A Multi Tone Modeling for Seismic Data Compression

Bo Liu; M. Mohandes; H. Nuha; M. Deriche; Naveed Iqbal; Faramarz Fekri; James H. McClellan

doi:10.1190/segam2019-3208024.1

A Multi Tone Modeling for Seismic Data Compression

Bo Liu
, M. Mohandes
, H. Nuha
, M. Deriche
, Naveed Iqbal
, Faramarz Fekri
, James H. McClellan

King Fahd University of Petroleum and Minerals
Georgia Institute of Technology

Research output: Contribution to journal › Conference article › peer-review

3 Scopus citations

Abstract

This work develops a multi tone modeling for seismic data compression. First, seismic traces are described as multitone decaying sinusoidal waves superposition. Each sinusoidal wave is regarded as a model component and is represented by a set of distinct parameters. Secondly, a novel parameter estimation algorithm for this model is proposed accordingly. In this algorithm, the parameters are estimated for each component sequentially. A suitable number of model components is determined by the level of the residuals energy. The proposed model-based compression scheme outperforms the Linear Predictive Coding (LPC) both analytically and experimentally in terms of compression ratio, reconstruction quality and convergence rate.

Original language	English
Pages (from-to)	263-267
Number of pages	5
Journal	SEG Technical Program Expanded Abstracts
DOIs	https://doi.org/10.1190/segam2019-3208024.1
State	Published - 10 Aug 2019
Externally published	Yes
Event	Society of Exploration Geophysicists International Exposition and 89th Annual Meeting, SEG 2019 - San Antonio, United States Duration: 15 Sep 2019 → 20 Sep 2019

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10.1190/segam2019-3208024.1

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@article{113116b468d243ebb45700f0c0599c5f,

title = "A Multi Tone Modeling for Seismic Data Compression",

abstract = "This work develops a multi tone modeling for seismic data compression. First, seismic traces are described as multitone decaying sinusoidal waves superposition. Each sinusoidal wave is regarded as a model component and is represented by a set of distinct parameters. Secondly, a novel parameter estimation algorithm for this model is proposed accordingly. In this algorithm, the parameters are estimated for each component sequentially. A suitable number of model components is determined by the level of the residuals energy. The proposed model-based compression scheme outperforms the Linear Predictive Coding (LPC) both analytically and experimentally in terms of compression ratio, reconstruction quality and convergence rate.",

author = "Bo Liu and M. Mohandes and H. Nuha and M. Deriche and Naveed Iqbal and Faramarz Fekri and McClellan, \{James H.\}",

note = "Publisher Copyright: {\textcopyright} 2019 SEG; Society of Exploration Geophysicists International Exposition and 89th Annual Meeting, SEG 2019 ; Conference date: 15-09-2019 Through 20-09-2019",

year = "2019",

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doi = "10.1190/segam2019-3208024.1",

language = "English",

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T1 - A Multi Tone Modeling for Seismic Data Compression

AU - Liu, Bo

AU - Mohandes, M.

AU - Nuha, H.

AU - Deriche, M.

AU - Iqbal, Naveed

AU - Fekri, Faramarz

AU - McClellan, James H.

PY - 2019/8/10

Y1 - 2019/8/10

N2 - This work develops a multi tone modeling for seismic data compression. First, seismic traces are described as multitone decaying sinusoidal waves superposition. Each sinusoidal wave is regarded as a model component and is represented by a set of distinct parameters. Secondly, a novel parameter estimation algorithm for this model is proposed accordingly. In this algorithm, the parameters are estimated for each component sequentially. A suitable number of model components is determined by the level of the residuals energy. The proposed model-based compression scheme outperforms the Linear Predictive Coding (LPC) both analytically and experimentally in terms of compression ratio, reconstruction quality and convergence rate.

AB - This work develops a multi tone modeling for seismic data compression. First, seismic traces are described as multitone decaying sinusoidal waves superposition. Each sinusoidal wave is regarded as a model component and is represented by a set of distinct parameters. Secondly, a novel parameter estimation algorithm for this model is proposed accordingly. In this algorithm, the parameters are estimated for each component sequentially. A suitable number of model components is determined by the level of the residuals energy. The proposed model-based compression scheme outperforms the Linear Predictive Coding (LPC) both analytically and experimentally in terms of compression ratio, reconstruction quality and convergence rate.

UR - https://www.scopus.com/pages/publications/85121860612

U2 - 10.1190/segam2019-3208024.1

DO - 10.1190/segam2019-3208024.1

M3 - Conference article

AN - SCOPUS:85121860612

SN - 1052-3812

SP - 263

EP - 267

JO - SEG Technical Program Expanded Abstracts

JF - SEG Technical Program Expanded Abstracts

T2 - Society of Exploration Geophysicists International Exposition and 89th Annual Meeting, SEG 2019

Y2 - 15 September 2019 through 20 September 2019

ER -

A Multi Tone Modeling for Seismic Data Compression

Abstract

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