Affiliation:
1. Centre de Géosciences, MINES ParisTech, PSL Research University, 77305 Fontainebleau, France
Abstract
SUMMARY
Iterative least-squares reverse time migration (LSRTM) is the state-of-the-art linearized waveform inversion method to obtain quantitative subsurface parameters. The main drawback of such an iterative imaging scheme is the significant computational expense of many modelling/adjoint cycles through iterations. In the context of the extended domain, an interesting alternative to LSRTM is the asymptotic linearized direct waveform inversion, providing quantitative results with only a single iteration. This approach was first proposed for constant-density acoustics and recently extended to the variable-density case. The former is based on the application of the asymptotic inverse Born operator, whereas the latter has two more extra steps: building an angle-dependent response of the asymptotic inverse Born operator and then solving a weighted least-squares approach for simultaneous inversion of two acoustic parameters. To examine the importance of accounting for density variations, we compare constant- and variable-density linearized direct waveform inversion techniques applied to a marine real data set from the Eastern Nankai Trough, offshore Japan. The inversion results confirm the efficiency of the asymptotic linearized direct waveform inversion in estimating quantitative parameters within a single iteration. The variable-density direct inversion yields subsurface images that (1) exhibit a superior resolution and (2) better reconstruct the field data than does the constant-density approach, even if the data set does not contain large enough surface offset to fully decompose velocity and density perturbations.
Publisher
Oxford University Press (OUP)
Subject
Geochemistry and Petrology,Geophysics
Cited by
1 articles.
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