Optimal Transport FWI with Graph transform: Analysis and Proposal of a Partial Shift Strategy

Kpadonou, Félix; Messud, Jérémie; Sedova, A.; Reinier, M.

doi:10.3997/2214-4609.202112846

Cited by 4 publications

(7 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It seems in this case that both graph-space and KR FWI manage to mitigate the non-convexity issues to a similar level, while working very differently on the data. Such a behavior has also been observed on field data [38] and deserves further fundamental investigations.…”

Section: Discussionsupporting

confidence: 66%

“…A natural perspective regarding the techniques presented here would be to find a way to combine the KR and graph-space approaches to accumulate their respective strengths and bring even more convexity. A first investigation in this direction has been performed in [38,47], with Another perspective would be to increase the effective dimensionality of the KR problem (considering a full 3D data representation space instead of a 2D splitting per line) or of the graph-space problem (considering more than one trace in the graph transform).…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

A review of the use of optimal transport distances for high resolution seismic imaging based on the full waveform

Métivier¹,

Brossier²,

Kpadonou³

et al. 2022

MathematicS in Action

View full text Add to dashboard Cite

show abstract

Section: Discussionsupporting

confidence: 66%

Section: Discussionmentioning

confidence: 99%

A review of the use of optimal transport distances for high resolution seismic imaging based on the full waveform

Métivier¹,

Brossier²,

Kpadonou³

et al. 2022

MathematicS in Action

View full text Add to dashboard Cite

show abstract

“…A natural perspective regarding the techniques presented here would be to find a way to combine the KR and graph-space approaches to accumulate their respective strengths and bring even more convexity. A first investigation in this direction has been performed in [47,38], with the proposal of embedding the graph transform into the KR norm. More investigations are ongoing.…”

Section: Discussionmentioning

confidence: 99%

A review of the use of optimal transport distances for high resolution seismic imaging based on the full waveform

Métivier¹,

Brossier²,

Kpadonou³

et al. 2022

Preprint

View full text Add to dashboard Cite

“…If the use of the KR norm within FWI significantly widens the global minimum valley compared to the use of LSQ, it does not fully solve the cycle-skipping issue or the challenge of FWI with reflected waves only. Further investigations in these directions are ongoing (Métivier et al, 2019;Sun and Al Khalifah, 2019;Tang et al, 2020;Kpadonou et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

“…Comparing various possible KT goes beyond the scope of this article. We mention this point as a perspective, that has started to be explored in Kpadonou et al (2021).…”

Section: Perspectivesmentioning

confidence: 99%

Optimal transport in full-waveform inversion: Analysis and practice of the multidimensional Kantorovich-Rubinstein norm

Messud,

Poncet,

Lambaré

2021

Preprint

View full text Add to dashboard Cite

In the last ten years, full-waveform inversion has emerged as a robust and efficient high-resolution velocity model-building tool for seismic imaging, with the unique ability to recover complex subsurface structures. Originally based on a data fitting process using a least-squares cost function, it suffered from high sensitivity to cycle-skipping and was therefore of poor efficiency in handling large time shifts between observed and modelled seismic events. To tackle this problem, a common practice is to start the inversion using the low temporal frequencies of the data and selecting diving wave events. Complementary to this, the use of other cost functions has been investigated. Among these, cost functions based on optimal transport appeared appealing to possibly handle large time shifts between seismic events. Several strategies inspired by optimal transport have been proposed, taking into account the specificities of seismic data. Among them, the approach based on the Kantorovich-Rubinstein norm offers the possibility of the direct use of seismic data and an efficient numerical implementation allowing for a multidimensional (data coordinate space) application.We present here an analysis of the Kantorovich-Rubinstein norm, discussing its theoretical and practical aspects. A key component of our analysis is the back-propagated adjoint-source. We highlight its piecewise linearity, analyze its frequency content and amplitude balancing. We also emphasize the benefit of having a multidimensional implementation. Furthermore, we give practical rules for setting the tuning parameters of the numerical implementation. Our set of synthetic and field data examples demonstrate the improvements brought by the use of the Kantorovich-Rubinstein norm over least-squares full-waveform inversion, and highlight the improvements brought by the multidimensional approach over the one-dimensional one.

show abstract

Optimal Transport FWI with Graph transform: Analysis and Proposal of a Partial Shift Strategy

Cited by 4 publications

References 0 publications

A review of the use of optimal transport distances for high resolution seismic imaging based on the full waveform

A review of the use of optimal transport distances for high resolution seismic imaging based on the full waveform

A review of the use of optimal transport distances for high resolution seismic imaging based on the full waveform

Optimal transport in full-waveform inversion: Analysis and practice of the multidimensional Kantorovich-Rubinstein norm

Contact Info

Product

Resources

About