Application of data mining in development index forecast of an oilfield during the middle and later stage

2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009

Volumn 4, Issue , 2009, Pages 291-296

  Yan, Yang ^a   Liu, Zhi Bin ^a   Zhong, Yi Hua ^a  

^a SOUTHWEST PETROLEUM UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL RESULTS; DATA MINING METHODS; GREY RELATIONAL ANALYSIS; HISTORICAL DATA; IMPACT FACTOR; INFLUENCE FACTORS; INPUT-OUTPUT; NON-LINEAR RELATIONSHIPS; OPTIMAL CONTROLS; SUPPORT VECTOR REGRESSIONS; WATER CUTS; WHOLE PROCESS;

COMPUTER SCIENCE; FORECASTING; FUZZY CLUSTERING; MINING;

OIL FIELD DEVELOPMENT;

EID: 70449364042     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CSIE.2009.390     Document Type: Conference Paper

References (18)

1. C. C. Chang and C. J. Lin. LIBSVM: A Library for Support Vector Machines (Version 2.71, November 2004). Software available at: ¡http://www.csie. ntu.edu.tw/ cjlin/libsvm¿.
2. T. C. Chang and S. J. Lin. Grey relation analysis of carbon dioxide emissions from industrial production and energy uses in Taiwan. Journal of Environmental Management, 1999, 56 (4): 247-257.
3. C. Chatfield. Time-series forecasting. Chapman & Hall/CRC Press, Boca Raton, 2001.
4. Y. Q. Chen. Derivation and Application of the Generalized Weng Model. Natural Gas Industry Journal, 1996, 16 (2): 22-26.(in Chinese).
5. N. Cristianini and J. Shawe-Taylor. An introduction to support vector machines and other kernel-based learning methods. Cambridge University Press, Cambridge, 2000.
6. J. L. Deng. Control problems of gray systems. System Control Letter, 1982, 1(4): 288-294.
7. L. Y. Feng, J. C. Li and X. Q. Pang, etc. Peak oil models forecast China's oil supply and demand. Oil & Gas Journal, 2008, 2: 43-47.
8. K. L. Peng, C. H. Wu and Y. J. Goo. The development of a new statistical technique for relating financial information to stock market returns. International Journal of Management, 2004, 21(4): 492-505.
9. C. W. Hsu, C. C. Chang and C. J. Lin. A Practical Guide to Support Vector Classification. Available at: 〈http://www.csie.ntu. edu.tw/ cjlin/papers/guide/guide.pdf〉, 2003.
10. J. G. Hu, Y. Q Chen and S. Z. Zhang. A New Model for Predicting Production and Reserves of Oil and Gas Fields. Acta Petrolei Sinica, 1995, 6 (1): 79-86.
11. A. D. Nola, S. Sessa, W. Pedrycz and E. Sanchez. Fuzzy Relation Equations and Their Applications to Knowledge Engineering, Kluwer Academic Publishers, Dordrecht, 1989.
12. B. Scholkopf and A. J. Smola. Learning with kernels. MIT Press, Cambridge, 2002.
13. A. J. Smola and B. Scholkopf. A tutorial on support vector regression. University of London, UK, 1998.
14. V. N. Vapnik. The nature of statistical learning theory. Springer, New York, 1995.
15. V. N. Vapnik. Statistical learning theory. Wiley, New York, 1998.
16. V. N. Vapnik. An overview of statistical learning theory. IEEE Transactions on Neural Networks 1999, 10 (5): 988-999.
17. H. H. Wu. A comparative study of using grey relational analysis in multiple attribute decision making problems. Quality Engineering, 2002, 159(2):209-217.
18. Q. F. Zhao and Y. Q Chen. Forecast and Analysis of China's Oil Consumption and Crude Oil Supply. Oil Forum, 2006, (2): 26-28.