Comparative analysis of matching pursuit algorithms for Kirchhoff migration on compressed data

  • Carlos A. Fajardo Universidad Industrial de Santander https://orcid.org/0000-0002-8995-4585
  • Fabián Sánchez Universidad Industrial de Santander
  • Ana B. Ramirez Universidad Industrial de Santander
Keywords: Migration over compressed data, Matching Pursuit, Memory wall, Kirchhoff migration

Abstract

Currently, the amount of recorded data in a seismic survey is in the order of hundreds of Terabytes. The processing of such amount of data implies significant computational challenges. One of them is the I/O bottleneck between the main memory and the node memory. This bottleneck results from the fact that the disk memory access speed is thousands-fold slower than the processing speed of the co-processors (eg. GPUs). We propose a special Kirchhoff migration that develops the migration process over compressed data. The seismic data is compressed by using three well-known Matching Pursuit algorithms. Our approach seeks to reduce the number of memory accesses to the disk required by the Kirchhoff operator and to add more mathematical operations to the traditional Kirchhoff migration. Thus, we change slow operations (memory access) for fast operations (math operations). Experimental results show that the proposed method preserves, to a large extent, the seismic attributes of the image for a compression ratio up to 20:1.

References

Wu, C., T. Wang, H. Wang, H. Li, and S. Liu, (2018). Full 3D double square root migration method for VTI media and its application in real data, Int. Geophys. Conf. Beijing, China, 24-27 April 2018, 600-603. https://doi.org/10.1190/IGC2018-147

Gregg, C. and K. Hazelwood, (2011). Where is the data? Why you cannot debate CPU vs. GPU performance without the answer, ISPASS 2011 - IEEE Int. Symp. Perform. Anal. Syst. Softw., 134-144. https://doi.org/10.1109/ISPASS.2011.5762730

Salamanca, W. A., A.-B. Ramirez, and F.-A. Vivas, (2018). Comparative analysis of 3D RTM Implementation Strategies for an Efficient Use of Memory in a Single GPU, CT&F-Ciencia, Tecnol. y Futur., 8(2), 75-82. https://doi.org/10.29047/01225383.83

Fajardo, C. A., Ó. M. Reyes, and J. (Universidad R. J. C. Castillo, (2018). Reducing the I/O Bottleneck by a Compression Strategy, Eng. Lett., 26(2), 203-209. [Online]. Available: http://www.engineeringletters.com/issues_v26/issue_2/EL_26_2_01.pdf

Bouska, J. and S. Gray, (1998). Migration of unequally sampled compressed seismic data, Expand. Abstr. Tech. Program, SEG 68th Annu. Meet., 1128-1130. https://doi.org/10.1190/1.1820087

Yu, Z., G. A. McMechan, P. D. Anno, and J. F. Ferguson, (2004). Wavelet-transform-based prestack multiscale Kirchhoff migration, Geophysics, 69(6), 1505-1512. https://doi.org/10.1190/1.1836823

Zheludev, V. A., E. Ragoza, and D. D. Kosloff, (2002). Fast Kirchhoff migration in the wavelet domain, Explor. Geophys., 33(1), 23-27. https://doi.org/10.1071/EG02023

Alkhalifah, T., (2011). Efficient traveltime compression for 3D prestack Kirchhoff migration, Geophys. Prospect., 59(1), 1-9. https://doi.org/10.1111/j.1365-2478.2010.00886.x

Mallat, S. G., (1993). Matching pursuits with time-frequency dictionaries, IEEE Trans. Signal Process., 41(12), 3397-3415. https://doi.org/10.1109/78.258082

Wang, B. and K. Pann, (1996). Kirchhoff migration of seismic data compressed by matching pursuit decomposition, in Expanded abstracts of the technical program, SEG 66th annual meeting, (1), 1642--1645. https://doi.org/10.1190/1.1826441

Li, X.--G., B. Wang, K. Pann, J. Anderson, and L. Deng, (1998). Fast migration using a matching pursuit algorithm, in Expanded Abstracts of the Technical Program, SEG 68th Annual Meeting, 1732-1735. https://doi.org/10.1190/1.1820261

Lin, L., B. Shi, and P. An, (2016). Multiwavelet prestack Kirchhoff migration, Geophysics, 81(3), S79-S85. https://doi.org/10.1190/geo2015-0140.1

Xiongwen, W., W. Huazhong, and Z. Xiaopeng, (2014). High dimensional seismic data interpolation with weighted matching pursuit based on compressed sensing, J. Geophys. Eng., 11(6). https://doi.org/10.1088/1742-2132/11/6/065003

Wang, Y., (2007). Seismic time-frequency spectral decomposition by matching pursuit, Geophysics, 72(1), V13-V20. https://doi.org/10.1190/1.2387109

Liu, J. and K. J. Marfurt, (2005). Matching pursuit using Morlet wavelets., in 2005 SEG Annual Meeting, (4), 786-790. https://doi.org/10.1190/1.2148276

Lin, H., Y. Li, H. Ma, B. Yang, and J. Dai, (2015). Matching-pursuit-based spatial-trace time-frequency peak filtering for seismic random noise attenuation, IEEE Geosci. Remote Sens. Lett., 12(2), 394-398. https://doi.org/10.1109/LGRS.2014.2344020

Gholamy, A. and V. Kreinovich, (2014). Why Ricker wavelets are successful in processing seismic data: Towards a theoretical explanation, IEEE SSCI 2014 - 2014 IEEE Symp. Ser. Comput. Intell. - CIES 2014 2014 IEEE Symp. Comput. Intell. Eng. Solut. Proc., 11-16. https://doi.org/10.1109/CIES.2014.7011824

Duval, L. C. and V. Buitran, (2001). Compression denoising: using seismic compression for uncoherent noise removal, EAGE 63rd Conf. Tech. Exhib. Netherlands, (June). https://doi.org/10.3997/2214-4609-pdb.15.A-21

Cai, T. T. and L. Wang, (2011). Orthogonal matching pursuit for sparse signal recovery with noise, IEEE Trans. Inf. Theory, 57(7), 4680-4688. https://doi.org/10.1109/TIT.2011.2146090

Pati, Y. C., R. Rezaiifar, and P. S. Krishnaprasad, (1993). Orthogonal matching pursuit: Recursive function approximation with applications to wavelet decomposition, in Signals, Systems and Computers, 1993. 1993 Conference Record of The Twenty-Seventh Asilomar Conference on, 40-44. [Online]. Available: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.348.5735

Santos*, P. N. and R. C. Pestana, (2015). Least-squares Kirchhoff migration using traveltimes based on the maximum amplitude criterion by the rapid expansion method, in 14th International Congress of the Brazilian Geophysical Society & EXPOGEF, Rio de Janeiro, Brazil, 3-6 August 2015, 1043-1047. https://doi.org/10.1190/sbgf2015-207

Vidale, J., (1988). Finite-difference calculation of travel times, Bull. Seismol. Soc. Am., 78(6), 2062-2076. Available at: https://earthweb.ess.washington.edu/vidale/Reprints/BSSA/1988_Vidale.pdf

How to Cite
Fajardo, C. A., Sánchez, F., & Ramirez, A. B. (2021). Comparative analysis of matching pursuit algorithms for Kirchhoff migration on compressed data . CT&F - Ciencia, Tecnología Y Futuro, 11(1), 47-53. https://doi.org/10.29047/01225383.142

Downloads

Download data is not yet available.
Published
2021-06-30
Section
Scientific and Technological Research Articles

Funding data

Crossref Cited-by logo