Bayes Meets Tikhonov: Understanding Uncertainty Within Gaussian Framework for Seismic Inversion

Muhammad Izzatullah, Daniel Peter, Sergey Kabanikhin, Maxim Shishlenin

Research output: Chapter in Book/Report/Conference proceedingChapterResearchpeer-review

Abstract

In this chapter, we demonstrate the sound connection between the Bayesian approach and the Tikhonov regularisation within Gaussian framework. We provide a thorough uncertainty analysis to answer the following two fundamental questions: (1) How well is the estimate determined by a posteriori PDF, i.e. by the combination of observed data and a priori information? (2) What are the respective contributions of observed data and a priori information? To support the proposed methodology, we demonstrate it through numerical applications in seismic inversions.

Original languageEnglish
Title of host publicationStudies in Systems, Decision and Control
PublisherSpringer Science and Business Media Deutschland GmbH
Pages121-145
Number of pages25
DOIs
Publication statusPublished - 2021

Publication series

NameStudies in Systems, Decision and Control
Volume320
ISSN (Print)2198-4182
ISSN (Electronic)2198-4190

Keywords

  • Bayesian framework
  • Inverse problems
  • Seismic inversion

OECD FOS+WOS

  • 2.02.AC AUTOMATION & CONTROL SYSTEMS
  • 5.09.WU SOCIAL SCIENCES, INTERDISCIPLINARY

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