Abstract
AbstractThrough analyzing the integrated oil and gas production process, a multi‐objective optimization model for the integrated oil and gas production process is established through considering nonlinear reservoir behaviour, multiphase flow in wells, and constraints from the surface facilities. In order to reduce the influence of model parameter uncertainty in the oil and gas production process, an error compensation method based on the Gaussian mixture model (GMM) is proposed to compensate the model. Non‐ dominated sorting genetic algorithm‐II (NSGA‐II) is used as the optimization algorithm. Moreover, an operational strategy using post‐ optimization is applied to solve the optimization model, so as to ensure the feasibility of the obtained optimal set‐point. Finally, a novel optimization approach for the oil and gas production process considering model parameter uncertainty is proposed. Simulation results indicate that the proposed optimization method is feasible and effective.
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 callDisclaimer: 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.
