I. Des, C. De, . Dispersion, and . Un-mod-`-elemod-`, MOD`ELE 3-D V S différentes méthodes, qu'on la mesure avec la méthode des fonctions récepteurs ou avec la méthode de la corrélation de bruit

. Au-contraire, lorsque la position de la source est connue, la méthode du beamforming permet par exemple d'´ etudier la déviation du rai par

. Le, 2014) utilisent le réseau dense USArray pour effectuer des mesures de beamforming sur des données de téléséismes. Ils montrent que les déviations obtenues sont duesàduesà des hétérogénéités situéessituées`situéesà l'intérieur de leur réseau, maiségalementàmaiségalementmaiségalement`maiségalementà l'extérieur. L'utilisation des corrélations de bruit nous permet de nous affranchir des hétérogénéités situéessituées`situéesà l'extérieur du réseau. En effet, avec la corrélation de bruit, chaque station peut-? etre considérée comme une source et les trajets ne se propagent alors qu

. Nous-pouvons-donc-mesurer-l-'erreur-sur-la-mesure-du-backazimut-obtenue, L'erreur sur la lenteur ne nous intéresse pas dans notre cas Le résultat du beamforming est normalisé, sa valeur maximum est donc de 1. Pour calculer l'erreur, nous considérons le profil d'intensité le long du vecteur lenteur correspondant au maximum d'intensité (Figure 4.9.b le long du trait noir sur la figure 4.9.a). L'erreur est alors calculée comme l

. Les-paramètres-d, inversion ont une forte influence sur la reconstruction des déviations dans le modèle de vitesse final. Les amplitudes des hétérogénéités du modèle sont fortement dépendantes des paramètres de lissage de l'inversion. Il serait

. Dans-la-même-optique, la taille du maillage utilisé joue sur la granularité du modèle reconstruit. Les déviations de rais sont sensibles au gradient de la vitesse, et introduire une granularité plus forte

L. Partie-est-du-massif, Central montre des profils de vitesse d'ondes S atypiques. La croûte y est amincie (de 21à21`21à 25 km d'´ epaisseur)

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