Use of Monte Carlo Techniques in Optimum Design of the Deconvolution Process

Foster, M. R.; Sengbush, R. L.; Watson, Robert P.

doi:10.1190/1.1439988

Cited by 11 publications

(3 citation statements)

References 5 publications

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“…The TVSW method, on the other hand, cannot achieve explicit relative amplitude of the seismogram. One common approach is to divide a nonstationary seismic trace into several segments using multiple overlapped windows, the attenuation effect is deconvolved in each window separately, and an output trace is then constructed by blending the windows together (Foster, 1968;Wang, 1969;van der Baan, 2008). However, this type of method usually uses windows with constant width, which are often not optimal.…”

Section: Introductionmentioning

confidence: 99%

Enhancing resolution of nonstationary seismic data by molecular-Gabor transform

Wang

Gao

Zhao³

et al. 2013

GEOPHYSICS

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We propose an adaptive spectrum-broadening method (ASBM) to improve the resolution of nonstationary seismic data. This method assumes that a seismic trace can be split into segments, each of which can be considered as approximately stationary. We construct a set of specific windows, called molecular-Gabor (MG) windows, by solving an optimization problem, such that the seismic trace in each of the MG windows is stationary. A time-frequency (t-f) transform, called MG transform, can be obtained from a MG frame constructed using the MG windows. For a seismic trace, we first transform it into the t-f domain, then spectrum-broadening and/or amplitude compensation are performed in each of the MG windows. Subsequently, a high-resolution version of the nonstationary seismic trace will be obtained after the inverse MG transform. Applications of this method to synthetic and field data show that the ASBM works well for a general earth Q-model that varies with traveltime. It can restore the attenuated energy and expand the frequency bandwidth of a nonstationary seismic trace effectively. One significant advantage of our method is that it automatically estimates all the parameters that are optimal for each trace.

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Section: Introductionmentioning

confidence: 99%

Enhancing resolution of nonstationary seismic data by molecular-Gabor transform

Wang

Gao

Zhao³

et al. 2013

GEOPHYSICS

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“…A proper time local series is critical for analysing a non‐stationary seismic signal. In practice, time local series are obtained by using multiple overlapping windows, and the data in each of these are considered as a stationary signal (Foster, Sengbush and Watson ; Wang ; Van der Baan ). However, due to the effects of wavefront divergence and frequency‐dependent attenuation during seismic wave propagation, these time windows with constant lengths specified by the user cannot provide optimal local features.…”

Section: Introductionmentioning

confidence: 99%

Coherence algorithm with a high‐resolution time–time transform and feature matrix for seismic data

Sun

Gao

Zhang

et al. 2020

Geophysical Prospecting

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A B S T R A C TTraditional coherence algorithms are often based on the assumption that seismic traces are stationary and Gaussian. However, seismic traces are actually non-stationary and non-Gaussian. A constant time window and the canonical correlation analysis in traditional coherence algorithms are not optimal for nonstationary seismic traces and cannot describe the similarity between adjacent seismic traces in detail. To overcome this problem, a new coherence algorithm using the high-resolution time-time transform and the feature matrix is designed. The high-resolution time-time transform used to replace the constant time window can produce a frequency-dependent time local series to analyse non-stationary seismic traces. The feature matrix, constructed by the frequency-dependent time local series and the related local gradients, defines a new correlation metric that enhances more details of the geological discontinuities in seismic images than does the canonical correlation analysis. Additionally, the Riemannian metric is introduced for related calculations because the feature matrices are not defined in a Euclidean space but rather in a manifold space. Application to field data illustrates that the proposed method reveals more details of structural and stratigraphic features.

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“…The conventional deconvolution process in shot seismics, its mathematical and statistical background, and its practical significance for digital data processing have been described by many authors in the last decade (Burns 1968, Clarke 1968, Ford and Hearne 1966, Foster, Sengbush, and Watson 1968, Robinson and Treitel 1967, Robinson 1967, Treitel and Robinson 1966and 1969.…”

Section: Introductionmentioning

confidence: 99%

Vibroseis Deconvolution*

RISTOW¹,

JURCZYK²

1975

Geophysical Prospecting

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RISTOW, D. and JURCZYK, D., 1975, Vibroseis Deconvolution. Geophysical Prospecting 23, 363-379. Vibroseis deconvolution can be performed either before or after correlation. As regards the deconvolution before correlation, the Vibroseis deconvolution operator can be described as convolution of a spike deconvolution operator with a minimum-phase filter operator with bandpass properties. As regards the deconvolution after correlation, the deconvolution operator can be shown to be the convolution of three operators: spike deconvolution operator and two-fold convolution with a minimum phase operator. Time-varyingVibroseis deconvolution can particularly well be described and performed after correlation.

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Use of Monte Carlo Techniques in Optimum Design of the Deconvolution Process

Cited by 11 publications

References 5 publications

Enhancing resolution of nonstationary seismic data by molecular-Gabor transform

Enhancing resolution of nonstationary seismic data by molecular-Gabor transform

Coherence algorithm with a high‐resolution time–time transform and feature matrix for seismic data

Vibroseis Deconvolution*

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