西安石油大学学报（自然科学版）2017，Vol.32Issue(4)：46-49,54,5.DOI:10.3969/j.issn.1673-064X.2017.04.007
基于支持向量机的页岩储层横波速度预测
Prediction of Shear Wave Velocity in Shale Reservoir Based on Support Vector Machine
摘要
Abstract
In order to solve the problem of lacking the data of shear wave velocity in oil and gas fields,a method for predicting the shear wave velocity in shale reservoir is proposed,which is based on conventional logging data.The relationship between shear wave velocity and natural gamma,density and resistivity logging data of shale reservoir was established by support vector machine (SVM).The prediction model was trained by the data of 10 000 samples from Weiyuan block in Sichuan Basin and tested by the data of 1 500 samples from the same block,its prediction accuracy of the test set is 97.2 ％.关键词
页岩储层/横波速度预测/支持向量机Key words
shale reservoir/prediction of shear wave velocity/support vector machine分类
能源科技引用本文复制引用
倪维军,李琪,郭文惠,冯涛,李旭梅,周婷婷..基于支持向量机的页岩储层横波速度预测[J].西安石油大学学报（自然科学版）,2017,32(4):46-49,54,5.基金项目
国家自然科学基金“基于多源信息和智能计算的钻井异常自适应预警方法研究”(编号:51574194) （编号:51574194）
陕西省工业科技攻关计划“非常规油气钻井随钻风险动态预警技术研究”(编号:2016GY-144) （编号:2016GY-144）
陕西省教育厅专项科研计划项目“页岩储层地质力学模型的建立方法及应用研究”(编号:16JK1613),“基于多源信息融合的钻井事故动态预警系统研究”(编号:15JK1567) （编号:16JK1613）
西安石油大学青年科技创新基金“基于地质力学模型的钻井异常预警方法研究”(编号:2016BS09). （编号:2016BS09）
