Abstract
Gas lift is one of the most widespread methods of artificial lift technologies used when wells' production rate declines. Gas is employed to maintain the production by injecting gas into the tubing through a gas lift orifice. Lifting costs are generally low. However, capital costs of compression are very high, so it is necessary to optimise gas lift wells. In this paper, conventional nodal analysis models were used to predict the optimisation parameters based on wells system parameters. Artificial neural network (ANN) models were also used based on gas lift databases. ANN models were trained then tested against nodal analysis models. Also, this paper presents a new theory about the relative importance of gas lift system inputs on output parameters of gas lift system. [Received: June 9, 2020; Accepted: August 7, 2020]
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Oil, Gas and Coal Technology
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
