Saman Gholtashi; Mohammad Amir Nazari Siahsar; Amin RoshandelKahoo; Hosein Marvi; Alireza Ahmadifard
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 ...
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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.
Amin Roshandel Kahoo; Saman Gholtashi
Abstract
The improvement in the temporal resolution of seismic data is a critical issue in hydrocarbon exploration. It is important for obtaining more detailed structural and stratigraphic information. Many methods have been introduced to improve the vertical resolution of reflection seismic data. Each method ...
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The improvement in the temporal resolution of seismic data is a critical issue in hydrocarbon exploration. It is important for obtaining more detailed structural and stratigraphic information. Many methods have been introduced to improve the vertical resolution of reflection seismic data. Each method has advantages and disadvantages which are due to the assumptions and theories governing their issues. In this paper, we improve the temporal resolution of reflection seismic data using the logarithmic time-frequency transform method. This method has minimum user-defined parameters. The algorithm uses valuable properties of both the time-frequency transform and the cepstrum to extend the frequency band at each translation of the spectral decomposing window. In this method, the displacement of amplitude spectrum by its logarithm is the basic idea of the algorithm. We tested the mentioned algorithm on both synthetic and real data. The results of the both tests show that the introduced method can increase the temporal resolution of seismic data.