Hydrocarbon prediction method based on SVM feature selection

Tianranqi Gongye/Natural Gas Industry

Volumn 24, Issue 7, 2004, Pages

  Yao, Kaifeng ^a   Lu, Wenkai ^a   Ding, Wenlong ^a   Zhang, Shanwen ^b   Xiao, Huanqin ^b   Li, Yanda ^a  

^a TSINGHUA UNIVERSITY   (China)

^b SINOPEC   (China)

Author keywords

Guanyinchang gas field; Oil and gas reservoir; Prediction; Seismic data processing; Vector computer

Indexed keywords

GUANYINCHANG GAS FIELDS; SEISMIC DATA PROCESSING; SUPPORT VECTOR MACHINES (SVM); VECTOR COMPUTERS;

DATA PROCESSING; FEATURE EXTRACTION; HYDROCARBONS; LEARNING SYSTEMS; PETROLEUM RESERVOIRS; SEISMOLOGY;

NATURAL GAS;

EID: 3943103414     PISSN: 10000976     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (9)

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2. Joachims T Making large-scale SVM learning practical. Advances in Kernel Methods-Support Vector Learning, Sch? lkopf B, Burges C and Smola A (ed.), MIT Press, 1999
3. Guyon I, Weston J, Barnhill S et al. Gene selection for cancer classification using support vector machines. Machine Learning, 2002; 46(1): 389-422
4. Yao Kai-Feng, Lu Wen-Kai, Zhang Shan-Wen et al. Feature expansion and feature selection for general pattern recognition problems. IEEE Int Conf Neural Networks & Signal Processing, Nanjing, China, 2003; (12) :29-32