Wave-equation Qs inversion of skeletonized surface waves

Li, Jing; Dutta, Gaurav; Schuster, Gerard T.

doi:10.1093/gji/ggx051

Cited by 28 publications

(11 citation statements)

References 35 publications

(36 reference statements)

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“…In these works the waveguide model has a planar geometry. Instead of inverting just for velocity, the WDG method can, in principle, be modified to invert for both the velocity and attenuation models. In this case the viscoelastic wave equation and its numerical solutions must be computed to estimate the gradients for the attenuation parameters (J. Li, Dutta, & Schuster, ; Schuster et al, ). However, there is an inherent nonuniqueness problem in inverting for both velocity and attenuation models, so it is likely that both dispersion curves and normalized amplitudes should be used as input data.…”

Section: Discussionmentioning

confidence: 99%

Wave‐Equation Dispersion Inversion of Guided P Waves in a Waveguide of Arbitrary Geometry

Hanafy

Schuster

2018

JGR Solid Earth

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We present a dispersion‐inversion method which inverts for the P‐velocity model from guided waves propagating in wave guides of arbitrary geometry. Its misfit function is the squared summation of differences between the predicted and observed dispersion curves of guided P waves, and the inverted result is a high‐resolution estimate of the near‐surface P‐velocity model. We denote this procedure as wave‐equation dispersion inversion of guided P waves (WDG), which is valid for near‐surface waveguides with irregular layers and does not require a high‐frequency approximation. It is more robust than full waveform inversion and can sometimes provide velocity models with higher resolution than wave‐equation traveltime tomography. Both the synthetic‐data and field data results demonstrate that WDG for guided P waves can accurately invert for complex P‐velocity models at the near surface of the Earth.

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Section: Discussionmentioning

confidence: 99%

Wave‐Equation Dispersion Inversion of Guided P Waves in a Waveguide of Arbitrary Geometry

Hanafy

Schuster

2018

JGR Solid Earth

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“…where the Fréchet derivative (Luo & Schuster 1991;Li et al 2017) for a source at the geophone position g i is…”

Section: A P P E N D I X B : E Q U I Va L E N C Y B E T W E E N Wav Ementioning

confidence: 99%

Resolution limits of migration and linearized waveform inversion images in a lossy medium

Schuster¹,

Dutta²,

Li³

2017

Geophysical Journal International

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CitationSchuster GT, Dutta G, Li J (2017) Resolution limits of migration and linearized waveform inversion images in a lossy medium. S U M M A R YThe vertical-and horizontal-resolution limits x lossy and z lossy of post-stack migration and linearized waveform inversion images are derived for lossy data in the far-field approximation. Unlike the horizontal resolution limit x ∝ λz/L in a lossless medium which linearly worsens in depth z, x lossy ∝ z 2 /QL worsens quadratically with depth for a medium with small Q values. Here, Q is the quality factor, λ is the effective wavelength, L is the recording aperture, and loss in the resolution formulae is accounted for by replacing λ with z/Q. In contrast, the lossy vertical-resolution limit z lossy only worsens linearly in depth compared to z ∝ λ for a lossless medium. For both the causal and acausal Q models, the resolution limits are linearly proportional to 1/Q for small Q. These theoretical predictions are validated with migration images computed from lossy data.

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“…The initial Q s model is a homogeneous half space (Figure 2d). Figure 4: (a) P-wave tomogram with ray tracing tomography, and (b) S-wave velocity tomogram by wave equation dispersion inversion (Li et al, 2017a).…”

Section: Connective Functionmentioning

confidence: 99%

Skeletonized wave-equation Qs tomography using surface waves

Dutta

Schuster

2017

SEG Technical Program Expanded Abstracts 2017

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We present a skeletonized inversion method that inverts surface-wave data for the Q s quality factor. Similar to the inversion of dispersion curves for the S-wave velocity model, the complicated surface-wave arrivals are skeletonized as simpler data, namely the amplitude spectra of the windowed Rayleighwave arrivals. The optimal Q s model is then found that minimizes the difference in the peak frequencies of the predicted and observed Rayleigh wave arrivals using a gradient-based wave-equation optimization method. Solutions to the viscoelastic wave-equation are used to compute the predicted Rayleigh-wave arrivals and the misfit gradient at every iteration. This procedure, denoted as wave-equation Q s tomography (WQ s), does not require the assumption of a layered model and tends to have fast and robust convergence compared to Q full waveform inversion (Q-FWI). Numerical examples with synthetic and field data demonstrate that the WQ s method can accurately invert for a smoothed approximation to the subsurface Q s distribution as long as the V s model is known with sufficient accuracy.

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Wave-equation Qs inversion of skeletonized surface waves

Cited by 28 publications

References 35 publications

Wave‐Equation Dispersion Inversion of Guided P Waves in a Waveguide of Arbitrary Geometry

Wave‐Equation Dispersion Inversion of Guided P Waves in a Waveguide of Arbitrary Geometry

Resolution limits of migration and linearized waveform inversion images in a lossy medium

Skeletonized wave-equation Qs tomography using surface waves

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