Caractérisation de milieux multiplement diffusants à l'aide de corrélations dans la coda

Abstract : Most of the waves recorded by seismometers are hard to interpret because of the complexity of the propagation medium, especially the late part of the seismic coda. These multiply scattered coda waves are close in nature to the ambient noise. We are applying recent noise correlation techniques to coda waves in order to retrieve information about the scattering medium. We show how the relationship between ambient noise and Green's function can be used in the case of the seismic coda. The quality of the Greens function retrieved by cross correlation of time windows in the coda is a proxy indicating the energy partition in the propagation medium. In particular, we establish a link between the symmetry of the causal and acausal parts of the reconstructed Green's function and the mean free path. We validate this theoretical approach with acoustical 2D numerical simulations. The same approach seems inefficient on a seismological dataset, due to the high S/N ratio and the non optimal repartition of receivers. Hence, we develop an MCMC based algorithm in order to optimally reconstruct the green's function in the seismic coda.
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Vincent Clerc. Caractérisation de milieux multiplement diffusants à l'aide de corrélations dans la coda. Tectonique. Université Grenoble Alpes, 2017. Français. ⟨NNT : 2017GREAU011⟩. ⟨tel-01686287⟩

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