Lithologic Reservoirs ›› 2019, Vol. 31 ›› Issue (5): 92-100.doi: 10.12108/yxyqc.20190510

• EXPLORATION TECHNOLOGY • Previous Articles     Next Articles

Random noise attenuation based on joint sparse representation in common offset gathers

SHI Zhanzhan1,2, XIA Yanqing1, ZHOU Huailai2, WANG Yuanjun2   

  1. 1. The Engineering & Technical College of Chengdu University of Technology, Leshan 614000, Sichuan, China;
    2. College of Geophysics, Chengdu University of Technology, Chengdu 610059, China
  • Received:2019-03-28 Revised:2019-05-20 Online:2019-09-21 Published:2019-09-16

Abstract: Under the restriction of multiplicity and single-channel signal processing methods,the traditional onedimensional random noise attenuation method based on sparse representation faces two problems:Firstly,the single-channel signal processing method does not consider the spatial correlation of the effective signals,thus the de-noise performance degrades significantly and may damage effective waves. Secondly,the sparse representation algorithm suffers from multiplicity,and the processing results of adjacent seismic traces are quite different, which makes it difficult to adapt to the spatial variation. The waveforms in the pre-stack common offset gathers are characterized by horizontally events,and have the same two-way travel time. Therefore,each trace signal in a gather shares the universal support. In this gather,joint sparse representation was used to suppress random noise,which can balance the correlation between channels and spatial variations of signals so as to reduce the multi-solution of the algorithm. The optimal sparse representation was obtained under the same conditions for each channel participated in the calculation,so the processing result had good consistency. The results of numerical simulation and practical data trial show that the proposed method can suppress random noise and maintain the effective signal,and has a good application effect.

Key words: joint sparse representation, alternating direction method of multipliers, common offset gather, random noise attenuation, L2,1-norm misfit function

CLC Number: 

  • P631.4
[1] 王西文,雍学善,王宇超,等.面对重点勘探领域的地震技术研究和应用实效. 岩性油气藏,2010,22(3):83-90. WANG X W,YONG X S,WANG Y C,et al. Study and application of seismic technologies for key exploration fields. Lithologic Reservoirs,2010,22(3):83-90.
[2] ANVARI R,SIAHSAR M A N,GHOLTASHI S,et al. Seismic random noise attenuation using synchro squeezed wavelet transform and low-rank signal matrix approximation. IEEE Transactions on Geoscience and Remote Sensing,2017,55(11):6574-6581.
[3] ABMA R,CLAERBOUT J. Lateral prediction for noise attenuation by t-x and f-x techniques. Geophysics,1995,60(6):1887-1896.
[4] CANALES L L. Random noise reduction. SEG Technical Program Expanded Abstracts,1984:525-527.
[5] LIU Y,LIU C,WANG D. A 1 D time-varying median filter for seismic random,spike-like noise elimination. Geophysics,2008, 74(1):V17-V24.
[6] LIU Y K. Noise reduction by vector median filtering. Geophysics, 2013,78(3):V79-V87.
[7] 陈可洋,吴沛熹,杨微. 扩散滤波方法在地震资料处理中的应用研究. 岩性油气藏,2014,26(1):117-122. CHEN K Y,WU P X,YANG W. Application of diffusion filtering method to the seismic data processing. Lithologic Reservoirs,2014,26(1):117-122.
[8] CHEN Y K. Fast dictionary learning for noise attenuation of multidimensional seismic data. Geophysical Journal International, 2017,209(1):21-31.
[9] HAN J,VAN DER BAAN M. Microseismic and seismic denoising via ensemble empirical mode decomposition and adaptive thresholding Denoising via EEMD. Geophysics,2015,80(6):S69-S80.
[10] KREIMER N,SACCHI M D. A tensor higher-order singular value decomposition for prestack seismic data noise reduction and interpolation. Geophysics,2012,77(3):V113-V122.
[11] CHEN Y K,MA J W,FOMEL S. Double-sparsity dictionary for seismic noise attenuation. Geophysics,2016,81(2):V103-V116.
[12] DENG L,YUAN S Y,WANG S X. Sparse Bayesian learningbased seismic denoise by using physical wavelet as basis functions. IEEE Geoscience and Remote Sensing Letters,2017,14(11):1993-1997.
[13] ZHANG Z,XU Y,YANG J,et al. A survey of sparse representation:Algorithms and applications. IEEE Access,2015,3:490-530.
[14] MANSOUR H,WASON H,LIN T T Y,et al. Randomized marine acquisition with compressive sampling matrices. Geophysical Prospecting,2012,60(4):648-662.
[15] MANSOUR H,HERRMANN F J,YILMAZ Ö. Improved wavefield reconstruction from randomized sampling via weighted onenorm minimization. Geophysics,2013,78(5):V193-V206.
[16] HERRMANN F J,LI X. Efficient least-squares imaging with sparsity promotion and compressive sensing. Geophysical Prospecting,2012,60(4):696-712.
[17] ZHANG R,CASTAGNA J. Seismic sparse-layer reflectivity inversion using basis pursuit decomposition. Geophysics,2011, 76(6):R147-R158.
[18] DONOHO D L. Compressed sensing. IEEE Transactions on Information Theory,2006,52(4):1289-1306.
[19] 许志强. 压缩感知. 中国科学:数学,2012,42(9):865-877. XU Z Q. Compressed sensing:a survey. Scientia Sinica Mathematica,2012,42(9):865-877.
[20] CAI T T,WANG L. Orthogonal matching pursuit for sparse signal recovery with noise. IEEE Transactions on Information Theory,2011,57(7):4680-4688.
[21] YANG J F,ZHANG Y. Alternating direction algorithms for l1-problems in compressive sensing. SIAM Journal on Scientific Computing,2011,33(1):250-278.
[22] DENG W,YIN W T,ZHANG Y. Group sparse optimization by alternating direction method. Proceedings of SPIE,2013:8858.
[23] PRESNELL B,TURLACH B A,OSBORNE M R. A new approach to variable selection in least squares problems. IMA Journal of Numerical Analysis,2000,20(3):389-403.
[24] PARIKH N,BOYD S. Proximal algorithms. Foundations and Trends® in Optimization,2014,1(3):127-239.
[25] COTTER S F,RAO B D,ENGAN K,et al. Sparse solutions to linear inverse problems with multiple measurement vectors. IEEE Transactions on Signal Processing,2005,53(7):2477-2488.
[26] ELDAR Y C,RAUHUT H. Average case analysis of multichannel sparse recovery using convex relaxation. IEEE Transactions on Information Theory,2010,56(1):505-519.
[27] JIN Y,RAO B D. Insights into the stable recovery of sparse solutions in overcomplete representations using network information theory. 2008 IEEE International Conference on Acoustics, Speech and Signal Processing,Las Vegas,2008.
[28] EDGAR J A,VAN DER BAAN M. How reliable is statistical wavelet estimation? Geophysics,2011,76(4):V59-V68.
[29] 冯玮,胡天跃,姚逢昌,等. 非稳态地震记录时变子波估计. 地球物理学报,2017,60(1):305-315. FENG W,HU T Y,YAO F C,et al. Time-varying seismic wavelet estimation from nonstationary seismic data. Chinese Journal of Geophysics,2017,60(1):305-315.
[30] 夏洪瑞,周开明,黄桥,等. 波阻抗反演技术中空变子波的求取. 石油物探,2002,41(4):470-474. XIA H R,ZHOU K M,HUANG Q,et al. Calculation of spatialvariant wavelet in acoustic impedance inversion. Geophysical Prospecting for Petroleum,2002,41(4):470-474.
[31] 刘晓晶,印兴耀,吴国忱,等.基于基追踪弹性阻抗反演的深部储层流体识别方法. 地球物理学报,2016,59(1):277-286. LIU X J,YIN X Y,WU G C,et al. Identification of deep reservoir fluids based on basis pursuit inversion for elastic impedance. Chinese Journal of Geophysics,2016,59(1):277-286.
[32] 周东勇,文晓涛,贺振华,等. MP算法在地震波阻抗反演中的应用. 成都理工大学学报(自然科学版),2014,41(1):87-93. ZHOU D Y,WEN X T,HE Z H,et al. Application of matching pursuits to seismic inversion. Journal of Chengdu University of Technology(Science & Technology Edition),2014,41(1):87-93.
[33] YIN X Y,LIU X J,ZONG Z Y. Pre-stack basis pursuit seismic inversion for brittleness of shale. Petroleum Science,2015,12(4):618-627.
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