DocumentCode
569736
Title
Application in Water Flooded Layer Recognition Based on Wavelet Packet Transform and Support Vector Machine
Author
Liu Jin-Yue ; Zhu Bao-Ling
Author_Institution
Comput. & Inf. Technol. Coll., Northeast Pet. Univ., Daqing, China
fYear
2012
fDate
17-19 Aug. 2012
Firstpage
1206
Lastpage
1209
Abstract
In view of the complex time-varying signal pattern recognition, the method of water flooded layer recognition based on wavelet packet transform and support vector machine had been proposed in this paper. According to the multi-resolution characteristics of wavelet packet analysis, the denoising for signals and the extraction of useful signals had been presented. The sample space had been mapped into the high dimensional feature space by employing the support vector machine. At the same time, the classification of signals had been also achieved by constructing the optimal separating hyperplane. The experiment showed that this method had the better classification performance and robustness.
Keywords
feature extraction; hydrocarbon reservoirs; petroleum industry; production engineering computing; signal classification; signal denoising; support vector machines; wavelet transforms; well logging; complex time-varying signal pattern recognition; high dimensional feature space; multiresolution characteristics; oilfield development; signal classification; signal denoising; signal extraction; support vector machine; water flooded layer recognition; wavelet packet analysis; wavelet packet transform; Floods; Kernel; Support vector machines; Wavelet analysis; Wavelet packets; support vector machine; water flooded layer recognition; wavelet packet transform;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational and Information Sciences (ICCIS), 2012 Fourth International Conference on
Conference_Location
Chongqing
Print_ISBN
978-1-4673-2406-9
Type
conf
DOI
10.1109/ICCIS.2012.79
Filename
6301333
Link To Document