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Performance Evaluation of Machine Learning Algorithms in Predicting Dew Point Pressure of Gas Condensate Reservoirs

机译：机器学习算法的性能评估预测气体冷凝水储层露点压力

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P. Ikpeka; J. Ugwu; P. Russell; G. Pillai;
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1. Evolving an accurate model based on machine learning approach for prediction of dew-point pressure in gas condensate reservoirs [J] . Seyed Mohammad Javad Majidi, Amin ShoferoIIahi, Milad Arabloo Chemical Engineering Research & Design: Transactions of the Institution of Chemical Engineers . 2014,第5期

机译：进化基于机器学习方法的精确模型以预测凝析气藏的露点压力
2. Determination of dew point pressure in gas condensate reservoirs based on a hybrid neural genetic algorithm [J] . Rabiei Arash, Sayyad Hossein, Riazi Masoud, Fluid Phase Equilibria . 2015,第Null期

机译：基于混合神经遗传算法的凝析气藏露点压力确定
3. Predicting the dew point pressure for gas condensate reservoirs: empirical models and equations of state [J] . Elsharkawy AM. Fluid Phase Equilibria . 2002,第1a2期

机译：预测凝析气藏的露点压力：经验模型和状态方程
4. Well Test Analysis in Naturally Fractured Gas Condensate Reservoirs Below Dew Point Pressure [C] . Al-Baqawi A. M, Al-Malki B. H. Deep Gas Conference and Exhibition . 2010

机译：在露点压力下的天然裂缝气体冷凝水储层中的测试分析
5. Evaluating gas injection performance in very low permeability, thick carbonate gas-condensate reservoirs to improve ultimate liquid yield. [D] . Syzdykov, Murat. 2014

机译：评估极低渗透率的厚碳酸盐气体凝析油藏的注气性能，以提高最终的液体产量。
6. Use of machine-learning algorithms to determine features of systolic blood pressure variability that predict poor outcomes in hypertensive patients [O] . Ronilda C Lacson, Bowen Baker, Harini Suresh, 2019

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7. Prediction of Dew Point Pressure in Gas Condensate Reservoirs Based On a Combination of Gene Expression Programming (GEP) and Multiple Regression Analysis [O] . El-hoshoudy AN 2018

机译：基于基因表达规划（GEP）和多元回归分析的组合对气体冷凝水储层露点压力的预测

Performance Evaluation of Machine Learning Algorithms in Predicting Dew Point Pressure of Gas Condensate Reservoirs

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