地震勘探论文

【英文摘要】Seismic exploration is a significant way to get information inside the earth, and it is also the basic way to find minerals and other resources. Today, seismic exploration technique is developing in the direction of multidimensional, multicomponent, multiparameter and high resolution, so that the seismic exploration data is increasing day by day. It becomes a serious problem to transform and store the data. Therefore, how to compress the data becomes the key to solve the problem.According to the analysis the character of seismic data, the data has redundancy information. The paper is based on wavelet transform, and studied the theory that how different wavelet bases convert to lifting scheme, so they can be used to transform seismic data. There are three classical compression method based on wavelet transform:EZW, SPIHT and EBCOT algorithm. The article studied each theory and the advantages and disadvantages, so the article chose SPIHT as the coding algorithm for seismic data. As for the original seismic data and the constructed data, the article designed five different evaluation criterions to analyze the constructed data. The experimental result shows:(1). The effect of the constructed data is different on the basis of different lifting wavelet transform. The db4 wavelet base and bior6.8 wavelet base have the best effect among all the chose wavelet bases.(2). According to the experimental result in the paper, transform the seismic data at the level of 5, and the compression rate is less than 10, the result of compression is best. Transform the seismic data at the level of 5, and the compression rate is between 10 and 20, the constructed result is the best.(3). With the SPIHT algorithm, the compression rate can be controlled precisely. When the compression rate is less than 5, the effect of the constructed data approximately equal to lossless compression, and when the compression rate increases, the quality of constructed data is reduced.In this article, the loss compression algorithm brings very good results, and the algorithm can be used to analyze different seismic data. Wavelet bases can be constructed according to different seismic data, and the SPIHT algorithm can be improved or using EBCOT algorithm to analyze seismic data.
地震勘探论文：基于提升小波变换的地震勘探数பைடு நூலகம்有损压缩研究
【中文摘要】地震勘探是获取地球内部信息的重要手段,是寻找地下矿产和其他资源的基本方法之一。当前,地震勘探技术正向多维、多分量、多参数、高分辨率方向发展,使得地震勘探数据量不断增加。如何对这些数据进行有效传送和存取是一个重大难题。因此,对地震勘探数据进行有效压缩是解决这个问题的关键。通过对地震勘探数据的特征分析可知,地震勘探信号存在冗余。本文以小波变换为基础,研究了不同小波转化为提升方案的原理,并且对选择出的bior系列和daubechies系列不同的小波基分别给出了其提升方案,用于地震勘探数据提升小波正逆变换。对基于小波变换的三种典型的有损压缩方法-EZW、SPIHT、EBCOT方法,研究了其各自的原理和优缺点,从而选择出SPIHT算法作为地震勘探数据的编码方法。对于地震勘探原始数据和重构数据,设计并使用5种不同的评价标准对重构数据进行分析。实验结果表明：(1).使用不同提升小波对地震勘探数据进行变换,得到重构数据的效果不同,其中db4小波和bior6.8提升小波变换的效果最好。(2).针对本文使用的实验数据,使用db4提升小波对地震勘探数据变换5次,且压缩倍率小于10时,压缩效果最好；使用bior6.8提升小波对地震勘探数据变换5次,且压缩倍率为10-20时,可取得很好的重构效果。(3).SPIHT算法可以精确控制压缩比,当压缩比小于5时,重构数据的效果近似于无损压缩；而当压缩比增大时,重构数据的质量降低。本文使用的有损压缩方法对地震勘探数据取得了较好的效果,也可以对不同的地震勘探数据体压缩效果进行分析。针对不同的数据可以构造自己的小波基,也可以对SPIHT算法可以进行改进,或者使用EBCOT算法对数据进行分析。