Wave‐equation traveltime inversion

Luo, Yi; Schuster, Gerard T.

doi:10.1190/1.1889952

Cited by 109 publications

(209 citation statements)

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“…The measurements were typically made for a set of frequencies {ω k } spaced at 0.01 Hz from 0.02 Hz to 0.20 Hz (Appendix A). For each waveform, we also measured the peak of the unfiltered cross-correlation function, which gives the "broadband" delay time ΔT c , i.e., the phase delay of the observed waveform relative to the synthetic averaged across the full bandwidth of the waveform [Sipkin and Jordan, 1980;Luo and Schuster, 1991;Tanimoto, 1995;Zhao and Jordan, 1998;Dahlen et al, 2000]. We calculated the Fréchet kernels for different measurement types using the appropriate seismogram perturbation kernels [Chen et al, 2007a[Chen et al, , 2007b[Chen et al, , 2010, as described in Appendix D.…”

Section: Data Measurement and Inversionmentioning

confidence: 99%

“…For the broadband cross-correlation traveltime delay, the SPK is the negative of the energy-normalized synthetic particlevelocity seismogram within the specified time window [Luo and Schuster, 1991;Tanimoto, 1995;Zhao and Jordan, 1998;Dahlen et al, 2000;Chen et al, 2007a]. For the frequency-dependent GSDF phase delay, the SPK, J p (t, ω), where ω is the angular frequency at which the narrowband phase-delay misfit was measured, was derived in Chen et al [2010].…”

Section: Journal Of Geophysical Research: Solid Earthmentioning

confidence: 99%

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Full‐3‐D tomography for crustal structure in Southern California based on the scattering‐integral and the adjoint‐wavefield methods

et al. 2014

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We have successfully applied full-3-D tomography (F3DT) based on a combination of the scattering-integral method (SI-F3DT) and the adjoint-wavefield method (AW-F3DT) to iteratively improve a 3-D starting model, the Southern California Earthquake Center (SCEC) Community Velocity Model version 4.0 (CVM-S4). In F3DT, the sensitivity (Fréchet) kernels are computed using numerical solutions of the 3-D elastodynamic equation and the nonlinearity of the structural inversion problem is accounted for through an iterative tomographic navigation process. More than half-a-million misfit measurements made on about 38,000 earthquake seismograms and 12,000 ambient-noise correlagrams have been assimilated into our inversion. After 26 F3DT iterations, synthetic seismograms computed using our latest model, CVM-S4.26, show substantially better fit to observed seismograms at frequencies below 0.2 Hz than those computed using our 3-D starting model CVM-S4 and the other SCEC CVM, CVM-H11.9, which was improved through 16 iterations of AW-F3DT. CVM-S4.26 has revealed strong crustal heterogeneities throughout Southern California, some of which are completely missing in CVM-S4 and CVM-H11.9 but exist in models obtained from previous crustal-scale 2-D active-source refraction tomography models. At shallow depths, our model shows strong correlation with sedimentary basins and reveals velocity contrasts across major mapped strike-slip and dip-slip faults. At middle to lower crustal depths, structural features in our model may provide new insights into regional tectonics. When combined with physics-based seismic hazard analysis tools, we expect our model to provide more accurate estimates of seismic hazards in Southern California.

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Section: Data Measurement and Inversionmentioning

confidence: 99%

Section: Journal Of Geophysical Research: Solid Earthmentioning

confidence: 99%

Full‐3‐D tomography for crustal structure in Southern California based on the scattering‐integral and the adjoint‐wavefield methods

et al. 2014

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“…where s i is the reference signal on component i and ht a function depending on the observable, the adjoint source time function f † is the function h reversed in time (Luo and Schuster, 1991;Tromp et al, 2005) …”

Section: Sensitivitymentioning

confidence: 99%

Finite-Frequency SKS Splitting: Measurement and Sensitivity Kernels

Sieminski

Paulssen

Trampert

et al. 2008

Bulletin of the Seismological Society of America

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Splitting of SKS waves caused by anisotropy may be analyzed by measuring the splitting intensity, i.e., the amplitude of the transverse signal relative to the radial signal in the SKS time window. This quantity is simply related to structural parameters. Extending the widely used cross-correlation method for measuring travel-time anomalies to anisotropic problems, we propose to measure the SKSsplitting intensity by a robust cross-correlation method that can be automated to build large high-quality datasets. For weak anisotropy, the SKS-splitting intensity is retrieved by cross-correlating the radial signal with the sum of the radial and transverse signals. The cross-correlation method is validated based upon a set of Californian seismograms. We investigate the sensitivity of the SKS-splitting intensity to general anisotropy in the mantle based upon a numerical technique (the adjoint spectralelement method) considering the full physics of wave propagation. The computations reveal a sensitivity remarkably focused on a small number of elastic parameters and on a small region of the upper mantle. These fundamental properties and the practical advantages of the measurement make the cross-correlation SKS-splitting intensity particularly well adapted for finite-frequency imaging of upper-mantle anisotropy.

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“…This preconditioner enjoyed early use by Beydoun and Mendes (1989) and Luo and Schuster (1991). Plessix and Mulder (2004) provide a thorough review of its performance and properties.…”

Section: Preconditioningmentioning

confidence: 99%

Multi‐source least‐squares reverse time migration

Dai

Fowler²,

Schuster

2012

Geophysical Prospecting

Self Cite

288

109

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Least‐squares migration has been shown to improve image quality compared to the conventional migration method, but its computational cost is often too high to be practical. In this paper, we develop two numerical schemes to implement least‐squares migration with the reverse time migration method and the blended source processing technique to increase computation efficiency. By iterative migration of supergathers, which consist in a sum of many phase‐encoded shots, the image quality is enhanced and the crosstalk noise associated with the encoded shots is reduced. Numerical tests on 2D HESS VTI data show that the multisource least‐squares reverse time migration (LSRTM) algorithm suppresses migration artefacts, balances the amplitudes, improves image resolution and reduces crosstalk noise associated with the blended shot gathers. For this example, the multisource LSRTM is about three times faster than the conventional RTM method. For the 3D example of the SEG/EAGE salt model, with a comparable computational cost, multisource LSRTM produces images with more accurate amplitudes, better spatial resolution and fewer migration artefacts compared to conventional RTM. The empirical results suggest that multisource LSRTM can produce more accurate reflectivity images than conventional RTM does with a similar or less computational cost. The caveat is that the LSRTM image is sensitive to large errors in the migration velocity model.

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Wave‐equation traveltime inversion

Cited by 109 publications

References 0 publications

Full‐3‐D tomography for crustal structure in Southern California based on the scattering‐integral and the adjoint‐wavefield methods

Full‐3‐D tomography for crustal structure in Southern California based on the scattering‐integral and the adjoint‐wavefield methods

Finite-Frequency SKS Splitting: Measurement and Sensitivity Kernels

Multi‐source least‐squares reverse time migration

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