Author/Authors :
Nazari Siahsar، Mohammad Amir نويسنده Department of Electrical & Robotic Engineering, University of Shahrood, Shahrood, Iran Nazari Siahsar, Mohammad Amir , roshandel kahoo، amin نويسنده , , Marvi، Hosein نويسنده Department of Electrical & Robotic Engineering, University of Shahrood, Shahrood, Iran Marvi, Hosein , Ahmadifard، Alireza نويسنده , , Gholtashi، Saman نويسنده Department of Mining, Petroleum & Geophysics Engineering, University of Shahrood, Shahrood, Iran Gholtashi, Saman
Abstract :
Seismic waves are non-stationary due to its propagation through the earth. Time-frequency transforms
are suitable tools for analyzing non-stationary seismic signals. Spectral decomposition can reveal the
non-stationary characteristics which cannot be easily observed in the time or frequency representation
alone. Various types of spectral decomposition methods have been introduced by some researchers.
Conventional spectral decompositions have some restrictions such as Heisenberg uncertainty principle
and cross-terms which limit their applications in signal analysis. In this paper, synchrosqueezingbased
transforms were used to overcome the mentioned restrictions; also, as an application of this new
high resolution time-frequency analysis method, it was applied to random noise removal and the
detection of low-frequency shadows in seismic data. The efficiency of this method is evaluated by
applying it to both synthetic and real seismic data. The results show that the mentioned transform is a
proper tool for seismic data processing and interpretation.
