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Data‐driven time–frequency analysis of seismic data using non‐stationary Prony method
Author(s) -
Wu Guoning,
Fomel Sergey,
Chen Yangkang
Publication year - 2018
Publication title -
geophysical prospecting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.735
H-Index - 79
eISSN - 1365-2478
pISSN - 0016-8025
DOI - 10.1111/1365-2478.12530
Subject(s) - hilbert–huang transform , mode (computer interface) , analytic signal , computer science , signal (programming language) , hilbert transform , algorithm , instantaneous phase , field (mathematics) , signal processing , amplitude , time–frequency analysis , mathematics , spectral density , physics , white noise , optics , telecommunications , radar , pure mathematics , programming language , operating system
Empirical mode decomposition aims to decompose the input signal into a small number of components named intrinsic mode functions with slowly varying amplitudes and frequencies. In spite of its simplicity and usefulness, however, empirical mode decomposition lacks solid mathematical foundation. In this paper, we describe a method to extract the intrinsic mode functions of the input signal using non‐stationary Prony method. The proposed method captures the philosophy of the empirical mode decomposition but uses a different method to compute the intrinsic mode functions. Having the intrinsic mode functions obtained, we then compute the spectrum of the input signal using Hilbert transform. Synthetic and field data validate that the proposed method can correctly compute the spectrum of the input signal and could be used in seismic data analysis to facilitate interpretation.