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Maximilien LEHUJEUR

Passive imaging of the Mauleon-Arzacq basins, application to the Maupasacq experiment

Supervisor:
Sébastien Chevrot, UMR 5563, Observatoire Midi Pyrénées, GET, Toulouse, France

Major Results

Rayleigh wave and shear wave velocity models of the upper 10 km of the Mauleon-Arzacq basins have been obtained using the Maupasacq dense seismic network. The innovative methods developed in this work provide new tools to analyze and to exploit the passive seismic fields recorded by such dense arrays of seismic sensors.

Abstract

The micro-seismic noise generated by the Atlantic ocean and the Mediterranean sea is the most important part of the signal that was recorded by the Large-N Maupasacq array deployed in the Mauleon-Arzacq basins for 6 months in 2017. Based on this unique data-set we have developed and implemented a novel approach to isolate and extract coherent surface wave wavefronts that travel across a dense array of seismic sensors. The method can separate interfering waves coming from different directions, to provide amplitude and travel time fields for each detected wave front.

 

These developpements could significantly enhance the ability to exploit ambient seismic noise fields recorded by such dense seismic networks both in terms of phase and amplitude and even in situations where the noise source distribution is very heterogeneous. Using this approach, we have obtained Rayleigh wave phase velocity maps for periods between 2 and 9 s, which correlate well with the surface geology at short period (T < 3 s) and reveal the deep architecture of the Arzacq and Mauleon basins at longer periods (T > 4 s). A 3D S-wave model of the upper 10 km of these basins has been obtained by inverting the surface wave velocity maps (paper in prep).
Model of the Rayleigh wave phase velocity over the Mauleon-Arzacq basins. Obtained from coherent surface wave fronts extracted from the ambient micro-seismic noise generated mostly in the Atlantic ocean and Mediterranenan sea.

Eikonal tomography from coherent noise surface wave fields extracted by iterative matched filtering – Application to the large-N Maupasacq array 

Eikonal tomography from coherent noise surface wave fields extracted by iterative matched filtering – Application to the large-N Maupasacq array 

Lehujeur, M., & Chevrot, S. (2020). Eikonal Tomography Using Coherent Surface Waves Extracted From Ambient Noise by Iterative Matched Filtering—Application to the Large-N Maupasacq Array. Journal of Geophysical Research: Solid Earth, 125 (6), e2020JB019363.

keywords: eikonal tomography, ambient noise tomography, surface waves, large‐N arrays

DOI: https://doi.org/10.1029/2020JB019363