| 基于阵列感应测井的支持向量机流体识别方法 |
| |
| 引用本文： | 周凡,姜洪福,王立艳,孟凡顺.基于阵列感应测井的支持向量机流体识别方法[J].中国海洋大学学报(自然科学版),2011(Z1):317-323. |
| |
| 作者姓名： | 周凡 姜洪福 王立艳 孟凡顺 |
| |
| 作者单位： | 中国海洋大学海洋地球科学学院;北京大学地球空间科学学院; |
| |
| 摘 要： | 基于研究区块的高分辨率阵列感应测井(HDIL)资料,首先分析了利用交会图法进行流体识别的效果,指出了该常规解释方法的局限性。在此基础上,将基于遗传算法优化的支持向量机(GA-SVM)引入到测井解释当中,结合阵列感应测井和常规测井资料,建立了流体识别的非线性模型。利用该模型对45个训练样本进行回判,准确率为100%,对21个预测样本进行预测的准确率为90.48%,相对于常规解释方法,该流体识别方法具有更高的准确率。
|
| 关 键 词： | 阵列感应测井 支持向量机 遗传算法 流体识别 |
Application of Array Induction Logging and Support Vector Machine to Fluid Identification |
| |
| ZHOU Fan,JIANG Hong-Fu,WANG Li-Yan,MENG Fan-Shun.Application of Array Induction Logging and Support Vector Machine to Fluid Identification[J].Periodical of Ocean University of China,2011(Z1):317-323. |
| |
| Authors: | ZHOU Fan JIANG Hong-Fu WANG Li-Yan MENG Fan-Shun |
| |
| Institution: | ZHOU Fan1,JIANG Hong-Fu2,WANG Li-Yan1,MENG Fan-Shun1(1.College of Marine Geo-Science,Ocean University of China,Qingdao 266100,China,2.College of Earth and Space Science,Peking University,Beijing 100871,China) |
| |
| Abstract: | Based on the data of high-definition array induction logging(HDIL),this paper first analyzes the effect of cross-plot method for fluid identification and points out the limitations of the conventional logging interpretation methods.Support Vector Machines with optimized parameters obtained by Genetic Algorithms(GA-SVM) is applied to the logging interpretation.Combined with HDIL and conventional logging data,a nonlinear mathematical model of fluid identification is established.By using the GA-SVM model,the c... |
| |
| Keywords: | high-definition array induction logging(HDIL) support vector machine(SVM) genetic algorithms(GA) fluid identification |
| 本文献已被 CNKI 等数据库收录！ |
|
