Computational strategies for reverse‐time migration

Symes, William W.; Denel, Bertrand; Cherrett, Adam; Dussaud, Eric; Williamson, Paul; Singer, Paul Frank; Lemaistre, L.

doi:10.1190/1.3059336

Cited by 94 publications

(35 citation statements)

References 15 publications

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“…It is only necessary to store the wavefield values of the layers. And the number of layers required can be determined by half of the number of the spatial order of the finite diffierence approximation used (Dussaud et al 2008). For instance, the order in space of the finite difference scheme used in this paper is ten, therefor we just need to store five layers of wavefield value at each time step for the top absorbing boundary.…”

Section: Fig3 Snapshots Corresponding To First Shotmentioning

confidence: 99%

Reverse Time Migration Based Ultrasonic Wave Detection for Concrete Structures

Chen

Pan

2014

Design, Construction, and Maintenance of Bridges

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Ultrasonic wave testing is a classic NDT method to detect, locate and monitor the crack/fracture in construction materials. In this paper, a new ultrasound data interpretation technique is introduced: The reverse time migration (RTM) is a wave equation based pre-stack method used in seismic exploration. Since RTM can utilize all kinds of waves, such as reflection waves, refraction waves and diffraction waves, it has no dip limits in migration and can image the inside of complicated structures. However, the large data generation and sophisticated velocity field analysis are the bottlenecks for RTM that hinder its wide applications. A hybrid boundary condition (including random boundary and absorption boundary simultaneously) is suggested in this paper to reconstruct the source wave field to address the memory storage issues. A numerical model with S-shaped internal fracture is presented to demonstrate the technique for detection of internal flaws. The results indicate that the accuracy of detecting the embedded flaw within construction material is affected by the sampling space and the range of wave frequency.

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Section: Fig3 Snapshots Corresponding To First Shotmentioning

confidence: 99%

Reverse Time Migration Based Ultrasonic Wave Detection for Concrete Structures

Chen

Pan

2014

Design, Construction, and Maintenance of Bridges

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“…To compute the gradients, we use a strategy based on making the forward (source) wavefield available at the same time step as the adjoint wavefield. We implement here the boundary saving approach (Dussaud et al, 2008;Yang et al, Figure 6. Inverted model parameters and their vertical profiles at (x ¼ 4 km, y ¼ 3 km).…”

Section: Methodsmentioning

confidence: 99%

Full-waveform inversion in acoustic orthorhombic media and application to a North Sea data set

Masmoudi

Alkhalifah

2018

GEOPHYSICS

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Full-waveform inversion (FWI) in anisotropic media is challenging, mainly because of the large computational cost, especially in 3D, and the potential trade-offs between the model parameters needed to describe such media. By analyzing the trade-offs and understanding the resolution limits of the inversion, we can constrain FWI to focus on the main parameters the data are sensitive to and push the inversion toward more reliable models of the subsurface. Orthorhombic anisotropy is one of the most practical approximations of the earth subsurface that takes into account the natural horizontal layering and the vertical fracture network. We investigate the feasibility of a multiparameter FWI for an acoustic orthorhombic model described by six parameters. We rely on a suitable parameterization based on the horizontal velocity and five dimensionless anisotropy parameters. This particular parameterization allows a multistage model inversion strategy in which the isotropic, then, the vertical transverse isotropic, and finally the orthorhombic model can be successively updated. We applied our acoustic orthorhombic inversion on the SEG-EAGE overthrust synthetic model. The observed data used in the inversion are obtained from an elastic variable density version of the model. The quality of the inverted model suggests that we may recover only four parameters, with different resolution scales depending on the scattering potential of these parameters. Therefore, these results give useful insights on the expected resolution of the inverted parameters and the potential constraints that could be applied to an orthorhombic model inversion. We determine the efficiency of the inversion approach on real data from the North Sea. The inverted model is in agreement with the geologic structures and well-log information.

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“…In this thesis, we focus on 2D data and it is therefore possible to reconstruct the source wavefield using this method. Two other solutions which can also be used in 3D modelling are to run the forward modelling scheme backwards in time (Dussaud et al, 2008) and to use a checkpointing scheme to reconstruct the source wavefield (Symes, 2007).…”

Section: Source Wavefield Reconstructionmentioning

confidence: 99%

Least-squares Reverse-time Migration

Yao¹,

Jakubowicz²

2012

Proceedings

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Conventional migration methods, including reverse-time migration (RTM) have two weaknesses: first, they use the adjoint of forward-modelling operators, and second, they usually apply a crosscorrelation imaging condition to extract images from reconstructed wavefields. Adjoint operators, which are an approximation to inverse operators, can only correctly calculate traveltimes (phase), but not amplitudes. To preserve the true amplitudes of migration images, it is necessary to apply the inverse of the forward-modelling operator. Similarly, crosscorrelation imaging conditions also only correct traveltimes (phase) but do not preserve amplitudes. Besides, the examples show crosscorrelation imaging conditions produce strong sidelobes. Least-squares migration (LSM) uses both inverse operators and deconvolution imaging conditions. As a result, LSM resolves both problems in conventional migration methods and produces images with fewer artefacts, higher resolution and more accurate amplitudes. At the same time, RTM can accurately handle all dips, frequencies and any type of velocity variation. Combining RTM and LSM produces least-squares reverse-time migration (LSRTM), which in turn has all the advantages of RTM and LSM.In this thesis, we implement two types of LSRTM: matrix-based LSRTM (MLSRTM) and non-linear LSRTM (NLLSRTM). MLSRTM is a matrix formulation of LSRTM and is more stable than conventional LSRTM; it can be implemented with linear inversion algorithms but needs a large amount of computer memory. NLLSRTM, by contrast, directly expresses migration as an optimisation which minimises the ‫ܮ‬ 2 norm of the residual between the predicted and observed data. NLLSRTM can be implemented using non-linear gradient inversion algorithms, such as non-linear steepest descent and non-linear conjugated-gradient solvers.We demonstrate that both MLSRTM and NLLSRTM can achieve better images with fewer artefacts, higher resolution and more accurate amplitudes than RTM using three synthetic examples. The power of LSRTM is also further illustrated using a field dataset. Finally, a simple synthetic test demonstrates that the objective function used in LSRTM is sensitive to errors in the migration velocity.As a result, it may be possible to use NLLSRTM to both refine the migrated image and estimate the migration velocity.

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Computational strategies for reverse‐time migration

Cited by 94 publications

References 15 publications

Reverse Time Migration Based Ultrasonic Wave Detection for Concrete Structures

Reverse Time Migration Based Ultrasonic Wave Detection for Concrete Structures

Full-waveform inversion in acoustic orthorhombic media and application to a North Sea data set

Least-squares Reverse-time Migration

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