基于对应分析的支持向量机回归在地震储层厚度预测中的应用

THE APPLICATION OF THE SUPPORT VECTOR MACHINE REGRESSION BASED ON CORRESPONDING ANALYSIS TO THE PREDICTION OF THE SEISMIC RESERVOIR THICKNESS

储层厚度的预测是油气藏描述的一项关键技术,然储层厚度和地震信息之间的关系是非线性的,其他的数学方法很难拟合。解决这一难点用到了一种新的数学统计方法——支持向量机。笔者介绍了对应分析和支持向量回归机算法原理,在此基础上以实际的数据为例子成功地对储层参数—厚度进行了预测,取得了实际的应用效果,得出了该方法切实可行的结论。

The prediction of oil-gas reservoir thickness is a key technology for oil-gas reservoir description. Nevertheless, the relationship between the thickness of the reservoir and the seismic information is nonlinear, and hence the present mathematical method can hardly perform the fitting. To solve this problem, the author used a new mathematical statistical method, namely Support Vector Machine Regression. This paper described the Support Vector Machine Regression and the corresponding analytical methods based on the principle of this technology. On such a basis and with the practical data as an example, the authors successfully predicted the reservoir parameter--the thickness. It is concluded that the technology is feasible and practical.