Application of support vector machine in prediction of reservoir parameters

摘要：

The conventional method is not performing well in reservoir parameters prediction because of lacking learning samples. The support vector machine method could help us in this situation. We repeat an experiment to verify the excellent generalization ability of SVM. Four applications of real data processing were done by us, and they were all working very well. The result shows that this method would bring us to a nice place.

关键词： support vector machine regression method reservoir parameter prediction porosity prediction

作者: Ye Duan-nan Zhang Guang-zhi

作者单位: College of Geo-resources and Information, China University of Petroleum (East China), Qingdao, China

会议类型: 国际会议

会议名称: 2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)

会议地点: 北京

会议语种:英文

页码: 2539-2542

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）