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
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;
Conference_Titel :
Computational and Information Sciences (ICCIS), 2012 Fourth International Conference on
Conference_Location :
Chongqing
Print_ISBN :
978-1-4673-2406-9
DOI :
10.1109/ICCIS.2012.79