The Study Of Blind Signal Technique In The Application Of Seismic Data Processing

Seismic data noise removal and multiple attenuation are the important part of seismic data process. The noise generated by the working machines and the power interference around the detectors collecting the seismic signal in some special fields such as factories usually contaminated the seismic data. The conventional methods proved inadequate in removing the machine noise with special characteristic from the seismic signal. Some new method should be studied to remove it. In addition, the method based on wave-equation has been the important technique on multiple attenuation. The adaptive multiple subtraction algorithm plays an important role in wave-equation method. Moreover Blind Signal Processing as the most popular subject has reliable theory and abroad application potential. Adaptive noise cancellation technique and Independent Component Analysis (ICA) which are the main methods of Blind Signal Processing, have been widely applied in some fields such as voice processing, biomedicine. This paper investigates the application of Blind Signal Processing in machine noise removal and multiple attenuation. The main contents are shown as follows:(1)Summarized the conventional noise removal methods and analyzed the characteristic of the signal and machine noise in the round.(2)Studied the theory of Blind Signal processing; Masterd the fundamentals;Studied some algorithms and newly deduced the formulas;Achieved the program based on Blind Signal Processing for reducing the machine noise.(3)Investigated and summarized the conventional adaptive multiple subtraction methods; Research showed that the primary vector is not vertical with the multiple vector make conventional methods can not get better result.(4)Studied the adaptive multiple subtraction method based on the Independent Component Analysis; Achieved the program of this method and processed the data; Compared the results with conventional methods'outcome.The main innovative points and achievements:(1) Presented the adaptive noise cancellation technique to reduce the machine noise; Developed a new algorithm aiming at the shortcoming of the conventional technique. (2) Primarily presented two ICA methods operated separately in frequency domain and in time domain for reducing seismic data noise; Solved the illegibility problem in amplitude and order of the frequency domain method; The results of tests and real data processing showed the effectiveness and the superiority.(3)Presented a optimized project for adaptive multiple subtraction; Used pseudomultichannel matching filter to revise the wavelet difference between the predicted multiple and the real multiple in the record before using the ICA adaptive multiple subtraction method which can get better result when primary and multiple vector have overlap; Theory and data processing proved that this method can eliminate the multiples effectively without hurting the primary.