2014ProceedingsOpen access

Time-frequency Analysis of Noisy Seismogram Using Modified S-transform

Amit Gahlot

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Abstract

Summary In noisy seismogram, it is very difficult to determine the arrival time of various phases like, P and S. However, as the seismic signals are non-stationary in nature analysing seismogram in time-frequency representation can give the location of P,S-wave with high accuracy. For exact location, higher time and frequency resolution is required and hence, needs a method which can provide enhanced energy concentration in the time-frequency domain. In past few years, S-transform has become a popular tool for analysis of time-frequency distribution of seismic signals. The method provides multi-resolution analysis while retaining the absolute phase information of each frequency component of the signal, and hence is superior to others like Short Time Fourier Transform (STFT), Continuous Wavelet transform (CWT). The S-transform is considered conceptually a hybrid of STFT and CWT. Standard S-transform technique has frequency dependent window,so it has some limitations as frequency resolution will be poor at high frequency and degradable time resolution at low frequency. In this paper, we analyse the noisy seismogram in the time-frequency plane using modified S-transform technique in which window consists of additional parameters which controls the scale and shape of window in such a way as to provide improved energy concentration of spectrum.

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Summary In noisy seismogram, it is very difficult to determine the arrival time of various phases like, P and S. However, as the seismic signals are non-stationary in nature analysing seismogram in time-frequency representation can give the location of P,S-wave with high accuracy. For exact location, higher time and frequency resolution is required and hence, needs a method which can provide enhanced energy concentration in the time-frequency domain. In past few years, S-transform has become a popular tool for analysis of time-frequency distribution of seismic signals. The method provides multi-resolution analysis while retaining the absolute phase information of each frequency component of the signal, and hence is superior to others like Short Time Fourier Transform (STFT), Continuous Wavelet transform (CWT). The S-transform is considered conceptually a hybrid of STFT and CWT. Standard S-transform technique has frequency dependent window,so it has some limitations as frequency resolution will be poor at high frequency and degradable time resolution at low frequency. In this paper, we analyse the noisy seismogram in the time-frequency plane using modified S-transform technique in which window consists of additional parameters which controls the scale and shape of window in such a way as to provide improved energy concentration of spectrum.

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Available abstract

Summary In noisy seismogram, it is very difficult to determine the arrival time of various phases like, P and S. However, as the seismic signals are non-stationary in nature analysing seismogram in time-frequency representation can give the location of P,S-wave with high accuracy. For exact location, higher time and frequency resolution is required and hence, needs a method which can provide enhanced energy concentration in the time-frequency domain. In past few years, S-transform has become a popular tool for analysis of time-frequency distribution of seismic signals. The method provides multi-resolution analysis while retaining the absolute phase information of each frequency component of the signal, and hence is superior to others like Short Time Fourier Transform (STFT), Continuous Wavelet transform (CWT). The S-transform is considered conceptually a hybrid of STFT and CWT. Standard S-transform technique has frequency dependent window,so it has some limitations as frequency resolution will be poor at high frequency and degradable time resolution at low frequency. In this paper, we analyse the noisy seismogram in the time-frequency plane using modified S-transform technique in which window consists of additional parameters which controls the scale and shape of window in such a way as to provide improved energy concentration of spectrum.

Key concepts: Short-time Fourier transform, S transform, Time–frequency analysis, Continuous wavelet transform, Time–frequency representation, Constant Q transform, Seismogram, Energy (signal processing)

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