A texture-based region growing algorithm for volume extraction in seismic data

M. G. Orozco-del-Castillo, M. Cárdenas-Soto, C. Ortiz-Alemán, C. Couder-Castañeda, J. Urrutia-Fucugauchi, A. Trujillo-Alcántara

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

We present a novel approach to automated volume extraction in seismic data and apply it to the detection of allochthonous salt bodies. Using a genetic algorithm, we determine the optimal size of volume elements that statistically, according to the U-test, best characterize the contrast between the textures inside and outside of the salt bodies through a principal component analysis approach. This information was used to implement a seeded region growing algorithm to directly extract the bodies from the cube of seismic amplitudes. We present the resulting three-dimensional bodies and compare our final results to those of an interpreter, showing encouraging results.

Original languageEnglish
Pages (from-to)97-105
Number of pages9
JournalGeophysical Prospecting
Volume65
Issue number1
DOIs
StatePublished - 1 Jan 2017

Keywords

  • Genetic algorithms
  • Principal component analysis
  • Salt bodies
  • Seeded-based region growing
  • Seismic textures
  • Statistical tests
  • seismic textures

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