Controlled Noise Seismology

Hanafy, Sherif M.; AlTheyab, Abdullah; Schuster, Gerard T.

doi:10.1190/segam2015-5906063.1

Cited by 14 publications

(6 citation statements)

References 8 publications

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“…The resulting seismic noise is recorded at each of the traces. Then, the traces are broken up into small windows, and each window of arrivals is correlated with the corresponding window of arrivals in other traces to give a virtual CSG (Hanafy et al, 2015). Stacking the virtual CSGs for the same source position gives the virtual shot gather.…”

Section: Qademah Fault Controlled Noise Source Seismic Datamentioning

confidence: 99%

Skeletonized wave equation of surface wave dispersion inversion

Schuster

2016

SEG Technical Program Expanded Abstracts 2016

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SUMMARYWe present the theory for wave equation inversion of dispersion curves, where the misfit function is the sum of the squared differences between the wavenumbers along the predicted and observed dispersion curves. Similar to wave-equation traveltime inversion, the complicated surface-wave arrivals in traces are skeletonized as simpler data, namely the picked dispersion curves in the (k x , ω) domain. Solutions to the elastic wave equation and an iterative optimization method are then used to invert these curves for 2D or 3D velocity models. This procedure, denoted as wave equation dispersion inversion (WD), does not require the assumption of a layered model and is less prone to the cycle skipping problems of full waveform inversion (FWI). The synthetic and field data examples demonstrate that WD can accurately reconstruct the S-wave velocity distribution in laterally heterogeneous media.

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Section: Qademah Fault Controlled Noise Source Seismic Datamentioning

confidence: 99%

Skeletonized wave equation of surface wave dispersion inversion

Schuster

2016

SEG Technical Program Expanded Abstracts 2016

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“…This low-velocity zone is denoted as the Qademah fault and strikes in a north-south direction. The direct evidence for the fault is not seen at this location but it is inferred from the geophysical data as a LVZ (Hanafy et al, 2015;Li and Hanafy, 2016). The shot spacing is 5 m, the y-component receiver spacing is 2.5 m, and there are 240 traces per shot gather to give a total of 120 shot gathers.…”

Section: Qademah Field Datamentioning

confidence: 87%

Dispersion inversion of guided P-waves in a waveguide of arbitrary geometry

Hanafy

Schuster

2018

SEG Technical Program Expanded Abstracts 2018

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“…9 The seismic survey line across the fault area (Hanafy et al, 2015). This paper presented here as accepted for publication in Geophysics prior to copyediting and composition.…”

Section: List Of Figuresmentioning

confidence: 99%

“…Downloaded 04/09/19 to 109.171.137.210. Redistribution subject to SEG license or copyright; see Terms of Use at http://library.seg.org/ Figure 9 The seismic survey line across the fault area (Hanafy et al, 2015).…”

Section: List Of Figuresmentioning

confidence: 99%

Wave-equation Rayleigh-wave dispersion inversion using fundamental and higher modes

Zhang

Alkhalifah

2019

GEOPHYSICS

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Recorded surface waves often provide reasonable estimates of the S-wave velocity in the near surface. However, existing algorithms are mainly based on the 1D layered-model assumption and require picking the dispersion curves either automatically or manually. We have developed a wave-equation-based inversion algorithm that inverts for S-wave velocities using fundamental and higher mode Rayleigh waves without picking an explicit dispersion curve. Our method aims to maximize the similarity of the phase velocity spectrum ([Formula: see text]) of the observed and predicted surface waves with all Rayleigh-wave modes (if they exist) included in the inversion. The [Formula: see text] spectrum is calculated using the linear Radon transform applied to a local similarity-based objective function; thus, we do not need to pick velocities in spectrum plots. As a result, the best match between the predicted and observed [Formula: see text] spectrum provides the optimal estimation of the S-wave velocity. We derive S-wave velocity updates using the adjoint-state method and solve the optimization problem using a limited-memory Broyden-Fletcher-Goldfarb-Shanno algorithm. Our method excels in cases in which the S-wave velocity has vertical reversals and lateral variations because we used all-modes dispersion, and it can suppress the local minimum problem often associated with full-waveform inversion applications. Synthetic and field examples are used to verify the effectiveness of our method.

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Controlled Noise Seismology

Cited by 14 publications

References 8 publications

Skeletonized wave equation of surface wave dispersion inversion

Skeletonized wave equation of surface wave dispersion inversion

Dispersion inversion of guided P-waves in a waveguide of arbitrary geometry

Wave-equation Rayleigh-wave dispersion inversion using fundamental and higher modes

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