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DTIC ADA569446: Development and Tuning of a 3D Stochastic Inversion...
by Defense Technical Information Center
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The development of three-dimensional (3D) seismic models
for the crust and upper mantle has traditionally focused
on finding one model that provides the best fit to the
data, while observing some regularization constraints.
Such deterministic models, however, ignore a fundamental
property of many inverse problems in geophysics:
nonuniqueness. It is likely that if a model can be found
to satisfy given datasets, an infinite number of
alternative models will exist that satisfy the datasets
equally well. Our solution to the inverse problem of
developing a seismic model for the Barents Sea, given
various datasets, is therefore a probabilistic model, a
posterior distribution of models that satisfy the data to
the same degree. We use a Markov Chain Monte Carlo
algorithm to sample the unknown posterior distribution,
which describes the ensemble of models that are in
agreement with prior information and the datasets.
Date Published: 2018-09-04 10:56:40
Identifier: DTIC_ADA569446
Item Size: 21540686
Language: english
Media Type: texts
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