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      Seismic tomography using variational inference methods

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          Abstract

          Seismic tomography is a methodology to image the interior of solid or fluid media, and is often used to map properties in the subsurface of the Earth. In order to better interpret the resulting images it is important to assess imaging uncertainties. Since tomography is significantly nonlinear, Monte Carlo sampling methods are often used for this purpose, but they are generally computationally intractable for large datasets and high-dimensional parameter spaces. To extend uncertainty analysis to larger systems we use variational inference methods to conduct seismic tomography. In contrast to Monte Carlo sampling, variational methods solve the Bayesian inference problem as an optimization problem, yet still provide probabilistic results. In this study, we applied two variational methods, automatic differential variational inference (ADVI) and Stein variational gradient descent (SVGD), to 2D seismic tomography problems using both synthetic and real data and we compare the results to those from two different Monte Carlo sampling methods. The results show that variational inference methods can produce accurate approximations to the results of Monte Carlo sampling methods, but in a significantly more efficient way. We expect that the methods can be applied fruitfully to many other types of geophysical inverse problems.

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          Long-range correlations in the diffuse seismic coda.

          The late seismic coda may contain coherent information about the elastic response of Earth. We computed the correlations of the seismic codas of 101 distant earthquakes recorded at stations that were tens of kilometers apart. By stacking cross-correlation functions of codas, we found a low-frequency coherent part in the diffuse field. The extracted pulses have the polarization characteristics and group velocities expected for Rayleigh and Love waves. The set of cross-correlations has the symmetries of the surface-wave part of the Green tensor. This seismological example shows that diffuse waves produced by distant sources are sufficient to retrieve direct waves between two perfectly located points of observation. Because it relies on general properties of diffuse waves, this result has potential applications in other fields.
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            Seismic tomography with the reversible jump algorithm

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              A 3-D shear velocity model of the crust and uppermost mantle beneath the United States from ambient seismic noise

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                Author and article information

                Journal
                22 August 2019
                Article
                1908.08356
                6c0e2389-d72c-49db-8bdb-3a6b00d15575

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

                History
                Custom metadata
                22 pages, 14 figures
                physics.geo-ph physics.comp-ph

                Geophysics,Mathematical & Computational physics
                Geophysics, Mathematical & Computational physics

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