Multi-Component Temporal-Correlation Seismic Data Compression Algorithm Based on the PCA and DWT

Industrial application data acquisition systems can be sources of vast amounts of data. The seismic surveys conducted by oil and gas companies result in enormous datasets, often exceeding terabytes of data. The storage and communication demands these data require can only be achieved through compres...

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Vydáno v:Algorithms Ročník 18; číslo 1; s. 33
Hlavní autoři: Lucena, Mateus Martinez de, Ribeiro, Josafat Leal, Wagner, Matheus, Fröhlich, Antônio Augusto
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 01.01.2025
Témata:
Algorithms
Case studies
Compressed gas
compression algorithms
Data acquisition
Data compression
Datasets
Decomposition
Discrete Wavelet Transform
Eigenvalues
Entropy
Error analysis
Frequency ranges
Industrial applications
Information storage and retrieval
Machine learning
Noise threshold
Performance evaluation
principal component analysis
Principal components analysis
Reconstruction
Seismic surveys
Time series
Wavelet analysis
Wavelet transforms
ISSN:1999-4893, 1999-4893
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Abstract Industrial application data acquisition systems can be sources of vast amounts of data. The seismic surveys conducted by oil and gas companies result in enormous datasets, often exceeding terabytes of data. The storage and communication demands these data require can only be achieved through compression. Careful consideration must be given to minimize the reconstruction error of compressed data caused by lossy compression. This paper investigates the combination of principal component analysis (PCA), discrete wavelet transform (DWT), thresholding, quantization, and entropy encoding to compress such datasets. The proposed method is a lossy compression algorithm tuned by evaluating the reconstruction error in frequency ranges of interest, namely 0–20 Hz and 15–65 Hz. The PCA compression and decompression acts as a noise filter while the DWT drives the compression. The proposed method can be tuned through threshold and quantization percentages and the number of principal components to achieve compression rates of up to 31:1 with reconstruction residues energy of less than 4% in the frequency ranges of 0–20 Hz, 15–65 Hz, and 60–105 Hz.
AbstractList Industrial application data acquisition systems can be sources of vast amounts of data. The seismic surveys conducted by oil and gas companies result in enormous datasets, often exceeding terabytes of data. The storage and communication demands these data require can only be achieved through compression. Careful consideration must be given to minimize the reconstruction error of compressed data caused by lossy compression. This paper investigates the combination of principal component analysis (PCA), discrete wavelet transform (DWT), thresholding, quantization, and entropy encoding to compress such datasets. The proposed method is a lossy compression algorithm tuned by evaluating the reconstruction error in frequency ranges of interest, namely 0–20 Hz and 15–65 Hz. The PCA compression and decompression acts as a noise filter while the DWT drives the compression. The proposed method can be tuned through threshold and quantization percentages and the number of principal components to achieve compression rates of up to 31:1 with reconstruction residues energy of less than 4% in the frequency ranges of 0–20 Hz, 15–65 Hz, and 60–105 Hz.
Audience Academic
Author Wagner, Matheus
Ribeiro, Josafat Leal
Lucena, Mateus Martinez de
Fröhlich, Antônio Augusto
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Cites_doi 10.1109/ACCESS.2020.3003682
10.1016/B978-012620861-0/50020-6
10.1016/j.petlm.2018.11.001
10.17487/rfc1951
10.1109/BigData.2018.8622520
10.1109/IEEEGCC.2017.8448168
10.1109/30.125072
10.17230/ingciencia.11.21.11
10.1109/TGRS.2018.2789354
10.1109/ICCA59364.2023.10401790
10.1190/sbgf2013-188
10.1017/CBO9780511804441
10.1109/PEMWA.2009.5208325
10.1109/TPAMI.2013.50
10.1016/j.jappgeo.2016.03.033
10.1109/TIE.2014.2327917
10.1109/ICDE51399.2021.00145
10.1190/1.3255623
10.1137/18M1168832
10.1007/s12517-021-08675-y
10.1109/TBDATA.2022.3201176
10.1109/MSP.2017.2784458
10.1109/TVCG.2014.2346458
10.1190/1.9781560803447
10.1088/1742-2132/13/2/135
10.20944/preprints202308.0165.v1
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References Xiong (ref_12) 2020; 8
Liang (ref_29) 2023; 9
ref_14
ref_13
Liu (ref_18) 2018; 56
Liu (ref_17) 2016; 13
ref_31
ref_30
ref_19
Mohammadpoor (ref_5) 2020; 6
ref_16
Diffenderfer (ref_28) 2019; 41
Lindstrom (ref_27) 2014; 20
Payani (ref_4) 2018; 35
ref_25
Javed (ref_3) 2015; 62
ref_24
ref_23
ref_21
Nuha (ref_11) 2021; 14
ref_20
ref_1
ref_2
Bengio (ref_22) 2013; 35
Wallace (ref_8) 1992; 38
Fajardo (ref_6) 2015; 11
ref_26
ref_9
Gan (ref_15) 2016; 130
ref_7
Sze (ref_10) 2014; Volume 39
References_xml – volume: 8
  start-page: 114443
  year: 2020
  ident: ref_12
  article-title: High Bit-Depth Seismic Data Compression: A Novel Codec Under the Framework of HEVC
  publication-title: IEEE Access
  doi: 10.1109/ACCESS.2020.3003682
– ident: ref_9
– ident: ref_24
  doi: 10.1016/B978-012620861-0/50020-6
– volume: 6
  start-page: 321
  year: 2020
  ident: ref_5
  article-title: Big Data analytics in oil and gas industry: An emerging trend
  publication-title: Petroleum
  doi: 10.1016/j.petlm.2018.11.001
– ident: ref_25
  doi: 10.17487/rfc1951
– ident: ref_31
  doi: 10.1109/BigData.2018.8622520
– ident: ref_7
  doi: 10.1109/IEEEGCC.2017.8448168
– volume: 38
  start-page: xviii
  year: 1992
  ident: ref_8
  article-title: The JPEG still picture compression standard
  publication-title: IEEE Trans. Consum. Electron.
  doi: 10.1109/30.125072
– volume: Volume 39
  start-page: 40
  year: 2014
  ident: ref_10
  article-title: High efficiency video coding (HEVC)
  publication-title: Integrated Circuit and Systems, Algorithms and Architectures
– ident: ref_14
– volume: 11
  start-page: 221
  year: 2015
  ident: ref_6
  article-title: Seismic Data Compression Using 2D Lifting-Wavelet Algorithms
  publication-title: Ingeniería Cienc.
  doi: 10.17230/ingciencia.11.21.11
– ident: ref_21
– volume: 56
  start-page: 3020
  year: 2018
  ident: ref_18
  article-title: A Distributed Principal Component Analysis Compression for Smart Seismic Acquisition Networks
  publication-title: IEEE Trans. Geosci. Remote Sens.
  doi: 10.1109/TGRS.2018.2789354
– ident: ref_20
  doi: 10.1109/ICCA59364.2023.10401790
– ident: ref_26
  doi: 10.1190/sbgf2013-188
– ident: ref_23
  doi: 10.1017/CBO9780511804441
– ident: ref_2
  doi: 10.1109/PEMWA.2009.5208325
– volume: 35
  start-page: 1798
  year: 2013
  ident: ref_22
  article-title: Representation Learning: A Review and New Perspectives
  publication-title: IEEE Trans. Pattern Anal. Mach. Intell.
  doi: 10.1109/TPAMI.2013.50
– volume: 130
  start-page: 194
  year: 2016
  ident: ref_15
  article-title: Compressive sensing for seismic data reconstruction via fast projection onto convex sets based on seislet transform
  publication-title: J. Appl. Geophys.
  doi: 10.1016/j.jappgeo.2016.03.033
– volume: 62
  start-page: 647
  year: 2015
  ident: ref_3
  article-title: Enabling Health Monitoring Approach Based on Vibration Data for Accurate Prognostics
  publication-title: IEEE Trans. Ind. Electron.
  doi: 10.1109/TIE.2014.2327917
– ident: ref_30
  doi: 10.1109/ICDE51399.2021.00145
– ident: ref_16
  doi: 10.1190/1.3255623
– volume: 41
  start-page: A1867
  year: 2019
  ident: ref_28
  article-title: Error Analysis of ZFP Compression for Floating-Point Data
  publication-title: SIAM J. Sci. Comput.
  doi: 10.1137/18M1168832
– ident: ref_13
– volume: 14
  start-page: 2542
  year: 2021
  ident: ref_11
  article-title: Seismic data modeling and compression using particle swarm optimization
  publication-title: Arab. J. Geosci.
  doi: 10.1007/s12517-021-08675-y
– volume: 9
  start-page: 485
  year: 2023
  ident: ref_29
  article-title: SZ3: A Modular Framework for Composing Prediction-Based Error-Bounded Lossy Compressors
  publication-title: IEEE Trans. Big Data
  doi: 10.1109/TBDATA.2022.3201176
– volume: 35
  start-page: 51
  year: 2018
  ident: ref_4
  article-title: Advances in seismic data compression via learning from data: Compression for seismic data acquisition
  publication-title: IEEE Signal Process. Mag.
  doi: 10.1109/MSP.2017.2784458
– volume: 20
  start-page: 2674
  year: 2014
  ident: ref_27
  article-title: Fixed-Rate Compressed Floating-Point Arrays
  publication-title: IEEE Trans. Vis. Comput. Graph.
  doi: 10.1109/TVCG.2014.2346458
– ident: ref_1
  doi: 10.1190/1.9781560803447
– volume: 13
  start-page: 135
  year: 2016
  ident: ref_17
  article-title: An effective approach to attenuate random noise based on compressive sensing and curvelet transform
  publication-title: J. Geophys. Eng.
  doi: 10.1088/1742-2132/13/2/135
– ident: ref_19
  doi: 10.20944/preprints202308.0165.v1
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SubjectTerms Algorithms
Case studies
Compressed gas
compression algorithms
Data acquisition
Data compression
Datasets
Decomposition
Discrete Wavelet Transform
Eigenvalues
Entropy
Error analysis
Frequency ranges
Industrial applications
Information storage and retrieval
Machine learning
Noise threshold
Performance evaluation
principal component analysis
Principal components analysis
Reconstruction
Seismic surveys
Time series
Wavelet analysis
Wavelet transforms
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