Frequency Domain Seismic Blind Deconvolution Based on ICA

Gao Wei, Huaishan Liu
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引用次数: 2

Abstract

Independent components ansalysis (ICA) is combined with shot time Fourier transform(STFT) to improve the traditional frequency domain seismic deconvolution in this paper. Neglecting noise, the seismic record is changed from time domain to frequency domain with STFT in order to transform the common seismic model to the basic ICA model. By applying FastICA algorithm, reflectivity series and the seismic wavelet can be produced in frequency domain and changed back to the time domain subsequently. The model and real seismic data numerical examples all show the algorithm valid. The advantage of this new method is to inverse blindly the wavelet and the reflectivity effectively with no assumption of Guassality and whiten noise to reflectivity, and no assumption of minimum phase to seismic wavelet. The algorithm refered here propose a new way of seismic deconvolution and worth doing more researches.
基于ICA的频域地震盲反褶积
将独立分量分析(ICA)与瞬时傅里叶变换(STFT)相结合,改进了传统的频域地震反褶积方法。在忽略噪声的情况下,利用STFT将地震记录从时域变换到频域,将常用地震模型转化为ICA基本模型。利用FastICA算法,可以在频域产生反射率序列和地震小波,并将其变换回时域。模型和实际地震资料的数值算例均表明了算法的有效性。该方法的优点是可以有效地进行小波和反射率的盲目反演,不需要对反射率进行质量假设和白噪声,也不需要对地震小波进行最小相位假设。该算法提出了一种新的地震反褶积方法,值得进一步研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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