Surface Wave Tomography (SWT) is a powerful and well-established technique to retrieve 3D shear-wave velocity models at regional scale from earthquakes and seismic noise measurements. SWT is here applied to 3D active-source data, where higher modes and heterogeneous spatial sampling make phase extraction challenging. First, synthetic traveltimes calculated on a dense, regular-spaced station array are used to test the performance of three different tomography algorithms (linearized inversion, Markov Chain Monte Carlo (MCMC) and Eikonal tomography). The tests suggest that the lowest misfit to the input model is achieved with the MCMC algorithm, at the cost of much longer computational time. Then, real phases are extracted from a 3D exploration dataset at different frequencies. This operation includes an automated procedure to isolate the fundamental mode from higher-order modes, phase unwrapping in two dimensions and the estimation of the zero-offset phase. These phases are used to compute traveltimes between each source-receiver couple, which are input into the previously tested tomography algorithms. The resulting phase velocity maps show good correspondence, highlighting the same geological structures for all three methods. Finally, individual dispersion curves obtained by the superposition of phase velocity maps at different frequencies are depth inverted to retrieve a 3D shear-wave velocity model.
Surface Wave Tomography using 3D active-source seismic data
Ilaria Barone;Giorgio Cassiani
2021
Abstract
Surface Wave Tomography (SWT) is a powerful and well-established technique to retrieve 3D shear-wave velocity models at regional scale from earthquakes and seismic noise measurements. SWT is here applied to 3D active-source data, where higher modes and heterogeneous spatial sampling make phase extraction challenging. First, synthetic traveltimes calculated on a dense, regular-spaced station array are used to test the performance of three different tomography algorithms (linearized inversion, Markov Chain Monte Carlo (MCMC) and Eikonal tomography). The tests suggest that the lowest misfit to the input model is achieved with the MCMC algorithm, at the cost of much longer computational time. Then, real phases are extracted from a 3D exploration dataset at different frequencies. This operation includes an automated procedure to isolate the fundamental mode from higher-order modes, phase unwrapping in two dimensions and the estimation of the zero-offset phase. These phases are used to compute traveltimes between each source-receiver couple, which are input into the previously tested tomography algorithms. The resulting phase velocity maps show good correspondence, highlighting the same geological structures for all three methods. Finally, individual dispersion curves obtained by the superposition of phase velocity maps at different frequencies are depth inverted to retrieve a 3D shear-wave velocity model.Pubblicazioni consigliate
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