The Polynomial Radon Transform

Bin-hua, Niu; Sun, Chunyan; Zhang, Zhongjie; Cao, Shen; Li, Yingcai; Lu, J.; Wang, Hongyu

doi:10.1002/cjg2.139

Cited by 8 publications

(4 citation statements)

References 6 publications

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“…[15]. The selection of parameter in τ -p transform can follow Niu B H et al [16] For bandwidth limited signal, the range of scale factor is selected according to the band range of signal. To improve the computational efficiency, the frame theory should be used.…”

Section: Ridgelet Forward Transform [8∼11]mentioning

confidence: 99%

Ridgelet Domain Method of Ground‐Roll Suppression

Bao¹,

Gao²,

Chen³

2007

Chinese J of Geophysics

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Ground-roll attenuation is an important and difficult problem in seismic data processing. The traditional methods can do these only using the ground-roll single characteristic during processing. In this paper, a method based on ridgelet transform is proposed. Firstly, the method transforms 2-D seismic data into (a, τ, p) domain, and then uses higher velocity and larger scale of ground-roll contrast to reflection wave to identify and separate them. During processing, in order to decrease the effect of alias and boundary effect, the root mean square velocity filter is used. Finally, the processing results of synthetic and real data show that the ridgelet transform method is feasible and effective in attenuating ground-roll, and it can obtain better results than f -k filter and τ -p transform method.

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Section: Ridgelet Forward Transform [8∼11]mentioning

confidence: 99%

Ridgelet Domain Method of Ground‐Roll Suppression

Bao¹,

Gao²,

Chen³

2007

Chinese J of Geophysics

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“…Chinese scholars have also carried out in-depth research on Radon transform to suppress multiple waves. Niu Binhua et al [7]. proposed a polynomial Radon transform by combining the advantages of parabolic Radon transform and linear Radon transform.…”

Section: Introductionmentioning

confidence: 99%

Research Status and Progress of Multiples Suppression Based on Radon Transform

Wang¹

2023

IJE

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The existence of multiple waves in seismic data has a substantial impact on earthquake imaging, inversion, and interpretation results. As a result, multiples are often suppressed as noise prior to seismic data preattack processing. Currently, there are two primary methods for suppressing multiple reflections in seismic data. One is a filtering technique based on geometric differences in the seismic waves, while the other is based on wave equation methods. The Radon transform, which suppresses multiple reflections, belongs to the class of geometric seismic diffraction filtering techniques. In the process of seismic data processing, it effectively separates multiple reflections from seismic data by utilizing the characteristic differences between primary and multiple reflections, thereby achieving noise attenuation and improving the signal-to-noise ratio of the data. This article primarily investigates the current state of methods for suppressing multiple reflections based on the Radon transform, both domestically and internationally. By introducing various forms and fundamental principles of the Radon transform, this study analyzes and compares the adaptability and pros and cons of each type of Radon transform. The high-precision Radon transform can effectively address the sawtooth phenomenon and energy dispersion issues that arise in the least-squares Radon transform. It also highlights the challenges associated with suppressing multiple reflections in the Radon transform and provides a glimpse into future developments.

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“…Radon transform is widely used in a range of applications in seismic data processing, such as multiple attenuation (Wang, 2003;Schonewille and Aaron, 2007;Xiong et al, 2009), de-noise (Gong et al, 2009), wavefield separation (Zeng et al, 2007;Feng et al, 2011), data interpolation and reconstruction (Wang et al, 2006;Wang et al, 2007), velocity dispersion analysis (Pan et al, 2010), migration and imaging (Huang et al, 2004), etc. According to the characteristics of the research problem, Radon transform based on the integration method has several flexible and diverse forms of transform, such as linear Radon transform (τ -p transform), parabolic Radon transform, hyperbolic Radon transform and polynomial Radon transform (Niu and Sun, 2001). For different physical fields, a suitable transform should be selected to achieve the optimal solution of the problem.…”

Section: Introductionmentioning

confidence: 99%

Anisotropic Radon Transform and Its Application to Demultiple

Gong

Han

2014

Chinese J of Geophysics

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For the seismic data acquired in the anisotropic medium and with large offset, although we use the high-resolution hyperbolic Radon transform, the energy of the Radon domain is still not convergent. In order to overcome this problem, the influence of the anisotropic factor is considered in the integral path of Radon transform. By introducing the anisotropic anellipticity parameters η from non-hyperbolic moveout formula, the travel-time curve can be accurately described in the horizontal layer for large offset. We derive the integral equation of forward and inverse Radon transform with three parameters, which are the offset, the slowness and the anellipticity. For time-varying of anisotropic Radon transform, the fast algorithm in the frequency domain is not applicable in the process of discretization. This paper adopt the optimal semblance weighted Gauss-Seidel iterative algorithm which not only keeps the high resolution but also has the high calculation efficiency. In the examples of the anisotropic model and real marine seismic data with large offset, this method shows the effective and efficient application to demultiple.

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The Polynomial Radon Transform

Cited by 8 publications

References 6 publications

Ridgelet Domain Method of Ground‐Roll Suppression

Ridgelet Domain Method of Ground‐Roll Suppression

Research Status and Progress of Multiples Suppression Based on Radon Transform

Anisotropic Radon Transform and Its Application to Demultiple

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