Optimal Transport Full Waveform Inversion - Applications

Carotti, D.; Hermant, Olivier; Masclet, S.; Reinier, M.; Messud, Jérémie; Sedova, A.; Lambaré, Gilles

doi:10.3997/2214-4609.202011288

Cited by 7 publications

(6 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This is especially true in the case of long‐offset OBS data that contain a wide variety of phases with different amplitudes and time signatures. The alternative approach based on the 1‐Wasserstein distance has shown interesting properties, especially because it is possible to apply it to multi‐D shot gathers and account for the lateral coherency of the data in this shot‐gather representation (see, for instance, successful applications to the exploration‐scale field data by Carotti et al., 2020; Messud & Sedova, 2019; Poncet et al., 2018; Sedova et al., 2019; Shutova et al., 2020). However, one identified drawback of this approach is the loss of convexity with respect to large time shifts (Métivier et al., 2018): the valley of attraction of the misfit function is only slightly larger than that of the L 2 norm.…”

Section: Methodsmentioning

confidence: 99%

Graph‐Space Optimal Transport Concept for Time‐Domain Full‐Waveform Inversion of Ocean‐Bottom Seismometer Data: Nankai Trough Velocity Structure Reconstructed From a 1D Model

2021

View full text Add to dashboard Cite

Full-waveform inversion (FWI) has proven to be a powerful tool able to reconstruct high-resolution velocity models of the subsurface. Rapid development of this technology during past decades has led to its successful application in imaging of various geological targets, from near-surface to global-scale endpoints (see Tromp, 2019 for a recent review). In particular, the oil & gas industry (stimulated by the hydrocarbon market) is currently routinely applying FWI at the exploration scale for high-resolution imaging of reservoirs (

show abstract

Section: Methodsmentioning

confidence: 99%

Graph‐Space Optimal Transport Concept for Time‐Domain Full‐Waveform Inversion of Ocean‐Bottom Seismometer Data: Nankai Trough Velocity Structure Reconstructed From a 1D Model

2021

View full text Add to dashboard Cite

show abstract

“…Many successful industrial applications of KR FWI on 3D field data have been published, see for instance [20,31,32,48,68,79]. In this Section, we review three examples.…”

Section: Industrial Applications Of the Kantorovich-rubinstein Strate...mentioning

confidence: 99%

“…The first example refers to 3D land data acquired in the North of Oman (see [20] for more details). The FWI was run with the frequency increasing from 2 Hz to 16 Hz, using a pseudoacoustic wave propagation and following the data pre-processing workflow proposed by [79].…”

Section: North Of Oman Land Datamentioning

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

“…Recently, this approach led to numerous successful industrial FWI applications, see e.g. Poncet et al (2018), Messud and Sedova (2019), Sedova et al (2019), Hermant et al (2019), Carotti et al (2020), Hermant et al (2020). Compared to LSQ FWI, an interesting reduction in sensitivity to cycle-skipping has been observed, together with an improved structural consistency in inverted subsurface models.…”

Section: Introductionmentioning

confidence: 99%

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

2021

View full text Add to dashboard Cite

In the last ten years, full-waveform inversion (FWI) has emerged as a robust and efficient high-resolution subsurface model-building tool for seismic imaging, with the unique ability to invert for complex models. FWI is based on the minimization of a cost function between observed and modelled data, the data space consisting in collections of time-series. Originally considering a least-squares (LSQ) cost function, the method suffered from high sensitivity to local minima and was therefore of poor efficiency in handling large time shifts between observed and modelled data events. To tackle this problem, a common practice is to start the inversion using the low temporal frequencies of the data and selecting specific data events called diving waves. Complementary to this, the use of other cost functions has been investigated. Among these, cost functions based on optimal transport (OT) appeared appealing to possibly handle large time shifts between observed and modelled data events. Several strategies inspired by OT have been proposed, taking into account the specificities of seismic data. Among them, the approach based on the Kantorovich–Rubinstein (KR) 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 KR norm, discussing its theoretical and practical aspects. A key component of our analysis is the adjoint-source or data-space gradient of the cost function (converted into the model-space gradient within FWI). We highlight its piecewise linearity, analyze its frequency content and amplitude, and emphasize the benefit of having a multidimensional implementation. We give practical rules for setting the tuning parameters. Our set of synthetic and field data examples demonstrate the improvements brought by the use of the KR norm over LSQ FWI, and highlight the improvements brought by the multidimensional approach over the one-dimensional one.

show abstract

Optimal Transport Full Waveform Inversion - Applications

Cited by 7 publications

References 1 publication

Graph‐Space Optimal Transport Concept for Time‐Domain Full‐Waveform Inversion of Ocean‐Bottom Seismometer Data: Nankai Trough Velocity Structure Reconstructed From a 1D Model

Graph‐Space Optimal Transport Concept for Time‐Domain Full‐Waveform Inversion of Ocean‐Bottom Seismometer Data: Nankai Trough Velocity Structure Reconstructed From a 1D Model

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