Reverse time migration of marine models with elastic wave equation and amplitude preservation

Phadke, Suhas; Dhubia, Santosh

doi:10.1190/segam2012-1107.1

Cited by 2 publications

(1 citation statement)

References 8 publications

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“…Even if anisotropy and elasticity are assumed in wavefield migration, such limitations still exist. Consequently, this type of migration often leads to images with poor resolution and unbalanced illumination due to such practical acquisition constraints, even though image amplitudes are more reliable when compared with acoustic and/or isotropic imaging (Lu et al, 2009;Phadke and Dhubia, 2012;Du et al, 2014;Hobro et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Elastic least-squares reverse time migration using the energy norm

Rocha

Sava

2017

SEG Technical Program Expanded Abstracts 2017

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Incorporating anisotropy and elasticity into least-squares migration is an important step toward recovering accurate amplitudes in seismic imaging. An efficient way to extract reflectivity information from anisotropic elastic wavefields exploits properties of the energy norm. We derive linearized modeling and migration operators based on the energy norm to perform anisotropic least-squares reverse time migration (LSRTM) describing subsurface reflectivity and correctly predicting observed data without costly decomposition of wave modes. Imaging operators based on the energy norm have no polarity reversal at normal incidence and remove backscattering artifacts caused by sharp interfaces in the earth model, thus accelerating convergence and generating images of higher quality when compared with images produced by conventional methods. With synthetic and field data experiments, we find that our elastic LSRTM method generates high-quality images that predict the data for arbitrary anisotropy, without the complexity of wave-mode decomposition and with a high convergence rate.

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Section: Introductionmentioning

confidence: 99%

Elastic least-squares reverse time migration using the energy norm

Rocha

Sava

2017

SEG Technical Program Expanded Abstracts 2017

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Elastic least-squares reverse time migration using the energy norm

Rocha

Sava

2018

GEOPHYSICS

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We have developed a least-squares reverse time migration (LSRTM) method that uses an energy-based imaging condition to obtain faster convergence rates when compared with similar methods based on conventional imaging conditions. To achieve our goal, we also define a linearized modeling operator that is the proper adjoint of the energy migration operator. Our modeling and migration operators use spatial and temporal derivatives that attenuate imaging artifacts and deliver a better representation of the reflectivity and scattered wavefields. We applied the method to two Gulf of Mexico field data sets: a 2D towed-streamer benchmark data set and a 3D ocean-bottom node data set. We found LSRTM resolution improvement relative to RTM images, as well as the superior convergence rate obtained by the linearized modeling and migration operators based on the energy norm, coupled with inversion preconditioning using image-domain nonstationary matching filters.

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Reverse time migration of marine models with elastic wave equation and amplitude preservation

Cited by 2 publications

References 8 publications

Elastic least-squares reverse time migration using the energy norm

Elastic least-squares reverse time migration using the energy norm

Elastic least-squares reverse time migration using the energy norm

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