Multi‐parameter reflection waveform inversion for acoustic transversely isotropic media with a vertical symmetry axis

Li, Yuanyuan; Alkhalifah, Tariq

doi:10.1111/1365-2478.12966

Cited by 18 publications

(6 citation statements)

References 50 publications

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“…Therefore, we scale the gradient with the depth-variable weighting factor ( 2 z e , where z indicates the depth) to amplify the deeper parts in both the inner and outer loops of Table 2. As addressed in the former studies, there are strong anisotropic effects at depths of 1  2.5 km in the Volve oil field (Oh et al 2018;Oh and Alkhalifah 2019;Li and Alkhalifah 2020). According to Zhang and Alkhalifah (2017) and…”

Section: Modelling and Inversion Parametersmentioning

confidence: 85%

Two-step full waveform inversion of diving and reflected waves with the diffraction-angle-filtering-based scale-separation technique

Kim

Hwang

Min

et al. 2021

Geophysical Journal International

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Summary Full waveform inversion (FWI) is a highly nonlinear optimization problem that aims to reconstruct high-resolution subsurface structures. The success of FWI in reflection seismology relies on appropriate updates of low-wavenumber background velocity structures, which are generally driven by the diving waves in conventional FWI. On the other hand, the reflected waves mainly contribute to updating high-wavenumber components rather than low-wavenumber components. To extract low-wavenumber information from the reflected waves in addition to the diving waves, we propose a two-step FWI strategy that separates a given model into the reflectivity and background velocity models and then alternately update them using the scale-separation technique based on diffraction-angle filtering (DAF; which was proposed to effectively control wavenumber components of the FWI gradient). Our strategy first inverts the high-wavenumber reflectivity model by suppressing energy at large diffraction angles, which are necessary to compute the reflection wavepaths (i.e., the rabbit-ears-shaped kernels) for low-wavenumber updates in the subsequent stage. Then, we extract low-wavenumber components due to the diving (banana-shaped kernels) and reflected waves (rabbit-ears-shaped kernels) from the gradient by suppressing energy at small diffraction angles. Our strategy is similar to reflection waveform inversion (RWI) in that it separates a given model into high- and low- wavenumber components and uses the rabbit-ears-shaped kernels for low-wavenumber updates. The main difference between our strategy and RWI is that our strategy adopts the DAF-based scale-separation technique in the space domain, which makes our algorithm of using both the banana-shaped and rabbit-ears-shaped kernels computationally attractive. By applying our two-step inversion strategy to the synthetic data from the Marmousi-II model and the real ocean-bottom cable (OBC) data from the North sea, we demonstrate that our method properly reconstructs low-wavenumber structures even if initial models deviate from the true models.

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Section: Modelling and Inversion Parametersmentioning

confidence: 85%

Two-step full waveform inversion of diving and reflected waves with the diffraction-angle-filtering-based scale-separation technique

Kim

Hwang

Min

et al. 2021

Geophysical Journal International

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“…These parameters give a simplified angular dependence of the wave velocities and enable the modeling of nonelliptic wavefronts. However, introducing more parameters in the model increases the ill-posedness of the inversion problem complicating the separation of individual parameters [30]- [32].…”

Section: Introductionmentioning

confidence: 99%

Modeling the Effect of Anisotropy in Ultrasonic-Guided Wave Tomography

Ratassepp¹,

Rao

et al. 2022

IEEE Trans. Ultrason., Ferroelect., Freq. Contr.

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Most of the existing ultrasonic guided wave tomography approaches to map structural changes in plate-like waveguides are based on the assumption of an isotropic material model. However, there are many other engineering applications that are made of anisotropic materials and structures. Applying these techniques on such structures becomes complicated due to the anisotropic wave propagation behavior. The main challenge is to develop a suitable forward model that describes the wave propagation in such material, thereby enabling accurate reconstruction of the material properties. The present study proposes an anisotropic formulation of the acoustic forward model to map velocity variations induced by defects in anisotropic plates. The anisotropic behavior of the waves along the plate is simulated by implementing approximate anisotropic parameters. The velocity reconstruction is based on a full-waveform inversion algorithm, and its performance is investigated in the case of different degrees of anisotropy of the plate material and the defect. The results suggest that the method is highly suitable for imaging velocity changes due to defects. This is found to be the case when the defect has a similar anisotropic structure to the surrounding plate material. The validation experiment is performed on a multilayered composite plate with a circular defect of stiffness reduction using A0 mode, showing a very good performance of the reconstruction algorithm.

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“…With the development of high‐performance computing and wide‐azimuth acquisition, FWI has been widely studied in the past decade. A variety of approaches have been proposed to alleviate the cycle skipping of FWI (Ma and Hale, 2013; Alkhalifah, 2015; Warner and Guasch, 2016; Métivier et al ., 2016; Wu and Alkhalifah, 2018; Li et al ., 2019; Yao et al ., 2019; Song et al ., 2020; Li and Alkhalifah, 2020). It is intuitive to select part of the data free from cycle skipping as the matching objective.…”

Section: Introductionmentioning

confidence: 99%

Extended full waveform inversion with matching filter

Alkhalifah

2021

Geophysical Prospecting

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Full waveform inversion has shown its huge potentials in recovering a high‐resolution subsurface model. However, conventional full waveform inversion usually suffers from cycle skipping, resulting in an inaccurate local minimum model. Extended waveform inversion provides an effective way to mitigate cycle skipping. A matching filter between the predicted and observed data can provide an additional degree of freedom to improve the data fitting and avoid the cycle skipping. We extend the search space to treat the matching filter as an independent variable that we use to bring the compared data within a half cycle to obtain the accurate direction of velocity updates. We formulate the objective function using the penalty method by linearly combining a data‐misfit term and a penalty term. The objective function with a reasonable penalty parameter has a larger region of convergence compared to conventional full waveform inversion. We search for the optimal solution over the extended model by updating the matching filter and the velocity in a nested way. The normalization of the data can bring us an equivalent normalization to the filter and a more effective convergence. In the synthetic Marmousi model, the proposed inversion method recovers the velocity model stably and accurately starting from a linearly increasing model in the case of lack of low frequencies below 3 Hz, in which conventional full waveform inversion suffers from cycle skipping. We also use a marine field data to demonstrate the effectiveness and practicality of the proposed method.

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Multi‐parameter reflection waveform inversion for acoustic transversely isotropic media with a vertical symmetry axis

Cited by 18 publications

References 50 publications

Two-step full waveform inversion of diving and reflected waves with the diffraction-angle-filtering-based scale-separation technique

Two-step full waveform inversion of diving and reflected waves with the diffraction-angle-filtering-based scale-separation technique

Modeling the Effect of Anisotropy in Ultrasonic-Guided Wave Tomography

Extended full waveform inversion with matching filter

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