Full-Waveform Inversion - Part 3: optimization

TitleFull-Waveform Inversion - Part 3: optimization
Publication TypeJournal Article
Year of Publication2018
AuthorsPhilipp A. Witte, Mathias Louboutin, Keegan Lensink, Michael Lange, Navjot Kukreja, Fabio Luporini, Gerard Gorman, Felix J. Herrmann
JournalThe Leading Edge
Volume37
Number2
Page142-145
Month1
Keywordsdevito, finite-differences, FWI, inversion, Modeling, tutorial
Abstract

This tutorial is the third part of a full-waveform inversion (FWI) tutorial series with a step-by-step walkthrough of setting up forward and adjoint wave equations and building a basic FWI inversion framework. For discretizing and solving wave equations, we use Devito, a Python-based domain-specific language for automated generation of finite-difference code (Lange et al., 2016). The first two parts of this tutorial (Louboutin et al., 2017, 2018) demonstrated how to solve the acoustic wave equation for modeling seismic shot records and how to compute the gradient of the FWI objective function using the adjoint-state method. With these two key ingredients, we will now build an inversion framework that can be used to minimize the FWI least-squares objective function.

Notes

(The Leading Edge)

URLhttps://www.slim.eos.ubc.ca/Publications/Public/Journals/TheLeadingEdge/2018/witte2018fwip3/witte2018fwip3.html
DOI10.1190/tle37020142.1
Citation Keywitte2018fwip3