Automatic fault tracking across seismic volumes via tracking vectors

Zhen Wang, Zhiling Long, Ghassan Alregib, Amin Asjad, Mohamed A. Deriche

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

25 Scopus citations

Abstract

The identification of reservoir regions has a close relationship with the detection of faults in seismic volumes. However, only relying on human intervention, most fault detection algorithms are inefficient. In this paper, we present a new technique that automatically tracks faults across a 3D seismic volume. To implement automation, we propose a two-way fault line projection based on estimated tracking vectors. In the tracking process, projected fault lines are integrated into a synthesized line as the tracked fault line, through an optimization process with local geological constraints. The tracking algorithm is evaluated using real-world seismic data sets with promising results. The proposed method provides comparable accuracy to the detection of faults explicitly in every seismic section, and it also reduces computational complexity.

Original languageEnglish
Title of host publication2014 IEEE International Conference on Image Processing, ICIP 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5851-5855
Number of pages5
ISBN (Electronic)9781479957514
DOIs
StatePublished - 28 Jan 2014

Publication series

Name2014 IEEE International Conference on Image Processing, ICIP 2014

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

Keywords

  • 3D seismic interpretation
  • fault detection and tracking
  • geological optimization
  • motion vectors

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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