Estimation of S-wave static corrections using CMP cross-correlation of surface waves

Askari, Roohollah; Ferguson, Robert J.; Isaac, J. Helen; Hejazi, S. Hossein

doi:10.1016/j.jappgeo.2015.07.004

Cited by 14 publications

(2 citation statements)

References 17 publications

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“…), are also used to compute the receiver static corrections (Mari ; Askari et al . ). The residual static corrections can be considered fine‐tuning of datum static corrections.…”

Section: Methodsmentioning

confidence: 97%

Research Note: Frequency domain orthogonal projection filtration of surface microseismic monitoring data

Azarov

Serdyukov

Gapeev³

2019

Geophysical Prospecting

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We address the problem of increasing the signal‐to‐noise ratio during surface microseismic monitoring data processing. Interference from different seismic waves causes misleading results of microseismic event locations. Ground‐roll suppression is particularly necessary. The standard noise suppression techniques assume regular and dense acquisition geometries. Many pre‐processing noise suppression algorithms are designed for special types of noise or interference. To overcome these problems, we propose a novel general‐purpose filtration method. The goal of this method is to amplify only the seismic waves that are excited in the selected target area and suppress all other signals. We construct a linear projector onto a frequency domain data subspace, which corresponds to the seismic emission of the target area. The novel filtration method can be considered an extension of the standard frequency–wavenumber flat wave filtration method for non‐flat waves and arbitrary irregular receiver‐position geometries. To reduce the effect of the uncertainty of the velocity model, we suggest using additional active shot data (typically the perforation shots), which provide static travel time corrections for the target area. The promising prospects of the proposed method are confirmed by synthetic and semi‐synthetic data processing.

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“…), are also used to compute the receiver static corrections (Mari ; Askari et al . ). The residual static corrections can be considered fine‐tuning of datum static corrections.…”

Section: Methodsmentioning

confidence: 97%

Research Note: Frequency domain orthogonal projection filtration of surface microseismic monitoring data

Azarov

Serdyukov

Gapeev³

2019

Geophysical Prospecting

View full text Add to dashboard Cite

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“…(2016) considered the ST analysis of seismic reflection data. ST was also widely applied to analyse the seismic surface wave propagation (Askari and Ferguson, 2012; Askari et al ., 2015; Serdyukov et al ., 2019).…”

Section: Introductionmentioning

confidence: 99%

Research Note: Reconstruction of seismic signals using S‐transform ridges

Serdyukov

Azarov

Yablokov

et al. 2021

Geophysical Prospecting

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We have addressed the problem of seismic data frequency–time filtration based on the S‐transform. The S‐transform provides frequency‐dependent resolution while maintaining a direct relationship with the Fourier spectrum and has been widely used in different seismic data‐processing applications. The standard S‐transform filtration method is based on its invertibility. In a sense of time localization, this method is not optimal because the calculation of the inverse S‐transform includes time averaging. We propose an alternative filtration method based on the reconstruction of a signal by S‐transform ridges. We approximate the phase of the Fourier spectrum of the reconstructed signal using the phase of the S‐transform ridge. We derive the integral equation, which expresses the S‐transform ridge amplitudes in terms of the amplitudes of the Fourier spectrum of the reconstructed signal. The introduced equation is numerically solved to find the signal amplitude using the truncated singular value decomposition. From the results, we obtain both the phase and amplitude of the signal. Thus, the signal can be extracted from the S‐transform spectrum only by the ridges. This finding is promising in terms of maximum usage of the time‐localization properties of the S‐transform during frequency–time filtration. The presented results of ground‐roll attenuation from reflection seismic data demonstrate that the proposed S‐transform ridge filtration method can be effective in practice.

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Stochastic fracture simulation using pixel-based multiple-point geostatistics by integrating seismic radial anisotropy and well data: applications in two hydrology sites

et al. 2020

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Estimation of S-wave static corrections using CMP cross-correlation of surface waves

Cited by 14 publications

References 17 publications

Research Note: Frequency domain orthogonal projection filtration of surface microseismic monitoring data

Research Note: Frequency domain orthogonal projection filtration of surface microseismic monitoring data

Research Note: Reconstruction of seismic signals using S‐transform ridges

Stochastic fracture simulation using pixel-based multiple-point geostatistics by integrating seismic radial anisotropy and well data: applications in two hydrology sites

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