Detection of thin layers with CWT method in one of the southern oil fields of Iran

the continuous wavelet transform (CWT) is one of the spectral decomposition methods to analyze a non-stationary signal in order to obtain an optimal time and frequency resolution of signals . Among spectral decomposition methods the first method is the short time fourier transform (STFT) , in this way , time - frequency resolution is limeted by predefining a window length. in contrast the continuous wavelet transform does not require preselecting a window length and does not have a fixed time frequency resolution over the time frequency space CWT used dilation and translation of the wavelet to produce a time scale map.then the time scale map of CWT is converted to a time -frequency CWT (TFCWT) map to obtain high time resolution at high frequencies and high frequency resolution at low frequencies . this property of the wavelet transform is used for detecting thin layers. in this paper at first a synthetic wedge model is considered , then attributes are extracted from spectra of CWT and TFCWT. then they are compared with each other it is shown that attributes given by the TFCWT have better resolution in comparison to CWT spectrum then exercise the same procedure on real data.

کلیدواژه ها:

spectral decomposition ، continuous wavelet transform ، thin bed ، seismic attributes and time frequency analysis