基于偏最小二乘回归方法的毛管压力曲线预测超致密砂岩储层渗透率  

Prediction of ultra-tight sandstone reservoir permeability by capillary pressure curve based on partial least squares regression method

作　　者：郭一凡 司马立强[1,2] 王亮[2,3] 郭宇豪 GUO Yifan;SIMA Liqiang;WANG Liang;GUO Yuhao(School of Geoscience and Technology,Southwest Petroleum University,Chengdu City,Sichuan Province,610500,China;State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation,Southwest Petroleum University,Chengdu City,Sichuan Province,610500,China;College of Energy,Chengdu University of Technology,Chengdu City,Sichuan Province,610059,China)

机构地区：[1]西南石油大学地球科学与技术学院,四川成都610500 [2]西南石油大学油气藏地质及开发工程国家重点实验室,四川成都610500 [3]成都理工大学能源学院,四川成都610059

出　　处：《油气地质与采收率》2022年第6期67-76,共10页Petroleum Geology and Recovery Efficiency

基　　金：国家自然科学基金联合项目“热液作用下的深部含铀油蚀变砂岩地球物理响应及铀油兼探方法”(U2003102);中国博士后科学基金面上资助项目“多因素耦合作用下的致密油储层孔隙结构与含油性评价”(2015M582568)。

摘　　要：由于川西坳陷南部大邑构造须家河组三段超致密砂岩储层渗透率影响因素复杂,经分析、计算发现基于毛管压力曲线的多种经典渗透率预测模型预测精度不理想且存在一定的局限性。为提高超致密砂岩储层渗透率预测精度,在详细分析6种经典渗透率预测模型存在预测误差原因的基础上,优选特征参数,综合考虑孔喉半径、孔喉分布等多项渗透率影响因子,采用留一交叉验证法确定的模型最佳潜变量个数,应用偏最小二乘回归方法(PLSR)建立Winland-r_(5)(PLSR)模型、Pittman(PLSR)模型、Swanson(PLSR)模型3类超致密砂岩储层渗透率预测模型,有效地解决了基于普通最小二乘回归方法(OLS)的渗透率预测模型面临众特征参数多重共线性、小样本不具备模型泛化能力的问题。结果表明,基于偏最小二乘回归方法的3类渗透率预测模型,预测超致密砂岩储层渗透率的误差明显降低,具备泛化能力强、预测精度高、适用性良好的优势。The affecting factors of ultra-tight sandstone reservoir permeability are complex in the Third Member of Xujiahe Formation in Dayi structure of the southern Western Sichuan Depression.Through the analysis and calculation,it is found that the prediction accuracy is not ideal by the various classical permeability prediction models based on the capillary pres⁃sure curves,which has certain limitations.This paper analyzed the reasons for the prediction error of six classical models,selected characteristic parameters,and comprehensively considered multiple affecting factors of permeability such as pore throat size and pore throat distribution to improve prediction accuracy of permeability in ultra-tight sandstone reservoirs.On this basis,the method of leave-one-out cross-validation(LooCV)was used to determine the optimal number of latent variables in the models,and the method of partial least squares regression(PLSR)was employed to construct three predic⁃tion models for ultra-tight sandstone reservoir permeability,i.e.,Winland-r5(PLSR),Pittman(PLSR),and Swanson(PLSR).In this way,the problems of the permeability prediction models based on the ordinary least squares(OLS)method can be effectively solved,such as the multicollinearity of many characteristic parameters and the inability of small samples to generalize models.The results reveal that the three permeability prediction models based on PLSR have strong general⁃ization ability,high prediction accuracy,and good applicability in the ultra-tight sandstone reservoirs of the study area.

关 键 词：地球物理勘探 超致密砂岩 毛管压力曲线 偏最小二乘回归方法 渗透率预测 

分 类 号：TE311.2[石油与天然气工程—油气田开发工程]