测井技术2026，Vol.50Issue(1)：75-86,12.DOI:10.16489/j.issn.1004-1338.2026.01.007
经典渗透率预测模型的物理意义和改进方法
Physical Significance and Improvement Methods of the Classic Permeability Model
摘要
Abstract
Permeability is a key parameter characterizing the fluid flow capacity in porous media and has significant application value in fields such as oil and gas exploration and development,and carbon dioxide geological storage.However,the complexity of the pore structure in reservoir rocks poses a huge challenge to the accurate prediction of permeability.Taking the Winland model as the core research object,this paper systematically reviews its development process,analyzes the differences between it and models such as Pittman and Swanson,explores the key factors affecting its prediction accuracy,and proposes targeted improvement methods and verifies them through experiments and data.The research results show that:① The core parameter of the Winland model is the throat radius r35 corresponding to the mercury injection saturation of 35%,which later developed into a multiple linear regression model.The optimal throat radius parameters vary for different reservoirs.For example,r30 corresponding to the mercury injection saturation of 30%is more suitable for tight sandstone reservoirs,while r40 and r45 corresponding to the mercury injection saturation of 40% and 45% are more suitable for carbonate reservoirs.② The prediction accuracy of the model is affected by the experimental dependence of the throat parameters,the heterogeneity of the reservoir,and diagenetic processes.In the low-permeability range of 0.1 to 1.0 mD,there is a tendency for the calculated values to be lower than the measured values.③ By introducing percolation theory and combining CT scanning and nuclear magnetic resonance technology,a multi-modal seepage and diagenetic correction system for fractures and cavities can be constructed,which can effectively improve the model's adaptability.④ An improved model based on the random forest algorithm and the fusion of multi-source logging data has a determination coefficient R2 of 0.76 for permeability prediction in the test set,which is significantly better than the traditional Winland model(R2=0.48).The conclusion is that the Winland model characterizes rock permeability through the statistical characteristics of throat size,and its improvement should focus on the dynamic optimization of core parameters,the correction of complex reservoir conditions,and the fusion of multi-source data.In the future,it should deeply integrate multiple regression and percolation theory to construct a"data-physical"dual-driven high-precision permeability prediction system.关键词
渗透率/Winland模型/孔隙结构/逾渗理论/多元回归/机器学习/致密砂岩/随机森林Key words
permeability/Winland model/pore structure/percolation theory/multiple regression/machine learning/tight sandstone/random forest分类
天文与地球科学引用本文复制引用
董旭,石雪莹,刘粤蛟,柳波,杨仁杰,石颖,张东晨..经典渗透率预测模型的物理意义和改进方法[J].测井技术,2026,50(1):75-86,12.基金项目
国家自然科学基金项目"流体赋存状态影响回注气高效动用页岩油机理研究"(42204131) （42204131）
国家自然科学基金项目"松辽盆地古龙页岩地震岩石物理响应机理研究"(42274173) （42274173）
国家科技重大专项课题"煤岩气富集规律与地质工程甜点评价"(2025ZD1404202) （2025ZD1404202）
黑龙江省优秀青年基金项目"CO2-油-水耦合作用下的古龙页岩油动用规律研究"(YQ2023D004) （YQ2023D004）
