1887

Abstract

Summary

Generally, the local full-waveform inversion (LFWI) is solved in a deterministic framework, in which a single solution is produced, without quantifying its uncertainties. We propose a multi-step strategy for uncertainty estimation in FWI and we demonstrate its applicability to the acoustic 2D Marmousi model. To cast the LFWI in a probabilistic framework, we use a genetic algorithm driven optimization, combined with a Markov chain Monte Carlo method (Gibbs sampler). The so derived posterior probability distribution (PPD) defines a possible set of starting models for subsequent LFWI which, in turn, transforms the initial set of starting models in a new set of final models exhibiting narrower PPDs and containing the true model.

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/content/papers/10.3997/2214-4609.201601543
2016-05-30
2024-03-29
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References

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