The Application Of The Second-Generation Wavelet Transform In Denoising Of The Seismic Data

Seismic Data Processing plays an important role in seismic signal analysis, the merits of the algorithm will directly affect the accuracy of geological analysis, the denoising technology of random noise in seismic signal has made significant progress, however, it still can not meet the requirements of denoising effect of geological materials, Particularly in the analysis of complex geological structures,such as the thin layer ,people need more clear and accurate geological materials,Therefore, improving the existing denoising techniques ,seeking for more precise, effective, fast and convenient denoising algorithm, is a very meaningful subject which needs for further study. Second generation wavelet transform is a new technique of wavelet analysis,it not only inherits the advantages of wavelet analysis, but also the algorithm realizing fast, the wavelet constructing flexiblely, and other advantages make it gradually replace the wavelet transform, and is applied to all areas of wavelet analysis. Second generation wavelet transform has been unanimously endorsed by the image compression field, it has also been gradually applied to the detection and recognition of the mechanical failure,image and signal denoising fields,but it has seldom applied to seismic signal denoising. Considering the second-generation wavelet denoising has a variety of advantages, it will also have great potential in seismic signal denoising areas.but it will be affected by many factors in the actual process of denoising.this paper carried out some of the work in the following aspects:1.Denoising method based on wavelet analysis has many kinds,comparing the advantages and disadvantages of several methods and application ranges,this paper aims to make a detailed analysis of determining the threshold value in threshold denoising method, According to the different characteristics shown by the useful information of the seismic signal and random noise through the wavelet decomposition, it improves the threshold method, revises the threshold value appropriately according to the different decomposition level, so that when making threshold processing to the signal thorough the algorithm, each decomposition level has a different threshold ,which can meet the characteristics of wavelet coefficients transform.2.The paper overcomes the shortcomings of classic threshold function with the improved threshold function to make the denoising results better, and the details of information retent more integrated.3.The paper combines the traditional algorithm with the white noise test method to solve the problem that the wavelet decomposition level is difficult to determine., it determines the major components of the wavelet coefficients and the best decomposition level according to the white noise test results of the wavelet coefficients,so that the second-generation wavelet denoising could achieve best results.4.Through the three aspects above,this paper improves the traditional wavelet denoising algorithm and the effect of second generation wavelet denoising, it also demonstrates the effectiveness and superiority of the algorithm thorough experimental results, at the same time applies it to the real seismic signal denoising.