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
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