Through 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 optimizationis 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.