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100   $a20200325d2020      u|             0
101 0 $aeng
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200 10$aModern Singular Spectral-Based Denoising and Filtering Techniques for 2D and 3D Reflection Seismic Data$b[electronic resource] /$fby R. K. Tiwari, R. Rekapalli
205   $a1st ed. 2020.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020.
215   $a1 online resource (XVI, 157 p. 104 illus., 43 illus. in color.) 
311   $a3-030-19303-9 
320   $aIncludes bibliographical references and index.
327   $a1. Introduction to Denoising and Data Gap Filling of Seismic Reflection Data -- 2. Time and Frequency Domain Eigen Image and Cadzow Noise Filtering of 2D Seismic Data -- 3. Time Domain Frequency Filtering of High Resolution Seismic Reflection Data Using Singular Spectral Analysis -- 4. Frequency and Time Domain SSA for 2D Seismic Data Denoising -- 5. Filtering 2D Seismic Data Using the Time Slice Singular Spectral Analysis -- 6. Robust and Fast Algorithms for Singular Spectral Analysis of Seismic Data -- 7. Denoising the 3D Seismic Data Using Multichannel Singular Spectrum Analysis -- 8. Seismic Data Gap Filling Using the Singular Spectrum Based Analysis -- 9. Singular Spectrum vs. Wavelet Based Denoising Schemes in Generalized Inversion Based Seismic Wavelet Estimation -- 10. Singular Spectrum-based Filtering to Enhance the Resolution of Seismic Attributes -- 11. Singular Spectrum Analysis with MATLAB -- Appendix -- Index.
330   $aThis book discusses the latest advances in singular spectrum-based algorithms for seismic data processing, providing an update on recent developments in this field. Over the past few decades, researchers have extensively studied the application of the singular spectrum-based time and frequency domain eigen image methods, singular spectrum analysis (SSA) and multichannel SSA for various geophysical data. This book addresses seismic reflection signals, which represent the amalgamated signals of several unwanted signals/noises, such as ground roll, diffractions etc. Decomposition of such non-stationary and erratic field data is one of the multifaceted tasks in seismic data processing. This volume also includes comprehensive methodological and parametric descriptions, testing on appropriately generated synthetic data, as well as comparisons between time and frequency domain algorithms and their applications to the field data on 1D, 2D, 3D and 4D data sets. Lastly, it features an exclusive chapter with MATLAB coding for SSA.
606   $aGeophysics
606   $aNoise control
606   $aEnvironmental management
606   $aPhysical geography
606   $aFossil fuels
606   $aGeophysics and Environmental Physics$3https://scigraph.springernature.com/ontologies/product-market-codes/P32000
606   $aGeophysics/Geodesy$3https://scigraph.springernature.com/ontologies/product-market-codes/G18009
606   $aNoise Control$3https://scigraph.springernature.com/ontologies/product-market-codes/U27004
606   $aEnvironmental Management$3https://scigraph.springernature.com/ontologies/product-market-codes/U17009
606   $aEarth System Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/G35000
606   $aFossil Fuels (incl. Carbon Capture)$3https://scigraph.springernature.com/ontologies/product-market-codes/114000
615  0$aGeophysics.
615  0$aNoise control.
615  0$aEnvironmental management.
615  0$aPhysical geography.
615  0$aFossil fuels.
615 14$aGeophysics and Environmental Physics.
615 24$aGeophysics/Geodesy.
615 24$aNoise Control.
615 24$aEnvironmental Management.
615 24$aEarth System Sciences.
615 24$aFossil Fuels (incl. Carbon Capture).
676   $a551.22
700   $aTiwari$b R. K$4aut$4http://id.loc.gov/vocabulary/relators/aut$0947692
702   $aRekapalli$b R$4aut$4http://id.loc.gov/vocabulary/relators/aut
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a996418162603316
996   $aModern Singular Spectral-Based Denoising and Filtering Techniques for 2D and 3D Reflection Seismic Data$92141305
997   $aUNISA