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Variance-based model interpolation for improved full-waveform inversion in the presence of salt bodies

Oleg Ovcharenko, Vladimir Kazei, Daniel Peter and Tariq Alkhalifah
Variance-based model interpolation for improved full-waveform inversion in the presence of salt bodies
Geophysics (October 2018) 83 (5): R541-R551

Abstract

When present in the subsurface, salt bodies impact the complexity of wave-equation-based seismic imaging techniques, such as least-squares reverse time migration and full-waveform inversion (FWI). Typically, the Born approximation used in every iteration of least-squares-based inversions is incapable of handling the sharp, high-contrast boundaries of salt bodies. We have developed a variance-based method for reconstruction of velocity models to resolve the imaging and inversion issues caused by salt bodies. Our main idea lies in retrieving useful information from independent updates corresponding to FWI at different frequencies. After several FWI iterations, we compare the model updates by considering the variance distribution between them to identify locations most prone to cycle skipping. We interpolate velocities from the surrounding environment into these high-variance areas. This approach allows the model to gradually improve from identifying easily resolvable areas and extrapolating the model updates from those to the areas that are difficult to resolve at early FWI iterations. In numerical tests, our method demonstrates the ability to obtain convergent FWI results at higher frequencies.


ISSN: 0016-8033
EISSN: 1942-2156
Coden: GPYSA7
Serial Title: Geophysics
Serial Volume: 83
Serial Issue: 5
Title: Variance-based model interpolation for improved full-waveform inversion in the presence of salt bodies
Affiliation: King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
Pages: R541-R551
Published: 201810
Text Language: English
Publisher: Society of Exploration Geophysicists, Tulsa, OK, United States
References: 40
Accession Number: 2019-003414
Categories: Applied geophysics
Document Type: Serial
Bibliographic Level: Analytic
Illustration Description: illus.
Country of Publication: United States
Secondary Affiliation: GeoRef, Copyright 2019, American Geosciences Institute.
Update Code: 201904
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