DocumentCode :
2426681
Title :
Feature Abstraction of Time-Sequence Curve and Its Similarity Calculation
Author :
Li, Guohe ; Jiang, Xi
Author_Institution :
China Univ. of Pet., Beijing
Volume :
4
fYear :
2007
fDate :
24-27 Aug. 2007
Firstpage :
374
Lastpage :
378
Abstract :
Time-sequence data are visually shown in curves. A great deal of information can be derived from them, which lays the foundation for the recognition of curves. Along the x-axis direction and by means of averagely dividing 0deg ~180deg into small intervals, standard codes are adopted to represent the general tendency of the curve. Based on standard codes, corresponding revisal codes are adopted to represent the deviation from them. The combination of the two-level codes describes the curve shape exactly. A similarity function is defined to compute the similarity between two curves, which in most cases are not of the same length. The method described above is proved effective in the recognition of sediment microfacies by well-logging curves from the Luliang Area of Xinjiang Kelamayi Oil Field.
Keywords :
pattern recognition; Xinjiang Kelamayi Oil Field; curve recognition; feature abstraction; revisal codes; similarity calculation; time-sequence curve; well-logging curves; Code standards; Computer science; Fourier transforms; Frequency domain analysis; Petroleum; Sediments; Shape; Testing; Wavelet domain; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2874-8
Type :
conf
DOI :
10.1109/FSKD.2007.289
Filename :
4406415
Link To Document :
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