A continuous-time-based MILP model for production and transportation scheduling in nonpipelined wells in low-permeability oil fields

The marginal wells in low-permeability oilfields are characterized by small storage size, scattered distribution, large regional span, low production, intermittent production, etc. The production mode of these wells is nonpipeline mode. In our previous work (Zhang et al., 2019), a novel mixed-integer linear programming (MILP) model using a discrete-time representation was presented for the operation scheduling of nonpipelined wells. However, too many discretization time points are required to ensure the accuracy of the model. Even for moderately sized problems, computationally intractable models can arise. The present paper describes a new continuous-time representation method to reformulate this schedule optimization problem. By introducing the continuous-time representation, the binary variables are largely reduced. The solution effect for different model sizes is also investigated. When the model size increases to a certain degree, a feasible solution cannot be obtained within a limited time. The results of a case study originated from a real oilfield in China show that the continuous-time model requires less time to obtain the optimal solution compared to the discrete-time model. In details, considering a same scale problem, the solution based on the continuous-time model saves 52.25% of the time comparing with the discrete-time model. The comparison validates the new model's superiority.