3D Prestack Time Domain Full Waveform Inversion

Vigh, Denes; Starr, W. E. S.; Dingwall, Kenneth

doi:10.3997/2214-4609.201400400

Cited by 9 publications

(4 citation statements)

References 10 publications

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“…More specifically, if the initial model does not generate predicted data within half a wavelength of the observed data, iterative optimization approaches may stagnate at physically meaningless solutions with a high probability. In order to conduct a successful inversion, conventional FWI needs a good initial model that is kinematically accurate at the longest data wavelengths and data containing enough low frequencies and long offsets [Virieux and Operto, 2009, Vigh et al, 2009, Warner et al, 2013. Research aimed at mitigating the "cycle-skipping" issue mainly focuses on different misfit functions [Cara and Lévêque, 1987, van Leeuwen and Mulder, 2010, Wu et al, 2013, Engquist and Froese, 2014, Warner and Guasch, 2016, Yang et al, 2018, expanding the search space [van Leeuwen and Herrmann, 2015, Huang et al, 2017, Fang et al, 2018b, and the integration with the advanced approach of migration velocity analysis [Symes, 2008, Li et al, 2014.…”

Section: Introductionmentioning

confidence: 99%

Lift and Relax for PDE-constrained inverse problems in seismic imaging

Fang,

Demanet

2020

Preprint

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We present Lift and Relax for Waveform Inversion (LRWI), an approach that mitigates the local minima issue in seismic full waveform inversion (FWI) via a combination of two convexification techniques. The first technique (Lift) extends the set of variables in the optimization problem to products of those variables, arranged as a moment matrix. This algebraic idea is a celebrated way to replace a hard polynomial optimization problem by a semidefinite programming approximation. Concretely, both the model and the wavefield are lifted from vectors to rank-2 matrices. The second technique (Relax) invites to consider the wave equation, not as a hard constraint, but as a soft constraint to be satisfied only approximately -a technique known as wavefield reconstruction inversion (WRI). WRI weakens wave-equation constraints by introducing wave-equation misfits as a weighted penalty term in the objective function. The relaxed penalty formulation enables balancing the data and wave-equation misfits by tuning a penalty parameter. Together, "Lift" and "Relax" help reformulate the inverse problem as a set of constraints on a rank-2 moment matrix in a higher dimensional space. Such a lifting strategy permits a good data and wave-equation fit throughout the inversion process, while leaving the numerical rank of the rank-2 moment matrix to be minimized down to one. Numerical examples indicate that compared to FWI and WRI, LRWI can conduct successful inversions using an initial model that would be considered too poor, and data with a starting frequency that would be considered too high, for either method in isolation. Specifically, LRWI increases the acceptable starting frequency from 1.0 Hz and 0.5 Hz to 2.0 Hz and 2.5 for the Marmousi model and the Overthrust model, respectively, in the cases of a linear gradient starting model.

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Section: Introductionmentioning

confidence: 99%

Lift and Relax for PDE-constrained inverse problems in seismic imaging

Fang,

Demanet

2020

Preprint

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“…One of the other advanced techniques that can offer the ability to resolve the velocity field and fully exploit the rich information offered by far-offset data is full-waveform inversion (FWI). Although first introduced in the 1980s (Tarantola, 1984), only recently has FWI been successfully applied to WAZ data sets (Vigh et al, 2009). It is recognized that, to lessen the sensitivity of the initial velocity, FWI must start with low frequencies and long offsets.…”

Section: Introductionmentioning

confidence: 99%

Velocity model building with long-offset and full-azimuth data: A case history for full-waveform inversion

Huang¹,

Ma²,

Vigh³

et al. 2013

SEG Technical Program Expanded Abstracts 2013

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In the last few years, there has been an increased focus on designing advanced acquisition methods for better subsalt imaging. These acquisition methods usually offer largeoffset, full-azimuth datasets with higher signal-to-noise ratio and rich content of low frequency data. To fully exploit the capability of these large-offset data sets, fullwaveform inversion is often adopted as the tool to build a high-fidelity, high-resolution velocity model. In this paper, we describe our general steps and QC measurements in full-waveform inversion model building for a field data set. Comparison of reverse time migration (RTM) images between the initial tomography velocity and full-waveform inversion velocity validate the uplift provided by fullwaveform inversion.

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“…FWI is an inversion technique that utilizes residual differences between the observed and wave-equation-modelled seismograms to update the velocity field, which was first introduced in the 1980s (Tarantola, 1984). Successful developments were made to increase the efficiency and accuracy (Vigh et al, 2009). With the development of newer computer hardware, and emerging high-performance algorithms, the application of FWI became possible.…”

Section: Introductionmentioning

confidence: 99%

Salt Exit Velocity Retrieval Using Full-waveform Inversion

Kapoor¹,

Huang²,

Jiang³

et al. 2013

London 2013, 75th Eage Conference en Exhibition Incorporating SPE Europec

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Accurate retrieval of salt exit velocity has been a important part in drilling hazard prediction, and is essential to achieve a clear subsalt image. Subsalt velocity retrieval is in many cases a difficult task to perform as the subsalt signal is often very weak. The common industrial practice to derive the subsalt velocity is to superpose a regional velocity gradient below the salt.However, using regional velocity gradient trend to estimate subsalt velocity ignores the relation between effective stress and velocities, which is extra important in determining the salt exit velocity. Full-waveform inversion(FWI) emerges as a advanced model building tool in recent years; however,the capability of FWI is limited due to lack of lowfrequency and large-offset dataset, which are essential to the success of FWI retrieval. In this work, we successfully use time-domain full waveform inversion together with large offset dataset to retrieve the salt exit velocity, which improve the subsalt image and benefit the pore pressure prediction.

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3D Prestack Time Domain Full Waveform Inversion

Cited by 9 publications

References 10 publications

Lift and Relax for PDE-constrained inverse problems in seismic imaging

Lift and Relax for PDE-constrained inverse problems in seismic imaging

Velocity model building with long-offset and full-azimuth data: A case history for full-waveform inversion

Salt Exit Velocity Retrieval Using Full-waveform Inversion

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