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

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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.

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Authors and Affiliations

  1. Institute of Geosciences and Info-Physics, Central South University, Changsha, 410083, China

    Guang Li, Xiao Xiao, Jing-Tian Tang, Jin Li & Cong Zhou

  2. Institute of Physics and Information Science, Hunan Normal University, Changsha, 410081, China

    Jin Li

  3. The First Engineering Scientific Research Institute of General Armaments Department, Wuxi, 214035, China

    Hui-Jie Zhu

  4. Institute of Space Science, Shandong University, Weihai, 264209, China

    Fa-Bao Yan

Authors
  1. Guang Li
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  2. Xiao Xiao
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  3. Jing-Tian Tang
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  4. Jin Li
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  5. Hui-Jie Zhu
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  6. Cong Zhou
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  7. Fa-Bao Yan
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Corresponding author

Correspondence to Xiao Xiao.

Additional information

This work is financially supported by the National High Technology Research and Development Program of China (No. 2014AA06A602), National Natural Science Foundation of China (No. 41404111), and Natural Science Foundation of Hunan Province (No. 2015JJ3088).

Li Guang received his bachelor’s and master’s degree from Hunan University of Science and Technology in 2011 and 2014, respectively. Presently, he is pursuing Ph.D. from Central South University. His main research interests are signal processing of electromagnetic methods and intelligent instruments. Email: li_guangg@163.com.

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Li, G., Xiao, X., Tang, JT. et al. Near-source noise suppression of AMT by compressive sensing and mathematical morphology filtering. Appl. Geophys. 14, 581–589 (2017). https://doi.org/10.1007/s11770-017-0645-6

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  • DOI: https://doi.org/10.1007/s11770-017-0645-6

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