Open AccessA Reservoir Information Extraction Method Based on Improved Hilbert-Huang Transform
Author(s) -
Qingmi Yang
Publication year - 2019
Publication title -
international journal of scientific research in science, engineering and technology
Language(s) - English
Resource type - Journals
eISSN - 2395-1990
pISSN - 2394-4099
DOI - 10.32628/ijsrset196510
Subject(s) - hilbert–huang transform , hilbert transform , aliasing , instantaneous phase , modal , signal processing , hilbert spectral analysis , computer science , algorithm , nonlinear system , signal (programming language) , mode (computer interface) , pattern recognition (psychology) , speech recognition , artificial intelligence , digital signal processing , computer vision , filter (signal processing) , chemistry , physics , quantum mechanics , undersampling , polymer chemistry , computer hardware , programming language , operating system
Hilbert-Huang transform (HHT) is a nonlinear non-stationary signal processing technique, which is more effective than traditional time-frequency analysis methods in complex seismic signal processing. However, this method has problems such as modal aliasing and end effect. The problem causes the accuracy of signal processing to drop. Therefore, this paper introduces the method of combining the Ensemble Empirical Mode Decomposition (EEMD) and the Normalized Hilbert transform (NHT) to extract the instantaneous properties. The specific process is as follows: First, the EEMD method is used to decompose the seismic signal to a series of Intrinsic Mode Functions (IMF), and then The IMFs is screened by using the relevant properties, and finally the NHT is performed on the IMF to obtain the instantaneous properties.