Robust Scheduling Optimization For Production And Transportation Of Large-scale Non-pipelined Wells

China’s low-permeability oil fields are widely distributed,with geological reserves accounting for about half of the country’s proven geological reserves,but the average recovery rate is only 21.4%.The marginal oil wells in low-permeability fields are characterized by small storage size,scattered distribution,large regional span,low production,intermittent production,etc.The construction of large-scale gathering pipelines has high investment,high operation cost and low economic efficiency,so most of them adopt non-pipelined production and transportation method of single-pull tank.At present,crude oil production and transportation scheduling schemes mainly rely on manual development,with poor synergy,which seriously restricts the release of production capacity and the reduction of transportation cost.At the same time,a large number of uncertainties exist in the process of crude oil production and transportation,which makes the optimal scheduling performance indexes obtained from various deterministic models and methods reduced or even infeasible.Therefore,how to coordinate the crude oil production and transportation process,take uncertainties into account,optimize the transportation mode and well operation parameters,and form an optimal production and transportation scheduling scheme is crucial to increase crude oil production,reduce transportation cost,and improve enterprise efficiency.Based on this,this paper proposes the use of computer-aided cooperative scheduling optimization of crude oil production process and tank truck transportation process for the non-pipelined wells.The main research contents of the paper are as follows.(1)To address the problem of collaborative scheduling optimization of nonpipelined crude oil production and transportation process,this paper analyzes the production constraints in the production process and the scheduling constraints and time constraints in the transportation process,and firstly establish a MINLP model based on continuous time description.A case study of the model was conducted in a scenario with multiple vehicle types and tank capacities.The accurate description of the above process model provides a solid foundation for constructing a robust scheduling model considering uncertainty,and also provides feasibility for implementing computer-aided scheduling decisions for the production and transportation process of non-pipelined wells.(2)To address the uncertainties in the production and transportation process of nonpipelined wells,this paper considers the uncertainty of production rate in the process of production and the uncertainty of travel time of tank trucks in the process of transportation,and obtain the ellipsoidal uncertain set by processing and analyzing the production rate and travel time data,and then establish the corresponding robust scheduling optimization model,and finally verify it by a case study.(3)Since the robust scheduling optimization problem for production and transportation of large-scale non-pipelined wells is difficult to be solved by classical algorithms,this paper proposes an improved particle swarm algorithm.Because the inertia weight factor is fixed,the standard particle swarm algorithm cannot balance its global and local search ability.In the improved particle swarm algorithm proposed in this paper,the inertia weight factor is set to be updated adaptively according to the iterations by considering the change of the fitness function value.It is concluded from the case study that the improved particle swarm algorithm gives full play to the global search capability in the early stage and the local search capability in the late stage.In addition,the improved particle swarm algorithm can improve the solution efficiency.