SVM model based on signal transformation and its applications in oil water-flooded identification

  • Authors:

  • Fuhua Shang;Lei Wang

  • Affiliations:

  • Computer Science and Technology Department, Daqing Petroleum Institute, Daqing, China;Computer Science and Technology Department, Daqing Petroleum Institute, Daqing, China

  • Venue:
  • FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 5
  • Year:
  • 2009

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Abstract

This paper, a method of signal transformation for feature extraction is proposed. It can transform log-signal space into the vector space, which the experiment system requires, and then use SVM (Support Vector Machine) automatically to identify the water-flooded status of oil-saturated stratum. The results of experiment indicate that this algorithm has good identification ability and strong generalization ability in condition that the number of training swatch is limited.