基于迭代阈值收缩的高分辨率Radon变换方法效果对比

doi:10.11720/wtyht.2021.2584

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Abstract

The study of the resolution improvement of Radon transform is one of the research hotspots in seismic data processing area.The commonly-used resolution improvement methods are carried out in the frequency domain.However,the weighting of the Radon model in the frequency domain is coupled,and it will impose the same weight on all the events,leading to the artifacts generated by high energy seismic events.This paper presents three resolution improvement methods of Radon transform in the time domain:Iterative Shrinkage Thresholding (IST),Fast Iterative Shrinkage Thresholding (FIST) and Sparse Radon Transform Iterative Shrinkage (SRTIS),with a comparison of their compute efficiencies and results.Synthetic data and real data test results show that SRTIS is superior to the other two methods in computation effect and efficiency,and it has a better multiple attenuation capability.

Key words： Radon transform iteration high resolution multiple suppression IST FIST SRTIS

Received: 17 December 2019 Published: 29 April 2021

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	Articles by authors
	Ji-Tao MA
	Zhen LIAO
	Jiao QI
	Lin CHI

Cite this article:

Ji-Tao MA,Zhen LIAO,Jiao QI, et al. The comparison of effects of high-resolution Radon transform based on iterative shrinkage thresholding[J]. Geophysical and Geochemical Exploration, 2021, 45(2): 413-422.

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https://www.wutanyuhuatan.com/EN/10.11720/wtyht.2021.2584 OR https://www.wutanyuhuatan.com/EN/Y2021/V45/I2/413

The simulated data in the time domain(a) and the corresponding result of the LS Radon transform(b)

The iterative results with different iterations of the IST transform
a—the 40 iterations;b—the 80 iterations;c—the 160 iterations

The comparison of multiple suppression results using IST method
a—the LS transform;b—the 40 iterations;c—the 160 iterations

The iterative result of the FIST transform
a—the 10 iterations;b—the 20 iterations;c—the 40 iterations

The comparison of multiple suppression results using FIST method
a—the 10 iterations;b—the 20 iterations;c—the 40 iterations

The iterative result of the SRTIS transform
a—the 5 iterations;b—the 15 iterations;c—the 30 iterations

The comparison of multiple suppression results using SRTIS method
a—the 5 iterations;b—the 15 iterations;c—the 30 iterations

The error energy between the iterative result of SRTIS and the original data

The compasion of three iterative algorithms' contraction efficiency

The comparsion of the three iterative based algorithms' results

The estimated multiple model by various methods

The multiple suppression result by various methods

The comparison of real data CDP gather stack results
a—the stack of the original data;b—the stack of LS Radon result;c—the stack of IST Radon result;d—the stack of FIST Radon result;e—the stack of SRTIS Radon result

[1]	戴晓峰, 刘卫东, 甘利灯, 等. Radon变换压制层间多次波技术在高石梯—磨溪地区的应用[J]. 石油学报, 2018,39(9):1028-1036.
[1]	Dai X F, Liu W D, Gan L D, et al. The application of Radon transform to suppress interbed multiples in Gaoshiti—Moxi region[J]. Acta Petrolei Sinica, 2018,39(9):1028-1036.
[2]	曹伦. 高分辨率Radon变换及其在地震资料处理中的应用[D]. 成都:成都理工大学, 2017.
[2]	Cao L. High resolution Radon transform and its application in seismic data processing[D]. Chengdu:Chengdu University of Technology, 2017.
[3]	Thorson J R, Claerbout J F. Velocity stack and slant stochastic inversion[J]. Geophysics, 1985,50(12):2727-2741.
[4]	Hampson D. Inverse velocity stacking for multiple elimination[J]. Canadian Society of Exploration Geophysicists, 1986,22(1):44-55.
[5]	张振波, 轩义华. 高分辨率抛物线拉冬变换多次波压制技术[J]. 物探与化探, 2014,38(5):981-988.
[5]	Zhang Z B, Xuan Y H. High resolution parabolic radon transform multiple wave suppression technique[J]. Geophysical and Geochemical Exploration, 2014,38(5):981-988.
[6]	Beylkin G. Discrete Radon transform[J]. IEEE Trans. Acoust.,Speech,and Sig. Proc., 1987,35(2):162-172.
[7]	Scales J, Gersztenkorn A, Treitel S. Fast lp solution of large,sparse,linear systems:Application to seismic travel time tomography[J]. Journal of Computational Physics, 1988,75(2):314-333.
[8]	Cary P. The simplest discrete Radon transform[C] //68^th Annual International Meeting,SEG,Expanded Abstracts, 1998: 1999-2002.
[9]	Sacchi M D, Ulrych T J. High-resolution velocity gathers and offset space reconstruction[J]. Geophysics, 1995,60(4):1169-1177.
[10]	Beylkin G, Coifman R, Rokhlin V. Fast wavelet transforms and numerical algorithms[J]. I.Comm Pure Appl Math, 1991,44(2):141-183.
[11]	Abbad B, Ursin B, Porsani M J. A fast,modified parabolic Radon transform[J]. Geophysics, 2011,76(1):V11-V24.
[12]	Elad M, Matalon B, Shtok J, et al. A wide-angle view at iterated shrinkage algorithms[C] //SPIE,The International Society for Optical Engineering, 2007.
[13]	Schonewille M A, Aaron P A. Applications of time-domain high-resolution Radon demultiple[C] //77^th Annual International Meeting,SEG,Expanded Abstracts, 2007: 2565-2569.
[14]	Trad D, Ulrych T, Sacchi M. Latest views of the sparse Radon transform[J]. Geophysics, 2003,68(1):386-399.
[15]	Lu W K. A time-domain high-resolution Radon transform based on iterative model shrinkage[C] //74^th Annual Conference and Exhibition,EAGE,Extended Abstracts, 2012.
[16]	Daubechies I, Defrise M, De-Mol C. An iterative thresholding algorithm for linear inverse problems with a sparsity constraint[J]. Communications on Pure and Applied Mathematics, 2004,57(9):1413-1457.
[17]	Zibulevsky M, Elad M. L1-L2 optimization in signal and image processing[J]. IEEE Signal Processing Magazine, 2010,27(3):76-88.
[18]	Figueiredo M, Nowak R. An EM algorithm for wavelet based image restoration[J]. IEEE Transactions on Image Processing, 2003,12(8):906-916.
[19]	Liu Y, Sacchi M D. De-multiple via a fast least squares hyperbolic Radon transform[C] //Salt Lake:72^nd Annual International Meeting,SEG,Expanded Abstracts, 2002,48(4):2182-2185.
[20]	Beck A, Teboulle M. A fast iterative shrinkage-thresholding algorithm for linear inverse problems[J]. SIAM Journal on Imaging Sciences, 2009,2(1):183-202.
[21]	Lu W K. An accelerated sparse time-invariant Radon transform in the mixed frequency-time domain based on iterative 2D model shrinkage[J]. Geophysics, 2013,78(4):V147-V155.