordret, Jean-Paul Montagner, Satish Singh, et al.. Joint inversion of the first overtone and fundamental mode for deep imaging at the Valhall oil field using ambient noise. Geophysical Journal International, 2018, 214 (1), pp.122-132. ⟨10.1093/gji/ggy122⟩. ⟨insu-02274784⟩
76 View
50 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More