Multiscattering inversion for low-model wavenumbers

Alkhalifah, Tariq; Wu, Zedong

doi:10.1190/geo2015-0650.1

Cited by 53 publications

(38 citation statements)

References 29 publications

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“…Multiples generally spend more time in the subsurface, compared to primaries; therefore, have a higher vertical resolution of the subsurface parameters (Zhang and Schuster, 2013;Berkhout, 2014c;Berkhout and Verschuur, 2016). Using them also broadens the subsurface illumination and attenuates the effect of shadow zones (Alkhalifah and Wu, 2016;Davydenko and Verschuur, 2017b), therefore providing a more balanced illumination of the subsurface (Whitmore et al, 2010;Kumar et al, 2014;Lu et al, 2015). A unique benefit of using internal multiples is that it enables imaging structures from below as shown by Davydenko andVerschuur (2013, 2017b).…”

Section: Introductionmentioning

confidence: 99%

Robust estimation of vertical symmetry axis models via joint migration inversion: Including multiples in anisotropic parameter estimation

Alshuhail

Verschuur

2019

GEOPHYSICS

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Because the earth is predominately anisotropic, the anisotropy of the medium needs to be included in seismic imaging to avoid mispositioning of reflectors and unfocused images. Deriving accurate anisotropic velocities from the seismic reflection measurements is a highly nonlinear and ambiguous process. To mitigate the nonlinearity and trade-offs between parameters, we have included anisotropy in the so-called joint migration inversion (JMI) method, in which we limit ourselves to the case of transverse isotropy with a vertical symmetry axis. The JMI method is based on strictly separating the scattering effects in the data from the propagation effects. The scattering information is encoded in the reflectivity operators, whereas the phase information is encoded in the propagation operators. This strict separation enables the method to be more robust, in that it can appropriately handle a wide range of starting models, even when the differences in traveltimes are more than a half cycle away. The method also uses internal multiples in estimating reflectivities and anisotropic velocities. Including internal multiples in inversion not only reduces the crosstalk in the final image, but it can also reduce the trade-off between the anisotropic parameters because internal multiples usually have more of an imprint of the subsurface parameters compared with primaries. The inverse problem is parameterized in terms of a reflectivity, vertical velocity, horizontal velocity, and a fixed [Formula: see text] value. The method is demonstrated on several synthetic models and a marine data set from the North Sea. Our results indicate that using JMI for anisotropic inversion makes the inversion robust in terms of using highly erroneous initial models. Moreover, internal multiples can contain valuable information on the subsurface parameters, which can help to reduce the trade-off between anisotropic parameters in inversion.

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Section: Introductionmentioning

confidence: 99%

Robust estimation of vertical symmetry axis models via joint migration inversion: Including multiples in anisotropic parameter estimation

Alshuhail

Verschuur

2019

GEOPHYSICS

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“…Specifically, gradients provided by wavepath updates adhere to resolution limits governed mainly by the wave path length. The maximum wavenumber obtained is approximately inversely proportional to the square root of the length of the wavepath (Alkhalifah, 2016 …”

Section: Resolution and Acquisitionmentioning

confidence: 99%

“…If that happens, we can also map the wavepaths, and thus, achieve wavepath updates. In this case, we can optimize the update to fit the data for multi scattering, and that is equivalent to imposing a full Hessian on the update (Alkhalifah and Wu, 2016). Such an acquisition can be accomplished by running the vibrator at a single frequency for the duration of the sweep.…”

Section: Analysis Of the Mutiscattering Gradient Resolutionmentioning

confidence: 99%

“…Even in reflection waveform inversion (RWI), we often include only single-scattered energy in the wave path background update. However, recently Alkhalifah and Wu (2016) proposed a multi scattering inversion for both the background and perturbation models (FWI+RWI), done entirely in the frequency domain. The added background and perturbation information provided by the multi scattering was obvious in their results.…”

Section: Introductionmentioning

confidence: 99%

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Sparse frequencies data inversion and the role of multi-scattered energy

Alkhalifah¹

2017

Proceedings

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SummaryIn trying to extract a broad spectrum of model wavenumbers from the data, necessary to build a plausible model of the Earth, we are, in theory, bounded at the high end by the diffraction resolution limit, which is proportional to the highest usable frequency in the data. At the low end, and courtesy of our multi-dimensional acquisition, the principles behind diffraction tomography theoretically extend our range to zero-wavenumbers, mainly provided by transmissions like diving waves. Within certain regions of the subsurface (i.e. deep), we face the prospective of having a model wavenumber gap in representing the velocity. Here, I demonstrate that inverting for multi scattered energy, we can recover additional wavenumbers not provided by single scattering gradients, that may feed the high and low ends of the model wavenumber spectrum, as well as help us fill in the infamous intermediate wavenumber gap. Thus, I outline a scenario in which we acquire dedicated sparse frequency data, allowing for more time to inject more energy of those frequencies at a reduced cost. Such additional energy is necessary to the recording of more multi-scattered events. (Claerbout, 1985), as it helped us reduce the dimensionality of the wavefield. Even in reverse time migration, the reduction of dimensionality allows for practical storage of the source wavefield in 3D, needed for a fast implementation of the imaging condition. However, solving the Helmholtz wave equation requires finding the inverse of a large-sparse matrix, and in 3D, this is problematic especially for a large image space. Nevertheless, as soon as such an inverse is established (the Green's function), it can be used efficiently to obtain wavefield solutions for any source, including the residual wavefield, and more importantly secondary sources (like those from the Born series).

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“…Zhou et al (2015) propose similar ideas that invert for velocity and impedance. In previous work, we proposed to invert for the background and perturbation simultaneously (Wu and Alkhalifah, 2015;Alkhalifah and Wu, 2016b), which can use diving waves, first-order reflection, and even multiscattering energy (Alkhalifah and Wu, 2016a) together. RWI can update along the wavepath of diving and reflected waves that can reduce the cycle-skipping problem in some way.…”

Section: Introductionmentioning

confidence: 99%

Selective data extension for full-waveform inversion: An efficient solution for cycle skipping

Alkhalifah

2018

GEOPHYSICS

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CitationWu Z, Alkhalifah T (2018) Selective data extension for fullwaveform inversion: An efficient solution for cycle skipping. ABSTRACTStandard full-waveform inversion (FWI) attempts to minimize the difference between observed and modeled data. However, this difference is obviously sensitive to the amplitude of observed data, which leads to difficulties because we often do not process data in absolute units and because we usually do not consider density variations, elastic effects, or more complicated physical phenomena. Global correlation methods can remove the amplitude influence for each trace and thus can mitigate such difficulties in some sense. However, this approach still suffers from the well-known cycle-skipping problem, leading to a flat objective function when observed and modeled data are not correlated well enough. We optimize based on maximizing not only the zero-lag global correlation but also time or space lags of the modeled data to circumvent the half-cycle limit. We use a weighting function that is maximum value at zero lag and decays away from zero lag to balance the role of the lags. The resulting objective function is less sensitive to the choice of the maximum lag allowed and has a wider region of convergence compared with standard FWI. Furthermore, we develop a selective function, which passes to the gradient calculation only positive correlations, to mitigate cycle skipping. Finally, the resulting algorithm has better convergence behavior than conventional methods. Application to the Marmousi model indicates that this method converges starting with a linearly increasing velocity model, even with data free of frequencies less than 3.5 Hz. Application to the SEG2014 data set demonstrates the potential of our method.

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Multiscattering inversion for low-model wavenumbers

Cited by 53 publications

References 29 publications

Robust estimation of vertical symmetry axis models via joint migration inversion: Including multiples in anisotropic parameter estimation

Robust estimation of vertical symmetry axis models via joint migration inversion: Including multiples in anisotropic parameter estimation

Sparse frequencies data inversion and the role of multi-scattered energy

Selective data extension for full-waveform inversion: An efficient solution for cycle skipping

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