Ambient noise multimode Rayleigh and Love wave tomography to determine the shear velocity structure above the Groningen gas field

Author(s):  
M. Chmiel ◽  
A. Mordret ◽  
A. Boué ◽  
P. Boué ◽  
F. Brenguier ◽  
...  
2021 ◽  
Author(s):  
Y Behr ◽  
John Townend ◽  
S Bannister ◽  
Martha Savage

Ambient noise correlation has been successfully applied in several cases to regions with dense seismic networks whose geometries are well suited to tomographic imaging. The utility of ambient noise correlation-based methods of seismic imaging where either network or noise field characteristics are less ideal has yet to be fully demonstrated. In this study, we focus on the Northland Peninsula of New Zealand using data from five seismographs deployed in a linear pattern parallel to the direction from which most of the ambient noise arrives. Shear wave velocity profiles computed from Rayleigh and Love wave dispersion curves using the Neighborhood Algorithm are in good agreement with the results of a previous active source refraction experiment and a teleseismic receiver function and surface wave analysis. In particular, we compute a path-averaged Moho depth of ̃28 km along a ̃250 km profile. The use of both Rayleigh and Love wave measurements enables us to estimate the degree of radial anisotropy in the crust, yielding values of 2-15%. These results demonstrate that ambient noise correlation methods provide useful geophysical constraints on lithospheric structure even for nonoptimal network geometries and noise field characteristics. © 2010 by the American Geophysical Union.


2021 ◽  
Author(s):  
Y Behr ◽  
John Townend ◽  
S Bannister ◽  
Martha Savage

Ambient noise correlation has been successfully applied in several cases to regions with dense seismic networks whose geometries are well suited to tomographic imaging. The utility of ambient noise correlation-based methods of seismic imaging where either network or noise field characteristics are less ideal has yet to be fully demonstrated. In this study, we focus on the Northland Peninsula of New Zealand using data from five seismographs deployed in a linear pattern parallel to the direction from which most of the ambient noise arrives. Shear wave velocity profiles computed from Rayleigh and Love wave dispersion curves using the Neighborhood Algorithm are in good agreement with the results of a previous active source refraction experiment and a teleseismic receiver function and surface wave analysis. In particular, we compute a path-averaged Moho depth of ̃28 km along a ̃250 km profile. The use of both Rayleigh and Love wave measurements enables us to estimate the degree of radial anisotropy in the crust, yielding values of 2-15%. These results demonstrate that ambient noise correlation methods provide useful geophysical constraints on lithospheric structure even for nonoptimal network geometries and noise field characteristics. © 2010 by the American Geophysical Union.


2019 ◽  
Vol 124 (8) ◽  
pp. 8358-8375 ◽  
Author(s):  
Kayla J. Crosbie ◽  
Geoffrey A. Abers ◽  
Michael Everett Mann ◽  
Helen A. Janiszewski ◽  
Kenneth C. Creager ◽  
...  

2013 ◽  
Vol 195 (2) ◽  
pp. 1300-1313 ◽  
Author(s):  
Nicholas Harmon ◽  
Mariela Salas De La Cruz ◽  
Catherine Ann Rychert ◽  
Geoffrey Abers ◽  
Karen Fischer

2019 ◽  
Vol 218 (3) ◽  
pp. 1781-1795 ◽  
Author(s):  
M Chmiel ◽  
A Mordret ◽  
P Boué ◽  
F Brenguier ◽  
T Lecocq ◽  
...  

SUMMARY The Groningen gas field is one of the largest gas fields in Europe. The continuous gas extraction led to an induced seismic activity in the area. In order to monitor the seismic activity and study the gas field many permanent and temporary seismic arrays were deployed. In particular, the extraction of the shear wave velocity model is crucial in seismic hazard assessment. Local S-wave velocity-depth profiles allow us the estimation of a potential amplification due to soft sediments. Ambient seismic noise tomography is an interesting alternative to traditional methods that were used in modelling the S-wave velocity. The ambient noise field consists mostly of surface waves, which are sensitive to the Swave and if inverted, they reveal the corresponding S-wave structures. In this study, we present results of a depth inversion of surface waves obtained from the cross-correlation of 1 month of ambient noise data from four flexible networks located in the Groningen area. Each block consisted of about 400 3-C stations. We compute group velocity maps of Rayleigh and Love waves using a straight-ray surface wave tomography. We also extract clear higher modes of Love and Rayleigh waves. The S-wave velocity model is obtained with a joint inversion of Love and Rayleigh waves using the Neighbourhood Algorithm. In order to improve the depth inversion, we use the mean phase velocity curves and the higher modes of Rayleigh and Love waves. Moreover, we use the depth of the base of the North Sea formation as a hard constraint. This information provides an additional constraint for depth inversion, which reduces the S-wave velocity uncertainties. The final S-wave velocity models reflect the geological structures up to 1 km depth and in perspective can be used in seismic risk modelling.


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