• DocumentCode
    1489240
  • Title

    Fuzzy Clustering of Seismic Sequences: Segmentation of Time-Frequency Representations

  • Author

    Hashemi, Hosein

  • Author_Institution
    Institute of Geophysics, University of Tehran, Tehran, IRAN
  • Volume
    29
  • Issue
    3
  • fYear
    2012
  • fDate
    5/1/2012 12:00:00 AM
  • Firstpage
    82
  • Lastpage
    87
  • Abstract
    Time-frequency (TF) representations based on minimum mean cross-entropy (MMCE) solution, Bessel kernel, and generalized marginal page distribution are used as the input of clustering. It is shown that general trends of frequency changed with time are not the same for these transforms. The proposed method is based on the knowledge integration of TF transforms followed by a clustering data matrix and the derivation of fuzzy membership values. Based on the output of cluster membership values, the full bandwidth illumination (FBWI) index is defined as a tool for qualitative seismic interpretation. The method is applicable for studying the frequency behavior of reflectors in a reservoir for detecting fluid migration paths.
  • Keywords
    Bessel functions; entropy; fuzzy set theory; geophysical fluid dynamics; geophysical signal processing; pattern clustering; seismology; sequences; Bessel kernel; FBWI index; MMCE solution; cluster membership values; clustering data matrix; fluid migration paths; full bandwidth illumination; fuzzy clustering; fuzzy membership values; generalized marginal page distribution; minimum mean cross-entropy; qualitative seismic interpretation; reflectors; reservoir; segmentation; seismic sequences; time-frequency representations; Clustering algorithms; Color; Fuzzy models; Geophysical measurements; Geophysical signal processing; Indexes; Shape analysis; Time frequency analysis;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    1053-5888
  • Type

    jour

  • DOI
    10.1109/MSP.2012.2185897
  • Filename
    6179821