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An improved lossless group compression algorithm for seismic data in SEG-Y and MiniSEED file formats

机译:改进的SEG-Y和MiniSEED文件格式的地震数据无损分组压缩算法

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摘要

An improved lossless group compression algorithm is proposed for decreasing the size of SEG-Y files to relieve the enormous burden associated with the transmission and storage of large amounts of seismic exploration data. Because each data point is represented by 4 bytes in SEG-Y files, the file is broken down into 4 subgroups, and the Gini coefficient is employed to analyze the distribution of the overall data and each of the 4 data subgroups within the range [0,255]. The results show that each subgroup comprises characteristic frequency distributions suited to distinct compression algorithms. Therefore, the data of each subgroup was compressed using its best suited algorithm. After comparing the compression ratios obtained for each data subgroup using different algorithms, the Lempel-Ziv-Markov chain algorithm (LZMA) was selected for the compression of the first two subgroups and the Deflate algorithm for the latter two subgroups. The compression ratios and decompression times obtained with the improved algorithm were compared with those obtained with commonly employed compression algorithms for SEG-Y files with different sizes. The experimental results show that the improved algorithm provides a compression ratio of 75-80%, which is more effective than compression algorithms presently applied to SEG-Y files. In addition, the proposed algorithm is applied to the miniSEED format used in natural earthquake monitoring, and the results compared with those obtained using the Steim2 compression algorithm, the results again show that the proposed algorithm provides better data compression.
机译:提出了一种改进的无损群压缩算法,以减小SEG-Y文件的大小,以减轻与大量地震勘探数据的传输和存储相关的巨大负担。由于SEG-Y文件中的每个数据点均由4个字节表示,因此该文件被细分为4个子组,并且使用基尼系数来分析整体数据的分布以及[0,255]范围内的4个数据子组中的每一个]。结果表明,每个子组都包含适合不同压缩算法的特征频率分布。因此,使用其最适合的算法压缩每个子组的数据。在比较使用不同算法为每个数据子组获得的压缩率之后,选择Lempel-Ziv-Markov链算法(LZMA)压缩前两个子组,然后选择Deflate算法压缩后两个子组。将改进算法获得的压缩率和解压缩时间与不同大小的SEG-Y文件的常用压缩算法进行了比较。实验结果表明,改进的算法提供了75-80%的压缩率,比目前应用于SEG-Y文件的压缩算法更有效。另外,将该算法应用于自然地震监测中使用的miniSEED格式,并将结果与​​使用Steim2压缩算法获得的结果进行比较,结果再次表明,该算法提供了更好的数据压缩。

著录项

  • 来源
    《Computers & geosciences》 |2017年第3期|41-45|共5页
  • 作者单位

    Southwest Univ Sci & Technol, Fundamental Sci Nucl Wastes & Environm Safety Lab, Mianyang 621010, Peoples R China;

    Southwest Univ Sci & Technol, Fundamental Sci Nucl Wastes & Environm Safety Lab, Mianyang 621010, Peoples R China|Sichuan Univ Sci & Engn, Zigong 643000, Peoples R China|Chengdu Univ Technol, State Key Lab Geohazard Prevent & Geoenvironm Pro, Chengdu 610059, Peoples R China;

    Sichuan Univ Sci & Engn, Zigong 643000, Peoples R China|Chengdu Univ Technol, State Key Lab Geohazard Prevent & Geoenvironm Pro, Chengdu 610059, Peoples R China;

    Southwest Univ Sci & Technol, Fundamental Sci Nucl Wastes & Environm Safety Lab, Mianyang 621010, Peoples R China;

    Southwest Univ Sci & Technol, Fundamental Sci Nucl Wastes & Environm Safety Lab, Mianyang 621010, Peoples R China;

    Southwest Univ Sci & Technol, Fundamental Sci Nucl Wastes & Environm Safety Lab, Mianyang 621010, Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Lossless compression; Group compression; Seismic data; SEG-Y; MiniSEED;

    机译:无损压缩群压缩地震数据SEG-Y MiniSEED;

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