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Abstract

Summary

Micro-seismic signal is typically weak, compared with the strong background noise. The weak signal detection is necessary in micro-seismic data processing. Classic approaches such as the frequency filtering is limited, or even invalid when the signal and noise share the same frequency band. In order to effectively detect the weak signal in micro-seismic data, we propose a mathematical morphology based approach. We decompose the initial data into several morphological multi-scale components. For detection of weak signal, an orthogonalization operator is proposed and introduced into the process of reconstruction of data by morphological multi-scale components. The orthogonalization operator impels the reconstruction of weak signal. Application of the proposed method on a real micro-seismic data set demonstrates a successful performance.

© EAGE Publications BV
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/content/papers/10.3997/2214-4609.201700745
2017-06-12
2024-04-16

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References

  1. Chen, Y., Zhang, D., Jin, Z., Chen, X., Zu, S., Huang, W. and Gan, S.
    [2016] Simultaneous denoising and reconstruction of 5-D seismic data via damped rank-reduction method. Geophysical Journal International, 206(3), 1695–1717.
     [Google Scholar]
  2. 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]
  3. Huang, W., Wang, R., Yuan, Y., Gan, S. and Chen, Y.
    [2016b] Signal extraction using randomized-order multichannel singular spectrum analysis. Geophysics, 82(2), V59–V74.
     [Google Scholar]
  4. Li, H., Wang, R., Cao, S., Chen, Y. and Huang, W.
    [2016a] A method for low-frequency noise suppression based on mathematical morphology in microseismic monitoring. Geophysics, 81(3), V159–V167.
     [Google Scholar]
  5. Li, H., Wang, R., Cao, S., Chen, Y., Tian, N. and Chen, X.
    [2016b] Weak signal detection using multi-scale morphology in microseismic monitoring. Journal of Applied Geophysics, 133, 39–19.
     [Google Scholar]
  6. Matheron, G.
    [1975] Random sets and integral geometry. John Wiley & Sons.
     [Google Scholar]
  7. Maxwell, S., Rutledge, J., Jones, R. and Fehler, M.
    [2010] Petroleum reservoir characterization using downhole microseismic monitoring. Geophysics, 75(5), 75A129–75A137.
     [Google Scholar]
  8. Schimmel, M. and Paulssen, H.
    [1997] Noise reduction and detection of weak, coherent signals through phase-weighted stacks. Geophysical Journal International, 130(2), 497–505.
     [Google Scholar]
  9. Serra, J.
    [1982] Image analysis and mathematical morphology, v. 1. Academic press.
     [Google Scholar]
  10. Wang, R.
    [2005] Noise-eliminated method by morphologic filtering in seismic data processing. Oil Geophysical Prospecting, 40(3), 277.
     [Google Scholar]
  11. Wang, R., Li, Q. and Zhang, M.
    [2008] Application of multi-scaled morphology in denoising seismic data. Applied Geophysics, 5(3), 197–203.
     [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201700745
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Mathematical Morphological Decomposition for Weak Signal Detection in Micro-seismic Monitoring
Conference Proceedings 2017, 1 (2017); https://doi.org/10.3997/2214-4609.201700745
/content/papers/10.3997/2214-4609.201700745
/content/papers/10.3997/2214-4609.201700745
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