Research on NMR Denoising Method Based on Empirical Mode Decomposition

doi:10.11885/j.issn.1674-5086.2019.09.16.32

Abstract

Abstract: NMR has unique advantages in pore structure evaluation and fluid identification, but NMR signals are easy to be influenced by noise. This paper presents a kind of denoising method according to time and frequency domain characteristics of NMR noise based on EMD. Firstly we decompose noise and noisy NMR signals using EMD. Then we determine guidelines of signal-noise separation using curve trend method and improved zero-crossing rate curve. Finally we add useful signals to residual term to obtain pure signals. It is confirmed by core data and logging data experiments that the denosing results are better than wavelet threshold and EMD-wavelet threshold method and porosity calculated is closer to real porosity and the inversion results are consistent with actual pore structure. The denosing method based on EMD can improve signal to noise ratio and reserve pore structure information.

Key words: empirical mode decomposition (EMD), characteristics of NMR noise, curve trend method, improved zero-crossing rate curve, separation criteria

CLC Number:

TE121
P631

LI Haitao, DENG Shaogui, WANG Yuexiang, HE Xuquan. Research on NMR Denoising Method Based on Empirical Mode Decomposition[J]. 西南石油大学学报(自然科学版), 2020, 42(3): 51-59.

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URL: http://journal15.magtechjournal.com/Jwk_xnzk/EN/10.11885/j.issn.1674-5086.2019.09.16.32

http://journal15.magtechjournal.com/Jwk_xnzk/EN/Y2020/V42/I3/51

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