经典渗透率预测模型的物理意义和改进方法OA

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.