From constant- to variable-density inverse extended Born modeling

Farshad, Milad; Chauris, Hervé

doi:10.1190/geo2019-0489.1

Cited by 7 publications

(1 citation statement)

References 44 publications

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“…Many forward modelling methods, most of them for the ultrasound imaging, have been developed with variable density (Kwon and Jeong, 1998; Lavarello and Oelze, 2009; Mojabi and LoVetri, 2015; Rao et al ., 2020). In recent years, some studies about integral equation methods for seismic forward modelling with variable density have been considered in several publications (Yang et al ., 2016; Yao et al ., 2016; Sun et al ., 2017; Jiménez et al ., 2018; Luo and Wu, 2018; Farshad and Chauris, 2020). Although these studies have been developed, there is still an important need to develop more accurate and efficient methods for seismic forward modelling with variable density.…”

Section: Introductionmentioning

confidence: 99%

Homotopy scattering series for seismic forward modelling with variable density and velocity

Xiang

Eikrem

Jakobsen

et al. 2021

Geophysical Prospecting

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We have derived a convergent scattering series solution for the frequency-domain wave equation in acoustic media with variable density and velocity. The convergent scattering series solution is based on the homotopy analysis of a vectorial integral equation of the Lippmann-Schwinger type. By using the Green's function and partial integration, we have derived the vectorial integral equation of the Lippmann-Schwinger type that involves the pressure gradient field as well as the pressure field from the wave equation. The vectorial Lippmann-Schwinger equation can in principle be solved via matrix inversion, but the computational cost of matrix inversion scales like N 3 , where N is the number of grid blocks. The computational cost can be significantly reduced if one solves the vectorial Lippmann-Schwinger equation iteratively. A simple iterative solution is the Born series, but it is only convergent when the scattering potential is sufficiently small. In this study, we have used the so-called homotopy analysis method to derive an iterative solution for the vectorial Lippmann-Schwinger equation which can be made convergent even in strongly scattering media. The computational cost of our convergent scattering series scales as N 2 . Our algorithm, which is based on the homotopy analysis method, involves a convergence control operator that we select using hierarchical matrices. We use a three-layer model and a resampled version of the SEG/EAGE salt model to show the performance of the developed convergent scattering series.

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Section: Introductionmentioning

confidence: 99%

Homotopy scattering series for seismic forward modelling with variable density and velocity

Xiang

Eikrem

Jakobsen

et al. 2021

Geophysical Prospecting

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Accelerating the multi-parameter least-squares reverse time migration using an appropriate preconditioner

Farshad

Chauris

2021

Comput Geosci

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The importance of including density in multiparameter asymptotic linearized direct waveform inversion: a case study from the Eastern Nankai Trough

Farshad

Chauris

Noble

2021

Geophysical Journal International

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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 modeling/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 dataset 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) exhibits a superior resolution and (2) better reconstructs the field data than does the constant-density approach, even if the dataset does not contain large enough surface offset to fully decompose velocity and density perturbations.

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From constant- to variable-density inverse extended Born modeling

Cited by 7 publications

References 44 publications

Homotopy scattering series for seismic forward modelling with variable density and velocity

Homotopy scattering series for seismic forward modelling with variable density and velocity

Accelerating the multi-parameter least-squares reverse time migration using an appropriate preconditioner

The importance of including density in multiparameter asymptotic linearized direct waveform inversion: a case study from the Eastern Nankai Trough

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