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

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

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Publisher Copyright:
© 2019 SEG

ASJC Scopus subject areas

Geotechnical Engineering and Engineering Geology
Geophysics

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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.}",

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doi = "10.1190/segam2019-3208024.1",

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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

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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.

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JO - SEG Technical Program Expanded Abstracts

JF - SEG Technical Program Expanded Abstracts

ER -

A Multi Tone Modeling for Seismic Data Compression

Abstract

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