1887

Abstract

Summary

Improvement of the signal-to-noise ratio (S/N) of seismic data is necessary in many seismic exploration areas. The attenuation of random noise is an important subject in improving the S/N. Geophysicists usually utilize the difference between signal and random noise in certain attributes, such as frequency, wave number, or correlation. In this paper, we have proposed a novel method utilizing the planar morphological attribute of seismic data to separate signal and random noise. The extraction of the morphological attribute is implemented by the planar morphological operations. The attenuation of random noise is achieved by removing the energy in the smaller morphological scales. We have named our proposed method planar mathematical morphological filtering (PMMF). Application of PMMF on synthetic and field seismic data demonstrates superior performance compared with the 2D median filtering and the singular spectrum analysis (SSA) method.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.201700575
2017-06-12
2024-03-29
Loading full text...

Full text loading...

References

  1. Chen, Y., Huang, W., Zhang, D. and Chen, W.
    [2016] An open-source Matlab code package for improved rank-reduction 3D seismic data denoising and reconstruction. Computers & Geosciences, 95, 59–66.
    [Google Scholar]
  2. Fomel, S. and Liu, Y.
    [2010] Seislet transform and seislet frame. Geophysics, 75(3), V25–V38.
    [Google Scholar]
  3. Gan, S., Wang, S., Chen, Y., Chen, X., Huang, W. and Chen, H.
    [2016] Compressive sensing for seismic data reconstruction via fast projection onto convex sets based on seislet transform. Journal of Applied Geophysics, 130, 194–208.
    [Google Scholar]
  4. Huang, W., Wang, R., Chen, Y., Li, H. and Gan, S.
    [2016a] Damped multichannel singular spectrum analysis for 3D random noise attenuation. Geophysics, 81, V261–V270.
    [Google Scholar]
  5. Huang, W., Wang, R., Zhang, L., An, Y. and Zhou, Y.
    [2016b] Coherent Noise Attenuation Using Mathematical Morphological Filtering. In: 78th EAGE Conference and Exhibition 2016.
    [Google Scholar]
  6. Li, H., Wang, R., Cao, S., Chen, Y. and Huang, W.
    [2016] A method for low-frequency noise suppression based on mathematical morphology in microseismic monitoring. Geophysics, 81(3), V159–V167.
    [Google Scholar]
  7. Liu, Y.
    [2013] Noise reduction by vector median filtering. Geophysics, 78, V79–V87.
    [Google Scholar]
  8. Matheron, G.
    [1975] Random sets and integral geometry. John Wiley & Sons.
    [Google Scholar]
  9. Serra, J.
    [1982] Image analysis and mathematical morphology, v. 1. Academic press.
    [Google Scholar]
  10. Trickett, S.
    [2008] F-xy Cadzow noise suppression. Seg Technical Program Expanded Abstracts, 27(1), 2586.
    [Google Scholar]
  11. Wang, R.
    [2005] Noise-eliminated method by morphologic filtering in seismic data processing. Oil Geophysical Prospecting, 40(3), 277.
    [Google Scholar]
  12. Yuan, Y., Wang, R., Huang, W., Chen, X., Zhou, Y. and Jiang, Y.
    [2016] Self-adaptive Multi-scaled Morphology for Weak Signal Detection of Thin Interbedded Reservoir. In: 78th EAGE Conference and Exhibition 2016.
    [Google Scholar]
  13. Zhou, Y., Wang, R., Huang, W., Yuan, Y., Chen, X., Wang, L. and Yang, R.
    [2016] Attenuation of diffraction noise in marine surveys with mathematical morphology. In: SEG Technical Program Expanded Abstracts 2016, Society of Exploration Geophysicists, 4644–4648.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201700575
Loading
/content/papers/10.3997/2214-4609.201700575
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error