Stabilizing the low frequencies

Whitcombe, David N.; Hodgson, Linda

doi:10.1190/1.2431833

Cited by 26 publications

(5 citation statements)

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“…The major three potential benefits of extending the bandwidth of seismic data to well below 10 Hz are: 1) better imaging for deep exploration targets; 2) more accurate seismic inversion; and 3) higher vertical resolution (Dragoset and Gabitzsch, 2007;Lau et al, 2007;Martin and Stewart, 1994;Whitcombe and Hodgson, 2007). In practice, there are still a number of obstacles that must be overcome to extend the useful bandwidth of seismic data much below 10 Hz.…”

Section: Introductionmentioning

confidence: 98%

A hybrid method for strong low-frequency noise suppression in prestack seismic data

2014

Journal of Applied Geophysics

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Section: Introductionmentioning

confidence: 98%

A hybrid method for strong low-frequency noise suppression in prestack seismic data

2014

Journal of Applied Geophysics

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“…Moreover, the suppression of surface waves also affects the lowfrequency components. Thus, researchers at home and abroad have looked at improving the low-frequency data processing methods (e.g., Guan and Tang, 1990;Whitcombe and Hodgson, 2007;Woodburn et al, 2011). Nevertheless, the currently available low-frequency processing methods have many limitations, e.g., strong interference in the low-velocity zone influences the effect of low-frequency expansion; the low-frequency stabilization based on spatial filtering only operates on low-frequency slices; the significance of frequency compensation is not clear; low-frequency expansion based on the deconvolution operator only processes the wavelet and not considering the wavelet change of the formation.…”

Section: Introductionmentioning

confidence: 98%

Low-frequency data analysis and expansion

Zhang

et al. 2015

Appl. Geophys.

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The use of low-frequency seismic data improves the seismic resolution, and the imaging and inversion quality. Furthermore, low-frequency data are applied in hydrocarbon exploration; thus, we need to better use low-frequency data. In seismic wavelets, the loss of low-frequency data decreases the main lobe amplitude and increases the first side lobe amplitude and results in the periodic shocking attenuation of the secondary side lobe. The loss of low frequencies likely produces pseudo-events and the false appearance of higher resolution. We use models to examine the removal of low-frequency data in seismic data processing. The results suggest that the removal of low frequencies create distortions, especially for steep structures and thin layers. We also perform low-frequency expansion using compressed sensing and sparse constraints and develop the corresponding module. Finally, we apply the proposed method to real common image point gathers with good results.

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“…In addition, since compaction is an interval property, it has the potential to provide low‐frequency information that is an important missing component in seismic inversion (e.g. Whitcombe and Hodgson ; Ten Kroode et al . ; Yuan et al .…”

Section: Introductionmentioning

confidence: 99%

“…In addition, since compaction is an interval property, it has the potential to provide low-frequency information that is an important missing component in seismic inversion (e.g. Whitcombe and Hodgson 2007;Ten Kroode et al 2013;Yuan et al 2019). Qualitative contrasts in differential compaction * E-mail: jgallop@ikonscience.com rely upon imaging rapid changes in subsurface horizon structure (time or depth), and interpretations are often made on attributes derived from these variations, such as curvature (Chopra and Marfurt 2012).…”

Section: Introductionmentioning

confidence: 99%

A rock physics model to map gross lithology using compaction

Gallop

Babak

Liu

2019

Geophysical Prospecting

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Differential compaction has long been used by seismic interpreters to infer subsurface geology using knowledge of the relative compaction of different types of sediments. We outline a method to infer the gross fraction of shale in an interval between two seismic horizons using sandstone and shale compaction laws. A key component of the method involves reconstruction of a smooth depositional horizon by interpolating decompacted thicknesses from well control. We derive analytic formulae for decompaction calculations using known porosity–stress relations and do not employ discrete layer iterative methods; these formulae were found to depend not only upon the gross fraction of shale but also on the clay content of the shales and the thickness of the interval. The relative merits of several interpolation options were explored, and found to depend upon the structural setting. The method was successfully applied to an oil sands project in Alberta, Canada.

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Stabilizing the low frequencies

Cited by 26 publications

References 0 publications

A hybrid method for strong low-frequency noise suppression in prestack seismic data

A hybrid method for strong low-frequency noise suppression in prestack seismic data

Low-frequency data analysis and expansion

A rock physics model to map gross lithology using compaction

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