Towards robust structure-based enhancement and horizon picking in 3-D seismic data

S. M. O'Malley; I. A. Kakadiaris

Towards robust structure-based enhancement and horizon picking in 3-D seismic data

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

Abstract

We present a navel structure-enhancing adaptive filter guided by features derived from the Gradient Structure Tensor. We employ this filter to reduce noise in seismic data and to assist in generating seed points for initializing an automatic horizon picking algorithm. In addition, our algorithm takes seismic attributes into consideration to reduce the possibilities of false horizon generation and fault-crossing. Comparative experimental results are presented to highlight the potential of our approach.

Original language	English (US)
Pages (from-to)	II482-II489
Journal	Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Volume	2
State	Published - 2004
Event	Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2004 - Washington, DC, United States Duration: Jun 27 2004 → Jul 2 2004

ASJC Scopus subject areas

Software
Computer Vision and Pattern Recognition

Cite this

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title = "Towards robust structure-based enhancement and horizon picking in 3-D seismic data",

abstract = "We present a navel structure-enhancing adaptive filter guided by features derived from the Gradient Structure Tensor. We employ this filter to reduce noise in seismic data and to assist in generating seed points for initializing an automatic horizon picking algorithm. In addition, our algorithm takes seismic attributes into consideration to reduce the possibilities of false horizon generation and fault-crossing. Comparative experimental results are presented to highlight the potential of our approach.",

author = "O'Malley, {S. M.} and Kakadiaris, {I. A.}",

year = "2004",

language = "English (US)",

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pages = "II482--II489",

journal = "Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition",

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note = "Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2004 ; Conference date: 27-06-2004 Through 02-07-2004",

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AU - O'Malley, S. M.

AU - Kakadiaris, I. A.

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N2 - We present a navel structure-enhancing adaptive filter guided by features derived from the Gradient Structure Tensor. We employ this filter to reduce noise in seismic data and to assist in generating seed points for initializing an automatic horizon picking algorithm. In addition, our algorithm takes seismic attributes into consideration to reduce the possibilities of false horizon generation and fault-crossing. Comparative experimental results are presented to highlight the potential of our approach.

AB - We present a navel structure-enhancing adaptive filter guided by features derived from the Gradient Structure Tensor. We employ this filter to reduce noise in seismic data and to assist in generating seed points for initializing an automatic horizon picking algorithm. In addition, our algorithm takes seismic attributes into consideration to reduce the possibilities of false horizon generation and fault-crossing. Comparative experimental results are presented to highlight the potential of our approach.

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M3 - Conference article

AN - SCOPUS:5044226939

SN - 1063-6919

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SP - II482-II489

JO - Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

JF - Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

T2 - Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2004

Y2 - 27 June 2004 through 2 July 2004

ER -

Towards robust structure-based enhancement and horizon picking in 3-D seismic data

Abstract

ASJC Scopus subject areas

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