| Raise the level of seismic exploration is largely dependent on the level of seismicdata processing. Seismic data processing task is to field acquisition of seismicinformation, the processing of a variety of methods, to suppress the informationcollection fails to eliminate the residual surface waves, multiple waves and randominterference and improve signal to noise ratio and to improve the resolution, providereliable information for the geological interpretation of seismic exploration. Therefore,the seismic data processing is an important part of the implementation process in theseismic exploration. To improve the signal to noise ratio of seismic data, you need toeliminate the seismic data in the random noise and coherent noise. This thesis work ismainly centered on how to eliminate the noise study.This article focuses on the wavelet transform modulus maxima denoising methodand wavelet threshold denoising method as the basic theory of programming for thesetwo algorithms, and at the same time the corresponding numerical simulation. Thesimulated results corresponding to the comparison and analysis, and pointed out theadvantages and disadvantages of these two methods, and this among a number ofproblems. Detailed study of the theme and content, including the following aspects:1.According to the characteristics of the seismic data signal itself and the formation ofseismic signals, the above two methods, a brief introduction and analysis of theadvantages and disadvantages of these two methods.2. Analysis and seismic signalwavelet transform modulus maxima to remove noise signal to noise separationmethod, and finally the wavelet transform modulus maximum signal to noiseseparation method for the study, analyze the strengths and weaknesses of the method.3. The analysis and discussion of the wavelet threshold denoising method, wavelet threshold denoising method of signal to noise separation method for the study,analyzed the strengths and weaknesses of the method. |
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