Global Optimization of Gas Allocation to a Group of Wells in Artificial Lift Using Nonlinear Constrained Programming

Abstract

Continuous flow gas lift is one of the most common artificial lift methods widely used in the oil industry. A continuous volume of high-pressure gas is injected as deep as possible into the tubing, to gasify the oil column, and thus facilitate the production. If there is no restriction in the amount of injection gas available, sufficient gas can be injected into each oil well to reach maximum production. However, the injection gas available is generally insufficient. An inefficient gas allocation in a field with limited gas supply reduces the revenues, since excessive gas injection is expensive due to the high gas prices and compressing costs. Therefore, it is necessary to assign the injection gas into each well in optimal form to obtain the field maximum oil production rate. The gas allocation optimization can be considered as a maximization of a nonlinear function, which models the total oil production rate for a group of wells. The variables or unknowns for this function are the gas injection rates for each well, which are subject to physical restrictions. In this work a nonlinear optimization technique, based on an objective function with constraints, was implemented to find the optimal gas injection rates. A new mathematical fit to the gas-lift performance curve (GLPC) is presented and the numeric results of the optimization are given and compared with those of other methods published in the specialized literature. The GLPC can be either measured in the field, or alternatively generated by computer simulations, by mean of nodal analysis. The optimization technique proved fast convergence and broad application.