Data‐driven time–frequency analysis of seismic data using non‐stationary Prony method

ABSTRACT 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 foundati...

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Bibliographic Details
Published in:Geophysical Prospecting 2018-01, Vol.66 (1), p.85-97
Main Authors: Wu, Guoning, Fomel, Sergey, Chen, Yangkang
Format: Article
Language:English
Subjects:
Bandwidths
Data analysis
Decomposition
Empirical analysis
Frequency analysis
Functions (mathematics)
Hilbert transform
Hilbert transformation
intrinsic mode function
non‐stationary Prony method
Philosophy
Prony's method
Seismic analysis
Seismic data
Time-frequency analysis
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Summary:ABSTRACT 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.
ISSN:0016-8025
1365-2478
DOI:10.1111/1365-2478.12530