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 proceedingChapter

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 (US)
Title of host publicationAdvanced Methods for Processing and Visualizing the Renewable Energy
PublisherSpringer Singapore
Pages121-145
Number of pages25
ISBN (Print)9789811586057
DOIs
StatePublished - Oct 21 2020

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