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8 - Seismic Wavelet Processing

from Part III - Statistical 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

Seismic wavelets model so many signals, including seismic source signatures, and are a main part of the seismic convolution model. They can be classified in various types. This chapter discusses various types of wavelet and their importantce. Also, it presents seismic wavelet processing as a method to shape the seismic wavelet, i.e., reduce its effect on seismic data sets.

Keywords

Seismic waveletswavelet typesdipole waveletsminimum-delymaximum-delay and mixed delay waveletsRicker waveletsWavelet processing
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Chapter
Information
Advanced Digital Signal Processing of Seismic Data , pp. 298 - 312
Publisher: Cambridge University Press
Print publication year: 2020

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  • Seismic Wavelet Processing
  • 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/10.1017/9781139626286.012
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  • Seismic Wavelet Processing
  • 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/10.1017/9781139626286.012
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.

  • Seismic Wavelet Processing
  • 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/10.1017/9781139626286.012
Available formats
×