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Tomography of the alpine arc using noise correlations & waveform modelling

Abstract : The primary goal of the thesis is to build high-resolution shear-wave velocity models of the Alpine crust and uppermost mantle using ambient noise based tomography.In this framework, we performed a series of tomographic applications using a large cross-correlation dataset computed from 4 years of noise recorded at 1293 broadband seismic stations across Europe.We first applied a 'classical' ambient noise group velocity tomography.Rayleigh wave group velocity measurements in the period band 5-150 s were inverted to construct group velocity maps.With a Bayesian 1-D depth inversion approach, we determined both the shear-wave velocity and probability of interfaces at each cell of the model.This has allowed to finally establish a high-resolution model of the European crust and uppermost mantle in good agreement with previous localized geophysical studies.Taking advantage of the dense seismic array in the Alpine region, we performed ambient noise Eikonal tomography using Rayleigh wave phase velocity measurements in the period band 7-25 s.With this method, we were able to study the anisotropy of the Alpine crust.We refined the shear wave velocity model of the Alpine crust and uppermost mantle using wave-equation tomography (WET) based on the numerical simulation of 3-D elastic wave propagation.We iteratively improved the initial model by minimizing the phase traveltime differences between the observed and synthetic Rayleigh waves in the period band 10-55 s.We obtained the final model after 15 iterations with a reduction of total misfit ~65%.At crustal and Moho depths, the final model displays several new features and much stronger velocity contrasts, which indicates that this approach can significantly improves the model obtained by classical ambient noise tomography.
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Submitted on : Wednesday, June 5, 2019 - 12:21:57 PM
Last modification on : Sunday, May 1, 2022 - 3:37:53 AM


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  • HAL Id : tel-02148214, version 1



Yang Lu. Tomography of the alpine arc using noise correlations & waveform modelling. Earth Sciences. Université Grenoble Alpes, 2019. English. ⟨NNT : 2019GREAU003⟩. ⟨tel-02148214⟩



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