Permeability Modelling In A Highly Heterogeneous Tight Carbonate Reservoir Using Comparative Evaluating Learning-based And Fitting-based Approaches

This article discusses the use of machine learning methods for reservoir property modeling, specifically focusing on the Random Forest algorithm. The algorithm is described and its application to supervised regression problems is highlighted. The importance of model selection is emphasized, as different databases may require different models for optimal performance.