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Volume 39 Number 12
  • ISSN: 0263-5046
  • E-ISSN: 1365-2397

Abstract

Summary

Least Squares RTM (LSRTM) is a powerful inversion-based imaging algorithm which minimizes the data misfit between observed seismic recordings and forward-modelled synthetic data. The algorithm, which can be implemented in either data or image domains, carries a fundamental limitation because it is based on a linear inversion theory which cannot accommodate velocity refinement as part of its model update process. Successful application of LSRTM therefore requires highly accurate velocity information, and if the velocity model is in significant error, modelled events will not be aligned kinematically with the observed data, and the algorithm will tend to produce unsatisfactory results.

FWI is another inversion-based algorithm that enjoys widespread industry use. Unlike LSRTM, FWI poses its inverse problem within a non-linear framework whereby it updates the velocity model and associated wave paths throughout its iterative process, gradually aligning modelled events with observed events. With the recent convergence of FWI and LSRTM methodologies, FWI is not only being used as a velocity update tool, but also as a direct imaging tool, thereby achieving two key imaging goals, namely refining the velocity model and deriving a better-quality seismic image. The latter process, which is known as ‘FWI imaging’, has recently been gaining a lot of industry attention as it offers the possibility of high-quality imaging along with workflow simplification.

In this article we will compare and contrast LSRTM and FWI. We conclude that the process of generating the FWI-imaging essentially amounts to nonlinear, data-domain inversion. This recognition facilitates a ready comparison against the data-domain form of LSRTM, the latter being a linear, data-domain inversion.

EAGE Publications BV
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2021-12-01
2024-04-20

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Inversion-based imaging: from LSRTM to FWI imaging
First Break 39, 85 (2021); https://doi.org/10.3997/1365-2397.fb2021096
/content/journals/10.3997/1365-2397.fb2021096
/content/journals/10.3997/1365-2397.fb2021096
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