【摘 要】
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The article describes different methods of spectral decomposition on model seismic traces via machine learning approach.The main methods are considered: windowed Fourier transform,continuous wavelet t
【机 构】
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LLC Gazpromneft Science & Technology Centre,Saint-Petersburg,Russia
【出 处】
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2017年第五届数字油田国际学术会议(DOFIAC2017)
论文部分内容阅读
The article describes different methods of spectral decomposition on model seismic traces via machine learning approach.The main methods are considered: windowed Fourier transform,continuous wavelet transform and algorithms of spectral inversion.As a result of performed study it was shown that spectral inversion methods based on the solution of the problem of approximation of an input alignment a library of wavelets with the help of regularization,provide a much more accurate spectral representation of the signal.Several possible ways of geological interpretation are shown in article,including simple amplitude analysis(with RGB-mixing)and more complicated algorithm for estimation relative acoustic impedance and attenuation.
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