Design of an Expandable Base Pipe Using a Genetic Algorithm-Based Multi-Objective Optimization Method

Perforated base pipe is an important component in a completion system. Field applications dictate that a good perforated base-pipe design should have good expandability and good post-expansion tensile strength and collapse strength. High fidelity FEA models for evaluation of expandable base pipes have been developed; however, to optimize hole pattern design (size, shape, placement pattern) of a given size base pipe, even numerically, can be expensive and time consuming. Using FEA models and a genetic algorithm-based multi-objective optimization scheme, the authors have successfully optimized a perforated base pipe in a relatively short period of time. The significant improvement over standard design has been demonstrated by physical tests. Several aspects of the optimization process will be presented in this paper.