Study On Independent Component Analysis-Based Seismic Blind Deconvolution Method

Seismic exploration plays an important role in searching for oil and gas fields, as foremost exploration means. Deconvolution is one of key techniques in seismic data processing, to improve the vertical resolution of seismic data. Seismic blind deconvolution based on blind signal separation can weaken or even eliminate reliance on assumptions, to solve seismic wavelet and reflectivity sequence, further improve the resolution of seismic data. Independent component analysis (ICA) is introduced into seismic data processing. The main works are as follows:Seismic exploration and deconvolution are introduced. According to the principle and algorithm of blind deconvolution methods, we classify them. Least square deconvolution is simulated, which is the basis of conventional deconvolution. There are several assumptions in conventional deconvolution. When those assumptions are not in accordance with the fact, the result of deconvolution is poor.A brief introduction to blind signal separation points out that ICA is an effective method to achieve blind signal separation. The independent component analysis as an effective method for blind source separation is a hotspot in signal processing. The definition and basic principles of ICA are introduced from the mathematical basis, basic model and principles.Using basic model and principles of complex ICA, FastICA algorithm based on kurtosis is simulated. Combining the complex ICA algorithm and seismology convolution model, we propose a complex FastICA -based seismic blind deconvolution which is better suitable for non-assumptions system and could obtain the optimum evaluation of raw reflection coefficient and be characteristic of fast convergence and high precision in the results of numeric simulation. Blind deconvolution solves seismic wavelet and the vertical reflectivity sequence, lacking assumptions. Finally, the application of ICA in the field of eliminating seismic data noise is discussed, which exists in seismic record. Aimed to improve SNR, complex ICA algorithm is introduced into eliminating seismic data noise. Simulation result shows that the method can eliminate noise from seismic data.