Applied Geophysics

, Volume 14, Issue 4, pp 581–589 | Cite as

Near-source noise suppression of AMT by compressive sensing and mathematical morphology filtering

  • Guang Li
  • Xiao Xiao
  • Jing-Tian Tang
  • Jin Li
  • Hui-Jie Zhu
  • Cong Zhou
  • Fa-Bao Yan
Article

Abstract

In deep mineral exploration, the acquisition of audio magnetotelluric (AMT) data is severely affected by ambient noise near the observation sites; This near-field noise restricts investigation depths. Mathematical morphological filtering (MMF) proved effective in suppressing large-scale strong and variably shaped noise, typically low-frequency noise, but can not deal with pulse noise of AMT data. We combine compressive sensing and MMF. First, we use MMF to suppress the large-scale strong ambient noise; second, we use the improved orthogonal match pursuit (IOMP) algorithm to remove the residual pulse noise. To remove the noise and protect the useful AMT signal, a redundant dictionary that matches with spikes and is insensitive to the useful signal is designed. Synthetic and field data from the Luzong field suggest that the proposed method suppresses the near-source noise and preserves the signal well; thus, better results are obtained that improve the output of either MMF or IOMP.

Keywords

Compressive sensing filtering magnetotellurics signal processing noise 

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Copyright information

© Editorial Office of Applied Geophysics and Springer-Verlag GmbH Germany, part of Springer Nature 2017

Authors and Affiliations

  • Guang Li
    • 1
  • Xiao Xiao
    • 1
  • Jing-Tian Tang
    • 1
  • Jin Li
    • 1
    • 2
  • Hui-Jie Zhu
    • 3
  • Cong Zhou
    • 1
  • Fa-Bao Yan
    • 4
  1. 1.Institute of Geosciences and Info-PhysicsCentral South UniversityChangshaChina
  2. 2.Institute of Physics and Information ScienceHunan Normal UniversityChangshaChina
  3. 3.The First Engineering Scientific Research Institute of General Armaments DepartmentWuxiChina
  4. 4.Institute of Space ScienceShandong UniversityWeihaiChina

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