2014毕业设计论文范本2.doc

摘 要 提高地震信号的分辨率是地震勘探所要解决的一项主要任务，而提高地震信号的信噪比是提高地震信号分辨率的先决条件。要提高地震资料的信噪比，需要去除地震资料中的随机噪声和相干噪声。相干噪声一般在时间上的出现具有规律性，有明显的运动学特征，可以有针对性地加以衰减。随机噪声没有统一的规律，在整张记录上随机出现，比较难以去除。因此如何有效消除随机噪声是人们一直追求的目标。 小波分析在时域频域同时具有良好的局部化性质和多分辨率分析的特点，与传统的去噪方法相比较，有着无可比拟的优点，成为信号分析的一个强有力的工具。小波变换能将信号在多个尺度上进行小波分解，信号和随机噪声在不同的尺度上进行小波分解时，存在一些不同的特征表现：地震信号中的有效反射波的小波变换模极大值随着尺度的增大而增大；噪声在小波变换下具有的特性同信号相比则完全相反,随着尺度的增大而减小。其截然不同的表现特征为我们选择和确定一个用于取舍信号和噪声模极大值的阈值提供了条件。本文主要是使用离散二进小波变换，采用小波域阈值的去噪方法对地震信号中随机噪声进行分析和处理. 论文主要介绍了小波变换和地震信号去噪的基本理论，分析了小波变换的特点，介绍了小波变换的去噪方法，及常见的小波集函数。最后将小波域阈值去噪方法与计算机技术相结合，利用软件对地震信号进行去噪。 关键词：地震信号；小波分析；小波域阈值去噪 ABSTRACT To improve the resolution of seismic data is a main task of geophysical exploration，and its prerequisite condition is to improve the signal-to-noise ratio．It is necessary to remove coherent noises and random noises in seismic data processing to improve the signal-to-noise ratio．Commonly there are some rules of coherent noises，so they can be removed according to their rules Random noises have no rules，so it is difficult to remove random noises．Therefore how to effectively get rid of random noises is a goal which many people want to reach． Wavelet transform has the characteristic of good local nature and analysis of multi-ratio in both time domain and frequency domain. Comparing with the conventional method, the new de-noising method has the incomparable strongpoint and becomes the powerful implement for analysis of data. The wavelet transform can resolve the data in different measure. It appears different features during the process of resolving on data and random noises, such as in seismic data the maximum of wavelet transform pattern of efficient reflection wave increases as the measure increasing; comparing with data, the noise has the completely opposite characteristic which decreases as the measure increasing. The entirely different feature provides the prerequisite condition for choosing a threshold filter applying to choosing data and owning the maximum of noise pattern. Thi