Gas Lift Optimization Under Facilities Constraints

Abstract

Abstract Gas lift optimization is often used to enhance production of mature oilfields consisting of multiple reservoirs. For efficiency, several of those reservoirs often share the same surface processing facilities. In such context, we wish to find the optimal allocation of gas lift over an entire network of wells and pipelines, while accounting for the constraints imposed by the reservoir operating conditions. In this study, we describe a novel, cost-effective approach to perform such optimizations involving non-smooth models and subject to expensive constraints that might be simulation-based and as costly to compute as the objective function. After classifying all constraints depending on their computational cost, points not satisfying simple linear constraints are feasibilized before evaluating expensive constraints. A sequential lexicographic ordering is applied in which the linear constraints take precedence over nonlinear constraints and inexpensive nonlinear constraints take precedence over expensive ones, which in turn take precedence over objective function values. Two oilfield-production optimization examples serve to demonstrate that the performance of the proposed method is much faster than the traditional ones.