درباره تعیین دقیق از خواص PVT در سیستم های نفت خام:روش مدل سازی سیستم هوشمند ماشین کمیته

This study is focused on accurate determination of PVT properties of reservoir oil using an ensemble approach referred to as committee machine intelligent system. PVT properties of interest are oil formation volume factor (Bo) and bubble point pressure (Pb). Committee machine intelligent system model developed in this work combine multi-layer perceptron network, radial basis function network, and least squares support vector machine via a modified weighted averaging method, while optimizing these weights using genetic algorithm. Developed committee machine intelligent system model was found to accord excellently with experimental data yielding correlation coefficients (R2) of 0.980 and 0.976 for bubble point pressure (Pb), and oil formation volume factor (Bo), respectively. Comprehensive comparisons were also carried out between a variety of PVT prediction models and committee machine intelligent system model developed in this study. At the end, leverage value statistics method was applied to detect and identify some probable outlying points from the gathered databases.