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Random noise reduction using a hybrid method based on ensemble empirical mode decomposition

WEI CHEN1 ,  DONG ZHANG2 ,  YANGKANG CHEN3*
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1 Institute of Geophysics and Petroleum Resources, Yangtze University, Daxue Road 111, Caidian District, Wuhan 430100, P.R. China. cwjycd@163.com,
2 State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum, Fuxue Road 18, Beijing 102200, P.R. China. zhangdongconan@sina.com,
3 Bureau of Economic Geology, John A. and Katherine G. Jackson School of Geosciences, The University of Texas at Austin, University Station, Box X, Austin, TX 78713 8924, U.S.A. chenyk1990@gmail.com,
JSE 2017, 26(3), 227–249;
Submitted: 9 June 2025 | Revised: 9 June 2025 | Accepted: 9 June 2025 | Published: 9 June 2025
© 2025 by the Authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
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Abstract

Chen, W., Zhang, D. and Chen, Y., 2017. Random noise reduction using a hybrid method based on ensemble empirical mode decomposition. Journal of Seismic Exploration, 26: 227-249. We have proposed a novel hybrid random noise reduction method based on ensemble empirical mode decomposition (EEMD) and wavelet threshold filtering. Firstly, the frequency band ranges of effective signal and noise in the initial seismic data set are studied by Fourier spectrum analysis method. Secondly, we make use of EEMD method to obtain the intrinsic mode functions (IMFs) of each original noisy trace. Wavelet threshold filtering is then applied to the high frequency IMFs of each trace to acquire the new denoised high frequency IMFs. Finally, by stacking the filtered high frequency IMFs with the low frequency IMFs and the trend item, we can obtain the ultimately denoised seismic data set. The proposed approach is confirmed via two synthetic data examples and one field data example. The results demonstrate that the proposed approach can achieve much cleaner denoising performance without harming most useful signals.

Keywords
ensemble empirical mode decomposition (EEMD)
wavelet threshold filtering
seismic data
random noise reduction
References
  1. Beasley, C.J., Chambers, R.E. and Jiang, Z., 1998. A new look at simultaneous sources. Expanded
  2. Abstr., 68th Ann. Internat. SEG Mtg., New Orleans: 133-135.
  3. Berkhout, A.J., 2008. Changing the mindset in seismic data acquisition. The Leading Edge, 27: 924-
  5. Canales, L., 1984. Random noise reduction. Expanded Abstr., 54th Ann. Internat. SEG Mtg.,
  6. Atlanta: 525-527.
  7. Chen, Y., Zhou, C., Yuan, J. and Jin, Z., 2014. Application of empirical mode decomposition to
  8. random noise attenuation of seismic data. J. Seismic Explor., 23: 481-495.
  9. Chen, Y., 2016. Dip-separated structural filtering using seislet thresholding and adaptive empirical
  10. mode decomposition based dip filter. Geophys. J. Internat., 206: 457-469.
  11. Chen, Y., Ma, J. and Fomel, S., 2016. Double-sparsity dictionary for seismic noise attenuation.
  12. Geophysics, 81(2): V17-V30.
  13. Chen, Y. and Fomel, S., 2015. Random noise attenuation using local signal-and-noise
  14. orthogonalization. Geophysics, 80(6): WD1-WD9.
  15. Chen, Y. and Jin, Z., 2016. Simultaneously removing noise and increasing resolution of seismic data
  16. using waveform shaping. IEEE Geosci. Remote Sens. Lett., 13: 102-104.
  17. Chen, Y. and Ma, J., 2014. Random noise attenuation by fx empirical-mode decomposition
  18. predictive filtering. Geophysics, 79(3): V81-V91.
  19. Gan, S., Chen, Y., Zu, S., Qu, S. and Zhong, W., 2015. Structure-oriented singular value
  20. decomposition for random noise attenuation of seismic data. J. Geophys. Engineer. , 12: 262-
  22. Gan, S., Wang, S., Chen, Y., Chen, J., Zhong, W. and Zhang, C., 2016a. Improved random noise
  23. attenuation using fx empirical mode decomposition and local similarity. Appl. Geophys., 13:
  24. 127-134.
  25. Gan, S., Wang, S., Chen, Y., Chen, X. and Xiang, K., 2016b. Separation of simultaneous sources
  26. using a structural-oriented median filter in the flattened dimension. Comput. Geosci., 86:
  27. 46-54.
  28. Gan, S., Wang, S., Chen, Y., Qu, S. and Zu, S., 2016c. Velocity analysis of simultaneous- source
  29. data using high-resolution semblancecoping with the strong noise. Geophys. J. Internat. , 204:
  30. 768-779.
  31. Han, J. and Mirko, V., 2013. Empirical mode decomposition for seismic time-frequency analysis.
  32. Geophysics, 78(2): 09-019.
  33. Huang, N.E., Shen, Z., Long, S.R., Wu, M.C., Shih, H.H., Zheng, Q., Yen, N.-C., Tang, C.C.
  34. and Liu, H.H., 1998. The empirical mode decomposition and the Hilbert spectrum for
  35. nonlinear and non-stationary time series analysis. Proc. Roy. Soc. London. Series A:
  36. Mathemat., Phys., Engineer. Sci., 454: 903-995.
  37. Huang, W., Wang, R., Chen, Y., Li, H. and Gan, S., 2016. Damped multichannel singular
  38. spectrum analysis for 3D random noise attenuation. Geophysics, 81(4): V261-V270.
  39. Li, H., Wang, R., Cao, S., Chen, Y. and Huang, W., 2016. A method for low-frequency noise
  40. suppression based on mathematical morphology in microseismic monitoring. Geophysics,
  41. 81(3): V159-V 167.
  42. Liu, G., Fomel, S., Jin, L. and Chen, X., 2009. Stacking seismic data using local correlation.
  43. Geophysics, 74: V43-V48.
  44. RANDOM NOISE REDUCTION 249
  45. Liu, W., Cao, S., Chen, Y. and Zu, S., 2016a. An effective approach to attenuate random noise
  46. based on compressive sensing and curvelet transform. J. Geophys. Engineer., 13: 135-145.
  47. Liu, W., Cao, S. and Chen, Y., 2016b. Application of variational mode decomposition in random
  48. noise attenuation and time-frequency analysis of seismic data. Extended Abstr., 78th EAGE
  49. Conf., Vienna.
  50. Liu, W., Cao, S. and Chen, Y., 2016c. Applications of variational mode decomposition in seismic
  51. time-frequency analysis. Geophysics, 81(5): V365-V378.
  52. Liu, Y., 2013. Noise reduction by vector median filtering. Geophysics, 78: V79-V87.
  53. Mao, J. and Gao, J., 2006. On the denoising method of prestack seismic data in the wavelet domain.
  54. Expanded Abstr., 76th Ann. Internat. SEG Mtg., New Orleans: 25(1).
  55. Ulrych, T., Freire, J. and Siston, P., 1988. Eigenimage processing of seismic sections. Expanded
  56. Abstr., 58th Ann. Internat. SEG Mtg., Anaheim: 525-527.
  57. Wang, Y., 1999. Random noise attenuation using forward-backward linear prediction. J. Seismic
  58. Explor., 8: 133-142.
  59. Wu, Z. and Huang, N., 2009. Ensemble empirical mode decomposition: A noise-assisted data
  60. analysis method. Advan. Adapt. Data Anal., 1: 1-41.
  61. Xue, Z., Chen, Y., Fomel, S. and Sun, J., 2016. Seismic imaging of incomplete data and
  62. simultaneous-source data using least-squares reverse time migration with shaping
  63. regularization. Geophysics, 81: $11-S20.
  64. Yang, W., Wang, R., Chen, Y., Wu, J., Qu, S., Yuan, J. and Gan, S., 2015a. Application of
  65. spectral decomposition using regularized non-stationary autoregression to random noise
  66. attenuation. J. Geophys. Engineer., 12: 175-187.
  67. Yang, W., Wang, R., Wu, J., Chen, Y., Gan, S. and Zhong, W., 2015b. An efficient and effective
  68. common reflection surface stacking approach using local similarity and plane- wave
  69. flattening. J. Appl. Geophys., 117: 67-72.
  70. Yuan, S. and Wang, S., 2013. Edge-preserving noise reduction based on bayesian inversion with
  71. directional difference constraints. J. Geophys. Engineer., 10(2): 123-136.
  72. Yuan, S., Wang, S. and Li, G., 2012. Random noise reduction using bayesian inversion. J.
  73. Geophys. Engineer., 9: 60-68.
  74. Zhang, R. and Ulrych, T., 2003. Physical wavelet frame denoising. Geophysics, 68: 225- 231.
  75. Zu, S., Zhou, H., Chen, Y., Qu, S., Zou, X., Chen H. and Liu, R., 2016. A periodically varying
  76. code for improving deblending of simultaneous sources in marine acquisition. Geophysics,
  77. 81(3): V213-V225.
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Journal of Seismic Exploration, Electronic ISSN: 0963-0651 Print ISSN: 0963-0651, Published by AccScience Publishing
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