Seismic Data Compression: A Survey

Hilal Nuha; Mohamed Mohandes; Bo Liu; Ali Al-Shaikhi

doi:10.1007/978-3-030-73026-0_58

Seismic Data Compression: A Survey

Hilal Nuha, Mohamed Mohandes^*, Bo Liu, Ali Al-Shaikhi

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

With the advent of robust computing power, any sophisticated algorithm for data compression is becoming a trivial task. With more than petabytes of seismic data produced every day and the trend toward 4D survey, it is becoming essential to develop robust algorithms for the seismic data compression. This led to significant research efforts in data compression for field implementation, as shown by the research trends. The study of seismic data compression techniques is the main focus of this paper. In particular, we provide a short survey of different seismic data compression methods. This survey covers several categories of compression techniques, namely transformation, prediction, quantization, run length, and sampling. This paper can be deemed an initial attempt to provide an up-to-date overview of the research work carried in this all-important field of seismic data processing.

Original language	English
Title of host publication	Advances in Geophysics, Tectonics and Petroleum Geosciences - Proceedings of the 2nd Springer Conference of the Arabian Journal of Geosciences CAJG-2, Tunisia 2019
Editors	Mustapha Meghraoui, Narasimman Sundararajan, Santanu Banerjee, Klaus-G. Hinzen, Mehdi Eshagh, François Roure, Helder I. Chaminé, Said Maouche, André Michard
Publisher	Springer Nature
Pages	253-255
Number of pages	3
ISBN (Print)	9783030730253
DOIs	https://doi.org/10.1007/978-3-030-73026-0_58
State	Published - 2022

Publication series

Name	Advances in Science, Technology and Innovation
ISSN (Print)	2522-8714
ISSN (Electronic)	2522-8722

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

Data compression
Seismics
Survey

ASJC Scopus subject areas

Architecture
Environmental Chemistry
Renewable Energy, Sustainability and the Environment

Access to Document

10.1007/978-3-030-73026-0_58

Cite this

Nuha, H., Mohandes, M., Liu, B., & Al-Shaikhi, A. (2022). Seismic Data Compression: A Survey. In M. Meghraoui, N. Sundararajan, S. Banerjee, K.-G. Hinzen, M. Eshagh, F. Roure, H. I. Chaminé, S. Maouche, & A. Michard (Eds.), Advances in Geophysics, Tectonics and Petroleum Geosciences - Proceedings of the 2nd Springer Conference of the Arabian Journal of Geosciences CAJG-2, Tunisia 2019 (pp. 253-255). (Advances in Science, Technology and Innovation). Springer Nature. https://doi.org/10.1007/978-3-030-73026-0_58

Nuha, Hilal ; Mohandes, Mohamed ; Liu, Bo et al. / Seismic Data Compression : A Survey. Advances in Geophysics, Tectonics and Petroleum Geosciences - Proceedings of the 2nd Springer Conference of the Arabian Journal of Geosciences CAJG-2, Tunisia 2019. editor / Mustapha Meghraoui ; Narasimman Sundararajan ; Santanu Banerjee ; Klaus-G. Hinzen ; Mehdi Eshagh ; François Roure ; Helder I. Chaminé ; Said Maouche ; André Michard. Springer Nature, 2022. pp. 253-255 (Advances in Science, Technology and Innovation).

@inproceedings{cce115ce63e14a55af12c858da0013d9,

title = "Seismic Data Compression: A Survey",

abstract = "With the advent of robust computing power, any sophisticated algorithm for data compression is becoming a trivial task. With more than petabytes of seismic data produced every day and the trend toward 4D survey, it is becoming essential to develop robust algorithms for the seismic data compression. This led to significant research efforts in data compression for field implementation, as shown by the research trends. The study of seismic data compression techniques is the main focus of this paper. In particular, we provide a short survey of different seismic data compression methods. This survey covers several categories of compression techniques, namely transformation, prediction, quantization, run length, and sampling. This paper can be deemed an initial attempt to provide an up-to-date overview of the research work carried in this all-important field of seismic data processing.",

keywords = "Data compression, Seismics, Survey",

author = "Hilal Nuha and Mohamed Mohandes and Bo Liu and Ali Al-Shaikhi",

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.",

year = "2022",

doi = "10.1007/978-3-030-73026-0_58",

language = "English",

isbn = "9783030730253",

series = "Advances in Science, Technology and Innovation",

publisher = "Springer Nature",

pages = "253--255",

editor = "Mustapha Meghraoui and Narasimman Sundararajan and Santanu Banerjee and Klaus-G. Hinzen and Mehdi Eshagh and Fran{\c c}ois Roure and Chamin{\'e}, {Helder I.} and Said Maouche and Andr{\'e} Michard",

booktitle = "Advances in Geophysics, Tectonics and Petroleum Geosciences - Proceedings of the 2nd Springer Conference of the Arabian Journal of Geosciences CAJG-2, Tunisia 2019",

address = "United States",

}

Nuha, H, Mohandes, M, Liu, B & Al-Shaikhi, A 2022, Seismic Data Compression: A Survey. in M Meghraoui, N Sundararajan, S Banerjee, K-G Hinzen, M Eshagh, F Roure, HI Chaminé, S Maouche & A Michard (eds), Advances in Geophysics, Tectonics and Petroleum Geosciences - Proceedings of the 2nd Springer Conference of the Arabian Journal of Geosciences CAJG-2, Tunisia 2019. Advances in Science, Technology and Innovation, Springer Nature, pp. 253-255. https://doi.org/10.1007/978-3-030-73026-0_58

Seismic Data Compression: A Survey. / Nuha, Hilal; Mohandes, Mohamed; Liu, Bo et al.
Advances in Geophysics, Tectonics and Petroleum Geosciences - Proceedings of the 2nd Springer Conference of the Arabian Journal of Geosciences CAJG-2, Tunisia 2019. ed. / Mustapha Meghraoui; Narasimman Sundararajan; Santanu Banerjee; Klaus-G. Hinzen; Mehdi Eshagh; François Roure; Helder I. Chaminé; Said Maouche; André Michard. Springer Nature, 2022. p. 253-255 (Advances in Science, Technology and Innovation).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Seismic Data Compression

T2 - A Survey

AU - Nuha, Hilal

AU - Mohandes, Mohamed

AU - Liu, Bo

AU - Al-Shaikhi, Ali

PY - 2022

Y1 - 2022

N2 - With the advent of robust computing power, any sophisticated algorithm for data compression is becoming a trivial task. With more than petabytes of seismic data produced every day and the trend toward 4D survey, it is becoming essential to develop robust algorithms for the seismic data compression. This led to significant research efforts in data compression for field implementation, as shown by the research trends. The study of seismic data compression techniques is the main focus of this paper. In particular, we provide a short survey of different seismic data compression methods. This survey covers several categories of compression techniques, namely transformation, prediction, quantization, run length, and sampling. This paper can be deemed an initial attempt to provide an up-to-date overview of the research work carried in this all-important field of seismic data processing.

AB - With the advent of robust computing power, any sophisticated algorithm for data compression is becoming a trivial task. With more than petabytes of seismic data produced every day and the trend toward 4D survey, it is becoming essential to develop robust algorithms for the seismic data compression. This led to significant research efforts in data compression for field implementation, as shown by the research trends. The study of seismic data compression techniques is the main focus of this paper. In particular, we provide a short survey of different seismic data compression methods. This survey covers several categories of compression techniques, namely transformation, prediction, quantization, run length, and sampling. This paper can be deemed an initial attempt to provide an up-to-date overview of the research work carried in this all-important field of seismic data processing.

KW - Data compression

KW - Seismics

KW - Survey

UR - http://www.scopus.com/inward/record.url?scp=85128986130&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-73026-0_58

DO - 10.1007/978-3-030-73026-0_58

M3 - Conference contribution

AN - SCOPUS:85128986130

SN - 9783030730253

T3 - Advances in Science, Technology and Innovation

SP - 253

EP - 255

BT - Advances in Geophysics, Tectonics and Petroleum Geosciences - Proceedings of the 2nd Springer Conference of the Arabian Journal of Geosciences CAJG-2, Tunisia 2019

A2 - Meghraoui, Mustapha

A2 - Sundararajan, Narasimman

A2 - Banerjee, Santanu

A2 - Hinzen, Klaus-G.

A2 - Eshagh, Mehdi

A2 - Roure, François

A2 - Chaminé, Helder I.

A2 - Maouche, Said

A2 - Michard, André

PB - Springer Nature

ER -

Nuha H, Mohandes M, Liu B, Al-Shaikhi A. Seismic Data Compression: A Survey. In Meghraoui M, Sundararajan N, Banerjee S, Hinzen KG, Eshagh M, Roure F, Chaminé HI, Maouche S, Michard A, editors, Advances in Geophysics, Tectonics and Petroleum Geosciences - Proceedings of the 2nd Springer Conference of the Arabian Journal of Geosciences CAJG-2, Tunisia 2019. Springer Nature. 2022. p. 253-255. (Advances in Science, Technology and Innovation). doi: 10.1007/978-3-030-73026-0_58

Seismic Data Compression: A Survey

Abstract

Publication series

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this