Robust hybrid machine learning algorithms for gas flow rates prediction through wellhead chokes in gas condensate fields

Abouzar Rajabi Behesht Abad,Hamzeh Ghorbani,Nima Mohamadian,Shadfar Davoodi,Mohammad Mehrad,Saeed Khezerloo-Ye Aghdam,Hamid Reza Nasriani

Fuel（2022）

Cited 33|Views4

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Abstract

•1009 record date of from the Iranian condensate fields (Marun-Khami, Aghajari-Khami and Ahvaz-Khami).•New hybrid machine learning technique accurately predicts gas flow rate through wellhead choke in gas condensate reservoirs.•MELM-PSO model constructs the most accurate condensate gas flow rate predictions.•Choke size (D64), downstream pressure (Pd) and gas liquid ratio (GLR) have the greatest influence.

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Key words

Gas flow rate,Multi-hidden layer extreme learning machine,Hybrid machine learning algorithms,Least squares support vector machine,Wellhead choke

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