A Mixed-Integer Linear Programming Model for the Station Capacity Allocation Problem of a Star-Tree Pipe Network

Abstract

The optimization of the layout of the surface gathering and transportation pipe network in the oil and gas field can effectively reduce the total investment in the pipe network. Currently, based on the constraints of fixed station capacity in the star-tree pipe network topology, hierarchical optimization strategies are often used to optimize the pipe network layout. Aiming at the overall optimization of the layout of the star-tree ground gathering and transportation pipe network, this paper constructs a special mixed-integer linear programming (MILP) mathematical model considering the station capacity allocation problem, which can simultaneously obtain the optimal pipe network topology, pipe connection relationship, station location and quantity, station type, central station [central processing plant (CPP)] location and investment of each part. Numerical analysis of gas fields of different scales is used to discuss the influence of station capacity allocation and different station capacity combinations on the optimization of pipe network layout. The optimization effect of star-tree and star-star pipe network layout is compared and analyzed. The results not only prove the correctness and effectiveness of the model and algorithm proposed in this paper but also reduce the total investment of the pipe network. It can be seen that the optimization scheme has guiding significance for the surface engineering construction of the oil and gas fields.