### Published as Geophysical Prospecting, 66, 85-97 (2018)

# Data-driven time-frequency analysis of seismic data using
non-stationary Prony method

**Guoning Wu**^{}, Sergey Fomel^{}, Yangkang Chen^{}

^{}The College of Science

China University of Petroleum

Beijing, China
^{}Bureau of Economic Geology,

John A. and Katherine G. Jackson School of Geosciences

The University of Texas at Austin

University Station, Box X

Austin, TX, USA, 78731-8924

^{}Previously: The University of Texas at Austin; Currently: Oak Ridge National Laboratory

### Abstract:

The 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, the empirical mode decomposition lack
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 use 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 the proposed method can correctly compute the
spectrum of the input signal, and could be used in seismic data analysis to facilitate
interpretation.

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2020-07-18