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小波多分辨率分析在地震资料处理中的应用.doc

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西安石油大学本科毕业设计(论文) - PAGE 76 - 小波多分辨率分析在地震资料处理中的应用 摘 要: 小波分析是近年来发展起来的新的数学理论和方法,在噪声消除方面有着广泛的应用。小波分析能同时在时频域内对信号进行分析,所以它能有效区分信号中的突变部分和噪声,从而实现对非平稳信号的消噪。小波多分辨率分析是利用小波变换对信号进行多尺度分解分析。利用小波多分辨率分析方法对地震记录进行去噪,可以有效地对噪声和信号进行分离,从而使地质信息丰富清晰,便于解释。利用此方法去噪的过程,可分为如下三个步骤:对记录进行小波多尺度分解,选择一个小波并确定分解的层次,然后进行分解计算;小波分解高频系数的阈值量化,对各个分解尺度下的高频系数选择一个阈值进行阈值量化处理;小波重构,根据小波分解的低频系数和各层高频系数进行小波重构。这三个步骤中,最关键的是如何选择阈值以及进行阈值量化。在某种程度上,它关系到信号消噪的质量。 关键词: 小波变换;多分辨率分析;去噪;阈值;地质信息提取 The wavelet multi-resolution analysis used in the processing of seimic data Abstract: The wavelet analysis is a newly mathematic theory and method that has developed recently. And specially ,it is widely used in de-noising. The wavelet analysis can simultaneously analyze signals in both time-domain and frequency-domain, so it can distinguish sudden changes of the signals from noises efficiently and be used to remove noises from nonstationary signals. The wavelet multi-resolution analysis uses the wavelet analysis to multi-scale decomposition for signals. It can be used to de-noise seismograms and can separate noises from signals efficiently,therefore the geological information can be made more plentiful and cleaning.The profile can be easily interpretated. There three steps to use this method to de-noise. First, do multi-scale decomposition for the signal. Select a wavelet and determine the scale of the decomposition, then decompose. Second, fix a threshold for high frequency coefficients under each scale and de-noise. Third, do wavelet reconstruction,according to the low frequency coefficients and the de-noised high frequency coefficients. The most important things in the three steps are the selection of thresholds and de-noising using the thresholds.To some degree, it has an effect on the quality of the result of de-noising. Key words: Wavelet transform; Multi-resolution analysis;De-noising; Threshold;The extract of geological information 目 录 1 绪论…………………………………………………………………………………….1 1.1 课题背景及意义…………………………………………………………………1
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