Open AccessFeature Extraction of Down-hole Drilling-plug Impact Signal Based on Empirical Mode Decomposition
Author(s) -
Fei Xu,
Quanzhi Yang,
Bin Wu,
Xiaobin Zhang,
Xiaolong Yu,
Shoubo Wan
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1894/1/012068
Subject(s) - drilling , hilbert–huang transform , spark plug , signal (programming language) , measurement while drilling , deep hole drilling , computer science , engineering , filter (signal processing) , mechanical engineering , computer vision , programming language
For analyzing the non-stationary drilling-plug impact signal under the complicated drilling environment, use of conventional discrete Fourier Transform (DFT) has been known to be less efficient. To extract useful information contained in the drilling-plug impact signal, a new extraction method based on empirical mode decomposition (EMD) is presented. In the signal processing, EMD is used to decompose the original drilling-plug impact signal into the intrinsic mode functions (IMFs). By analyzing kurtosis and energy spectrum of the IMFs, the first three IMFs are found that contain the characteristic of the drilling-plug, and the specific frequency band of the drilling-plug impact signal is determined after power spectrum analyzing. The reconstruction drilling-plug impact signal after band-pass filter can clearly show the detailed process of the drilling-plug such as drilling the rubber plug, drilling the float collars and drilling the formation.