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4 - Sampling Theorem for Seismic Data

from Part II - Deterministic Digital Signal Processing for Seismic Data

Published online by Cambridge University Press:  24 December 2019

Wail A. Mousa
Wail A. Mousa
Affiliation:
King Fahd University of Petroleum and Minerals, Saudi Arabia
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Summary

This chapter presents sampling theorem for seismic data, including Shannon sampling theory for sampling continuous time (space) signals. Also, we explain the aliasing effects due to under-sampling of seismic data sets. Moreover, the theory of compressive sensing (CS) is currently considered the state-of-the-art theory of DSP, with many applications related to signal and image compression, signal recovery, and many other applications. CS is currently used for various seismic data processing problems. Hence, in this chapter we introduce CS principles and provide a few seismic data processing-related applications.

Keywords

sampling theoremShannon samplingaliasing effects and seismic datacomprehensive sensing
Type
Chapter
Information
Advanced Digital Signal Processing of Seismic Data , pp. 193 - 220
Publisher: Cambridge University Press
Print publication year: 2020

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  • Sampling Theorem for Seismic Data
  • Wail A. Mousa, King Fahd University of Petroleum and Minerals, Saudi Arabia
  • Book: Advanced Digital Signal Processing of Seismic Data
  • Online publication: 24 December 2019
  • Chapter DOI: https://doi.org/10.1017/9781139626286.007
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To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

  • Sampling Theorem for Seismic Data
  • Wail A. Mousa, King Fahd University of Petroleum and Minerals, Saudi Arabia
  • Book: Advanced Digital Signal Processing of Seismic Data
  • Online publication: 24 December 2019
  • Chapter DOI: https://doi.org/10.1017/9781139626286.007
Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

  • Sampling Theorem for Seismic Data
  • Wail A. Mousa, King Fahd University of Petroleum and Minerals, Saudi Arabia
  • Book: Advanced Digital Signal Processing of Seismic Data
  • Online publication: 24 December 2019
  • Chapter DOI: https://doi.org/10.1017/9781139626286.007
Available formats
×