3D surface-related multiples elimination based on improved apex shifted Radon transform

Yang, Fan; Wang, Deli; Hu, Bin; Zhu, Hongyu; Sun, Jing

doi:10.1007/s11600-021-00643-0

Artykuł - szczegóły

Tytuł artykułu

3D surface-related multiples elimination based on improved apex shifted Radon transform

Autorzy

Yang Fan , Wang Deli , Hu Bin , Zhu Hongyu , Sun Jing

Wybrane pełne teksty z tego czasopisma

https://www.springer.com/journal/11600

Identyfikatory

DOI

10.1007/s11600-021-00643-0

Warianty tytułu

Języki publikacji

Abstrakty

Considering the 3D propagation characteristics of seismic waves, theoretically, 3D surface-related multiples elimination (3D SRME) can suppress multiples with high accuracy. However, 3D SRME has strict requirements for acquisition geometry, which makes it difficult to be implemented in practice. In the process of 3D SRME, the multiple contribution gather (MCG) is a collection of wavefields with different propagation paths. The accuracy of the multiple propagation paths in the MCGs can be directly characterized by the inclination of the wavefields, which can achieve the weighted superposition of the wavefields. The direct summation of the sparse MCGs in the crossline direction produces serious spatial aliasing, which can easily cause the contamination of primaries. Based on the kinematic characteristics of multiple propagation, MCGs can be considered as a set of hyperbolas with temporal and spatial characteristics. Then, the direct summation of the sparse MCGs can be transformed into a process of superposition along the hyperbolic integration paths. However, as the stable phase points of the events, the apexes of the hyperbola have different spatial distributions in complex geological structures. Such hyperbolic stacking paths are difficult to be controlled by conventional Radon transform or constrained inversion. In this paper, we modify the apex-shifted hyperbolic Radon transform (ASHRT) to implement the summation of crossline MCGs with variable stable phase points along the hyperbolic integration paths. Improved ASHRT uses local similarity to locate the position of stable phase points, which can improve the stability of the algorithm and the efficiency of the computation. The proposed method is demonstrated on a 3D synthetic data set, as well as on a 3D marine data set, effectively avoiding the spatial aliasing caused by sparse crossline MCGs and improving the accuracy of multiple suppression.

Słowa kluczowe

3D SRME local similarity multiple contribution gathers apex-shifted hyperbolic Radon transform

3D SRME

Wydawca

Instytut Geofizyki PAN
Springer

Czasopismo

Acta Geophysica

Rocznik

2021

Tom

Vol. 69, no. 5

Strony

1679--1696

Opis fizyczny

Bibliogr. 34 poz.

Twórcy

autor

Yang Fan

College of Geo-Exploration Science and Technology, Jilin University, Changchun, China

autor

Wang Deli

College of Geo-Exploration Science and Technology, Jilin University, Changchun, China

autor

Hu Bin

binhu@jlu.edu.cn

College of Geo-Exploration Science and Technology, Jilin University, Changchun, China

https://orcid.org/0000-0002-5608-4966

autor

Zhu Hongyu

College of Geo-Exploration Science and Technology, Jilin University, Changchun, China

autor

Sun Jing

Department of Geosciences, University of Oslo, Oslo, Norway

Bibliografia

1. Baumstein A, Hadidi MT (2006) 3D surface-related multiple elimination: data reconstruction and application to field data. Geophysics 71(3):E25–E33. https://doi.org/10.1190/1.2194515
2. Berkhout AJ, Verschuur DJ (1997) Estimation of multiple scattering by iterative inversion; part 1. Theor Consid Geophys 62(5):1586–1595. https://doi.org/10.1190/1.1444261
3. Bickel SH (2000) Focusing aspects of the hyperbolic Radon transform. Geophysics 65(2):652. https://doi.org/10.1190/1.1444762
4. Borselen RV, Verschuur DJ (2003) Optimization of marine data acquisition for the application of 3D SRME. SEG Tech Progr Expand Abstr 22(1):1965. https://doi.org/10.1190/1.1817709
5. Chen YK, Fomel S (2014) Random noise attenuation using local similarity. In: 84th Annual international meeting, SEG, expanded abstracts. pp. 4360–4365. https://doi.org/10.1190/segam2014-0594.1
6. Dedem EJV, Verschuur DJ (2002) 3D Surface-related multiple prediction using sparse inversion: experience with field data. SEG Tech Prog Expand Abstr 21(1):2094. https://doi.org/10.1190/1.1817115
7. Dedem EJV, Verschuur DJ (2005) 3D surface-related multiple prediction: a sparse inversion approach. Geophysics 70(3):V31–V43. https://doi.org/10.1190/1.1925752
8. Dedem EJV, Schonewille MA, Verschuur DJ (1999) 3D surface-related multiple prediction and data reconstruction. SEG Tech Progr Expand Abstr. https://doi.org/10.1190/1.1820683
9. Dragoset B, Moore I, Yu M et al (2009) 3D general surface multiple prediction: an algorithm for all surveys. SEG Techn Prog Expand Abstr 27(1):2426. https://doi.org/10.1190/1.3059366
10. Dragoset B, Verschuur E, Moore I et al (2010) A perspective on 3D surface-related multiple elimination. Geophysics 75(5):A245–A261. https://doi.org/10.1190/1.3475413
11. Fang YF, Ke BX, Li P et al (2015) Suppression of 3D surface related multiples by optimizing the sum aperture of multiple contribution gathers. Pet Geophys Explor 50(5):848–853
12. Fomel S (2007) Local seismic attributes. Geophysics 72(3):A29–A33. https://doi.org/10.1190/1.2437573
13. Foster DJ, Mosher CC (1992) Suppression of multiple reflections using the Radon transform. Geophysics 57(3):386–395. https://doi.org/10.1190/1.1443253
14. Hokstad K, Sollie R (2006) 3D surface-related multiple elimination using parabolic sparse inversion. Geophysics 71(6):V145–V152. https://doi.org/10.1190/1.2345050
15. Hu B, Wang DL, Wang R (2020) An iterative focal denoising strategy for passive seismic data. Pure Appl Geophys. https://doi.org/10.1007/s00024-020-02534-9
16. Ibrahim A, Terenghi P, Sacchi M D (2015) Wavefield reconstruction using a Stolt-based asymptote and apex shifted hyperbolic Radon transform. In: 85th Annual international meeting, SEG, expanded abstracts pp. 3836–3841. https://doi.org/10.1190/segam2015-5873567.1
17. Ibrahim A (2015) Separating simultaneous seismic sources using robust inversion of Radon and migration operators. Dissertation, University of Alberta
18. Karimpouli S, Malehmir A, Hassani H et al (2015) Automated diffraction delineation using an apex-shifted Radon transform. J Geophys Eng 12(2):199–199. https://doi.org/10.1088/1742-2132/12/2/199
19. Li SF, Shuai PY (2016) Method of 3D GSRME and its application. China Pet Explor 21(004):108–113. https://doi.org/10.3969/j.issn.1672-7703.2016.04.0012
20. Lopez GA, Verschuur DJ (2015) 3D Focal closed-loop SRME for shallow water. SEG Tech Progr Expand. https://doi.org/10.1190/segam2015-5921009.1
21. Moore I, Dragoset WH (2008) General surface multiple prediction (GSMP)-A fleible 3D SRME algorithm. In: 70nd EAGE Conference and exhibition incorporating SPE EUROPEC 2008, Rome, Italy, pp. 9–12 June 2010
22. Moore I, Bisley R (2005) 3D surface-related multiple prediction (SMP): a case history. Lead Edge 24(3):270–274. https://doi.org/10.1190/1.1895311
23. Nowak EJ, Imhof MG (2006) Amplitude preservation of Radon-based multiple-removal filters. Geophysics 71:V123–V126. https://doi.org/10.1190/1.2243711
24. Radon J (1986) On the determination of functions from their integral values along certain manifolds. IEEE Trans Med Imaging 5(4):170–176. https://doi.org/10.1109/TMI.1986.4307775
25. Schonewille MA, Duijndam A (2012) Parabolic Radon transform, sampling and efficiency. Geophysics 66(2):667–678. https://doi.org/10.1190/1.1444957
26. Shi Y, Jing H, Zhang W et al (2017) Suppressing multiples using an adaptive multichannel filter based on L1-norm. Acta Geophys 65:667–681. https://doi.org/10.1007/s11600-017-0053-6
27. Stewart J, Shatilo A, Jing C et al (2004) A comparison of streamer and OBC seismic data at Beryl alpha field U. K North Sea. Geophysics 72(72):841
28. Trad D, Ulrych T, Sacchi M (2003) Latest views of the sparse Radon transform. Geophysics 68(1):386–399. https://doi.org/10.1190/1.1543224
29. Vermeer GJO (2010) 3D symmetric sampling of sparse acquisition geometries. Geophysics 75(6):3796–3801. https://doi.org/10.1190/1.3513640
30. Verschuur DJ, Berkhout AJ, Wapenaar CPA (1989) Wavelet estimation by prestack multiple elimination. SEG Tech Progr Expand Abstr 8(1):1129–1132. https://doi.org/10.1190/1.1889855
31. Verschuur DJ, Berkhout AJ, Wapenaar CPA (1991) Surface-related multiple elimination: application on real data. SEG Tech Progr Expand Abstr. https://doi.org/10.1190/1.1889015
32. Verschuur DJ, Berkhout AJ, Wapenaar CPA (1992) Adaptive surface-related multiple elimination. Geophysics 57(9):1166–1177. https://doi.org/10.1190/1.1443330
33. Wang TX, Wang DL, Sun J et al (2017) Closed-loop SRME based on 3D L1-norm sparse inversion. Acta Geophys 65(6):1145–1152. https://doi.org/10.1007/s11600-017-0098-6
34. Weglein AB (1999) Multiple attenuation: an overview of recent advances and the road ahead. Lead Edge 18(1):40–44. https://doi.org/10.1190/1.1438150

Typ dokumentu

Bibliografia

Identyfikator YADDA

bwmeta1.element.baztech-5e017162-afd5-4129-8ae4-5b56b217aca3