SCI和EI收录∣中国化工学会会刊

›› 2016, Vol. 24 ›› Issue (10): 1423-1430.doi: 10.1016/j.cjche.2016.04.050

• Process Systems Engineering and Process Safety • 上一篇    下一篇

Modeling and optimization for oil well production scheduling

Jin Lang1,2, Jiao Zhao3   

  1. 1 The Institute of Industrial Engineering and Logistics Optimization, Northeastern University, Shenyang, 110819, China;
    2 State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819, China;
    3 School of Automobile, Chang'an University, Xi'an 710064, China
  • 收稿日期:2015-06-16 修回日期:2015-11-29 出版日期:2016-10-28 发布日期:2016-11-19
  • 通讯作者: Jin Lang,E-mail address:langjin@ise.neu.edu.cn. E-mail:langjin@ise.neu.edu.cn
  • 基金资助:
    Supported by National High Technology Research and Development Programof China (2013AA040704) and the Fund for the National Natural Science Foundation of China (61374203).

Modeling and optimization for oil well production scheduling

Jin Lang1,2, Jiao Zhao3   

  1. 1 The Institute of Industrial Engineering and Logistics Optimization, Northeastern University, Shenyang, 110819, China;
    2 State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819, China;
    3 School of Automobile, Chang'an University, Xi'an 710064, China
  • Received:2015-06-16 Revised:2015-11-29 Online:2016-10-28 Published:2016-11-19
  • Supported by:
    Supported by National High Technology Research and Development Programof China (2013AA040704) and the Fund for the National Natural Science Foundation of China (61374203).

摘要: In this paper, an oil well production scheduling problem for the light load oil well during petroleum field exploitation was studied. The oil well production scheduling was to determine the turn on/off status and oil flow rates of thewells in a given oil reservoir, subject to a number of constraints such as minimumup/down time limits and well grouping. The problem was formulated as a mixed integer nonlinear programming model that minimized the total production operating cost and start-up cost. Due to the NP-hardness of the problem, an improved particle swarm optimization (PSO) algorithm with a new velocity updating formula was developed to solve the problemapproximately. Computational experiments on randomly generated instanceswere carried out to evaluate the performance of the model and the algorithm's effectiveness. Compared with the commercial solver CPLEX, the improved PSO can obtain high-quality schedules within a much shorter running time for all the instances.

关键词: Oil well production, Scheduling, Mixed integer nonlinear programming, (MINLP), Improved particle swarm optimization

Abstract: In this paper, an oil well production scheduling problem for the light load oil well during petroleum field exploitation was studied. The oil well production scheduling was to determine the turn on/off status and oil flow rates of thewells in a given oil reservoir, subject to a number of constraints such as minimumup/down time limits and well grouping. The problem was formulated as a mixed integer nonlinear programming model that minimized the total production operating cost and start-up cost. Due to the NP-hardness of the problem, an improved particle swarm optimization (PSO) algorithm with a new velocity updating formula was developed to solve the problemapproximately. Computational experiments on randomly generated instanceswere carried out to evaluate the performance of the model and the algorithm's effectiveness. Compared with the commercial solver CPLEX, the improved PSO can obtain high-quality schedules within a much shorter running time for all the instances.

Key words: Oil well production, Scheduling, Mixed integer nonlinear programming, (MINLP), Improved particle swarm optimization