A review of multiple suppression methods based on feedback iteration model

HE Zi-Lin; LI Zhen-Chun; LI Zhi-Na; XU Yi-Peng

doi:10.11720/wtyht.2022.2446

2022 Vol. 46, No. 2

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Article navigation > Geophysical and Geochemical Exploration > 2022 > 46(2): 275-284

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HE Zi-Lin, LI Zhen-Chun, LI Zhi-Na, XU Yi-Peng. 2022. A review of multiple suppression methods based on feedback iteration model. Geophysical and Geochemical Exploration, 46(2): 275-284. doi: 10.11720/wtyht.2022.2446

Citation:

HE Zi-Lin, LI Zhen-Chun, LI Zhi-Na, XU Yi-Peng. 2022. A review of multiple suppression methods based on feedback iteration model. Geophysical and Geochemical Exploration, 46(2): 275-284. doi: 10.11720/wtyht.2022.2446

A review of multiple suppression methods based on feedback iteration model

School of Geosciences,China University of Petroleum(East China),Qingdao 266580,China

Received Date: 12 October 2020

Publish Date: 28 June 2022

Abstract

Abstract

In oil and gas exploration,multiples are usually regarded as the coherent noise that affects the processing and interpretation accuracy of seismic data.Therefore,the study of multiple suppression methods has always been an important research direction in the field of geophysical prospecting.Given that the surface-related multiples are the most developed multiples in seismic exploration,especially in marine seismic exploration,it is necessary to conduct a deep study on the suppression methods of surface-related multiples.At present,the surface-related multiple suppression method that enjoys high accuracy and is widely applied at home and abroad is the feedback iteration method based on the wave equation.This method takes the original seismic data as the predictive factor and requires no other prior conditions and allows for high-precision suppression of surface-related multiples driven by data.A series of more advanced methods have been developed based on the theory of this method in recent years.This paper briefly introduces the theoretical basis of the feedback iteration method(i.e.,the feedback iteration model) firstly and then describes the surface-related multiple suppression mechanisms of the four methods developed based on the feedback iterative model, namely SRME,the inverse data domain method,EPSI,and Cl-SRME.Finally,it compares the advantages and disadvantages of these four methods and proposes the research prospects of multiple suppression methods based on the feedback iteration model.
- surface-related multiple /
- SRME /
- inverse data domain /
- EPSI /
- CL-SRME

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References

[1]	石颖, 邢小林. 表面多次波压制的研究进展:回顾与展望[J]. 地球物理学进展, 2011, 26(6):2046-2054. Google Scholar
[2]	Shi Y, Xing X L. Investigation progress on surface-related multiple suppression:Review and outlook[J]. Progress in Geophysics, 2011, 26(6):2046-2054. Google Scholar
[3]	张文武. 基于稀疏反演的表面多次波压制方法研究[D]. 大庆: 东北石油大学, 2018. Google Scholar
[4]	Zhang W W. Research on surface-related multiple attenuation by sparse inversion[D]. Daqing: Northeast Petroleum University, 2018. Google Scholar
[5]	Riley D C, Claerbout J F. 2-D multiple reflections[J]. Digital Library Home, 1976, 41(4):592-620. Google Scholar
[6]	Kennett B L N. The suppression of surface multiples on seismic records[J]. Geophysical Prospecting, 1979, 27(3):584-600. Google Scholar
[7]	Berkhout A J. Seismic migration:Imaging of acoustic energy by wave field extrapolation[M]. Amsterdam:Elsevier Scientific Pub. Co., 1982. Google Scholar
[8]	Verschuur D J, Berkhout A J, Wapenaar C P A. Adaptive surface-related multiple elimination[J]. Geophysics, 1992, 57(9):1166-1177. Google Scholar
[9]	Berkhout A J, Verschuur D J. Estimation of multiple scattering by iterative inversion,Part 1:Theoretical considerations[J]. Geophysics, 1997, 62(5):1586-1595. Google Scholar
[10]	Verschuur D J, Berkhout A J. Estimation of multiple scattering by iterative inversion,Part II:Practical aspects and examples[J]. Geophysics, 1997, 62(5):1596-1611. Google Scholar
[11]	Verschuur D J. Surface-related multiple elimination,an inversion approach[D]. Delft: Delft University of Technology, 1991. Google Scholar
[12]	Monk D J. Wave-equation multiple suppression using constrained gross-equalization[J]. Geophysical Prospecting, 1993, 41(6):725-736. Google Scholar
[13]	Spitz, Simon. Pattern recognition,spatial predictability, and subtraction of multiple events[J]. Leading Edge, 1999, 18(1):55-58. Google Scholar
[14]	Guitton A. Multiple attenuation with multidimensional prediction-error filter[J]. Geophysics, 2003:57-74. Google Scholar
[15]	Wang Y. Multiple subtraction using an expanded multichannel matching filter[J]. Geophysics, 2003, 68(1):346-354. Google Scholar
[16]	陆文凯, 骆毅, 赵波, 等. 基于独立分量分析的多次波自适应相减技术[J]. 地球物理学报, 2004, 47(5):886-891. Google Scholar
[17]	Lu W K, Luo Y, Zhao B, et al. Adaptive multiple wave subtraction using independent component analysis[J]. Chinese Journal of Geophysics, 2004, 47(5):886-891. Google Scholar
[18]	Van Dedem E J. 3D surface-related multiple prediction[D]. Delft: Delft University of Technology, 2002. Google Scholar
[19]	Van Dedem E J, Verschuur D J. Analysis of surface-related multiples in 3D media[C]// SEG Expanded Abstracts, 1997, 16(1):1180-1183. Google Scholar
[20]	Van Dedem E J, Verschuur D J. 3D surface-related multiple prediction,an inversion approach[C]// SEG Expanded Abstracts, 2000:1965-1968. Google Scholar
[21]	Van Dedem E J, Verschuur D J. 3D surface-related multiple prediction:A sparse inversion approach[J]. Geophysics, 2005, 70(3):V31-V43. Google Scholar
[22]	Anatoly B, Mohamed T H. 3D surface-related multiple elimination:Data reconstruction and application to field data[J]. Geophysics, 2006, 71(3):E25-E33. Google Scholar
[23]	石颖, 王维红, 李莹, 等. 基于波动方程三维表面多次波预测方法研究[J]. 地球物理学报, 2013, 56(6):2023-2032. Google Scholar
[24]	Shi Y, Wang W H, Li Y, et al. 3D surface-related multiple prediction approach investigation based on wave equation[J]. Chinese Journal of Geophysics, 2013, 56(6):2023-2032. Google Scholar
[25]	井洪亮, 石颖, 李莹, 等. 基于L1/L2范数的表面多次波自适应相减方法[J]. 石油地球物理勘探, 2015, 50(4):619-625. Google Scholar
[26]	Jing H L, Shi Y, Li Y, et al. Surface-related multiple adaptive subtraction method based on L1/L2 norm[J]. OGP, 2015, 50(4):619-625. Google Scholar
[27]	Lopez G A, Verschuur D J. Closed-Loop SRME — A New Direction in Surface Multiple Removal Algorithms[C]// EAGE,Extended Abstracts, 2014. Google Scholar
[28]	Berkhout A J. Seismic processing in the inverse data space[J]. Geophysics, 2006, 71(4):A29-A33. Google Scholar
[29]	Berkhout A J, Verschuur D J. Multiple removal and wavelet deconvolution in the inverse data space[C]// SEG Expanded Abstracts, 2006:2684-2688. Google Scholar
[30]	Kelamis P G, Zhu W, Rufaii K O, et al. Land multiple attenuation — The future is bright[C]// SEG Expanded Abstracts, 2006, 25(1):2699-2703. Google Scholar
[31]	Luo Y, Zhu W, Kelamis P G. Internal multiple reduction in inverse-data domain[C]// SEG Expanded Abstracts, 2007:1711-1723. Google Scholar
[32]	Berkhout A J, Verschuur D J. Time lapse processing in the inverse data space[C]// SEG Expanded Abstracts, 2007:2919-2923. Google Scholar
[33]	Berkhout A J, Verschuur D J. Seismic processing in the inverse data space,removal of surface —Related and internal multiples[C]// EAGE Extended Abstracts, 2007. Google Scholar
[34]	马继涛, 陈小宏, 黄小宁. 反数据域压制多次波方法研究[J]. 石油地球物理勘探, 2009, 44(5):537-542. Google Scholar
[35]	Ma J T, Chen X H, Huang X N. Studying on multiple elimination in inverse data domain[J]. OGP, 2009, 44(5):537-542. Google Scholar
[36]	马继涛, Sen M K, 陈小宏. 平面波域反数据处理压制多次波方法研究[J]. 地球物理学报, 2009, 52(3):808-816. Google Scholar
[37]	Ma J T, Sen M K, Chen X H. Multiple attenuation using inverse data processing in the plane-wave domain[J]. Chinese Journal of Geophysics, 2009, 52(3):808-816. Google Scholar
[38]	Ma J T, Sen M K, Chen X H. Free-surface multiple attenuation using inverse data processing in the coupled plane-wave domain[J]. Geophysics, 2009, 74(4):V75-V81. Google Scholar
[39]	Van Groenestijn G J, Verschuur D J. Estimating primaries by sparse inversion and application to near-offset data reconstruction[J]. Geophysics, 2009, 74(3):A23-A28. Google Scholar
[40]	Van Groenestijn G J, Verschuur D J. Estimation of primaries by sparse inversion from passive seismic data[J]. Geophysics, 2010, 75(4):SA61-SA69. Google Scholar
[41]	Van Groenestijn G J A, Ross W. Primary estimation on OBC data by sparse inversion[C]// SEG Expanded Abstracts, 2011:311-353. Google Scholar
[42]	Van Groenestijn G J A, Verschuur D J. Estimation of primaries by sparse inversion applied to up/down wavefields[C]// SEG Expanded Abstracts, 2009:3143-3147. Google Scholar
[43]	Van Groenestijn G J A, Verschuur D J. Using surface multiples to estimate primaries by sparse inversion from blended data[J]. Geophysical Prospecting, 2015, 59(1):10-23. Google Scholar
[44]	Van Groenestijn G J A, Verschuur D J. Towards a new approach for primary estimation[C]// SEG Expanded Abstracts, 2008, 27(1):2487-2491. Google Scholar
[45]	Van Groenestijn G J A, Verschuur D J. Incorporating the source array into primary estimation[C]// EAGE Extended Abstracts, 2010. Google Scholar
[46]	Van Groenestijn G J, Verschuur D J. Estimation of primaries by sparse inversion from blended data[C]// EAGE Extended Abstracts, 2009. Google Scholar
[47]	刘国昌, 陈小宏, 宋家文. 基于稀疏反演的OBS数据多次波压制方法[J]. 地球物理学报, 2013, 56(12):4288-4296. Google Scholar
[48]	Liu G C, Chen X H, Song J W. Estimation of primaries and multiples by sparse inversion for OBS data with integration of streamer data[J]. Chinese Journal of Geophysics, 2013, 56(12):4288-4296. Google Scholar
[49]	Lin T T Y, Herrmann F J. Robust estimation of primaries by sparse inversion via one-norm minimization[J]. Geophysics, 2013, 78(3):R133-R150. Google Scholar
[50]	Lopez G, Verschuur D J. SRME and estimation of primaries by sparse inversion:a hybrid approach[C]// SEG Expanded Abstracts, 2012: 1-5. Google Scholar
[51]	Ypma F H C, Verschuur D J. Estimating primaries by sparse inversion, a generalized approach[J]. Geophysical Prospecting, 2013, 61(s1):94-108. Google Scholar
[52]	Angarita G A L, Verschuur D J. Estimation of primaries by sparse inversion-parameterization via the focal domain[C]// EAGE Extended Abstracts, 2013. Google Scholar
[53]	Feng F, Wang D L, Zhu H, et al. Estimating primaries by sparse inversion of the 3D Curvelet transform and the L1-norm constraint[J]. Applied Geophysics, 2013, 10(2):201-209. Google Scholar
[54]	程浩, 王德利, 冯飞, 等. L1范数约束被动源数据稀疏反演一次波估计[J]. 地球物理学报, 2015, 58(2):674-684. Google Scholar
[55]	Cheng H, Wang D L, Feng F, et al. Estimating primaries by sparse inversion of passive-source seismic data with L1-norm constraint[J]. Chinese Journal of Geophysics, 2015, 58(2):674-684. Google Scholar
[56]	Van Groenestijn G J A. Estimation of primaries and multiples by sparse inversion[D]. Delft:Delft University of Technology, 2010. Google Scholar
[57]	王铁兴. 三维稀疏约束反演Closed-loop SRME方法研究[D]. 长春: 吉林大学, 2020:201-209. Google Scholar
[58]	Wang T X. Research on the Closed-loop SRME based on the 3D sparse inversion[D]. Changchun: Jilin University, 2020:201-209. Google Scholar
[59]	Lopez G A, Verschuur D J. Closed-loop surface-related multiple elimination and its application to simultaneous data reconstruction[J]. Geophysics, 2015, 80(6):V189-V199. Google Scholar
[60]	Gabriel A, Lopez, Verschuur D J. Closed-loop surface-related multiple elimination and its application to simultaneous data reconstruction[J]. Geophysics, 2015, 80(6):V189-V199. Google Scholar
[61]	Lopez G A, Verschuur D J. 3D focal Closed-Loop SRME for shallow water[C]// SEG Expanded Abstracts, 2015:4418-4422. Google Scholar
[62]	Vrolijk J W, Verschuur D. Integrated receiver deghosting and closed-loop surface multiple elimination[C]// SEG Expanded Abstracts, 2016:4481-4486.[53] Wang T, Wang D, Sun J, et al. Closed-loop SRME based on 3D L1-norm sparse inversion[J]. Acta Geophysica, 2017, 65(6):1145-1152. [54] Vrolijk J W, Verschuur D. Integrated receiver deghosting and closed-loop surface multiple elimination[J]. Geophysics, 2017, 82(4):T133-T141. Google Scholar