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The Hilbert–Huang Transform-Based Denoising Method for the TEM Response of a PRBS Source Signal

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Abstract

The denoising process is critical in processing transient electromagnetic (TEM) sounding data. For the full waveform pseudo-random binary sequences (PRBS) response, an inadequate noise estimation may result in an erroneous interpretation. We consider the Hilbert–Huang transform (HHT) and its application to suppress the noise in the PRBS response. The focus is on the thresholding scheme to suppress the noise and the analysis of the signal based on its Hilbert time–frequency representation. The method first decomposes the signal into the intrinsic mode function, and then, inspired by the thresholding scheme in wavelet analysis; an adaptive and interval thresholding is conducted to set to zero all the components in intrinsic mode function which are lower than a threshold related to the noise level. The algorithm is based on the characteristic of the PRBS response. The HHT-based denoising scheme is tested on the synthetic and field data with the different noise levels. The result shows that the proposed method has a good capability in denoising and detail preservation.

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Acknowledgments

This research was supported by R&D of Key Instruments and Technologies for Deep Resources Prospecting (the National R&D Projects for Key Scientific Instruments), Grant No. ZDYZ2012-1-05- 04. The EMD code was developed by Wu, Z., and N. E Huang, and we are grateful to them for sharing their code. We are also grateful to constructive feedback by two anonymous reviewers.

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Authors and Affiliations

  1. Key Laboratory of Mineral Resources, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing, China

    Li Hai, Xue Guo-qiang, Zhao Pan, Zhong Hua-sen & Muhammad Younis Khan

  2. University of Chinese Academy of Sciences, Beijing, China

    Li Hai, Zhao Pan & Zhong Hua-sen

  3. National Centre of Excellence in Geology, University of Peshawar, Peshawar, Pakistan

    Muhammad Younis Khan

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  1. Li Hai
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  2. Xue Guo-qiang
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  3. Zhao Pan
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  4. Zhong Hua-sen
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  5. Muhammad Younis Khan
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Correspondence to Li Hai.

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Hai, L., Guo-qiang, X., Pan, Z. et al. The Hilbert–Huang Transform-Based Denoising Method for the TEM Response of a PRBS Source Signal. Pure Appl. Geophys. 173, 2777–2789 (2016). https://doi.org/10.1007/s00024-016-1308-x

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