A Mixed-Integer convex formulation for production optimization of gas-lifted oil fields with routing and pressure constraints
AUTOR(ES)
Aguiar, M. A. S., Camponogara, E., Silva, T. L.
FONTE
Braz. J. Chem. Eng.
DATA DE PUBLICAÇÃO
2014-06
RESUMO
Production optimization of gas-lifted oil fields under facility, routing, and pressure constraints has attracted the attention of researchers and practitioners for its scientific challenges and economic impact. The available methods fall into one of two categories: nonlinear or piecewise-linear approaches. The nonlinear methods optimize simulation models directly or use surrogates obtained by curve fitting. The piecewise-linear methods represent the nonlinear functions using a convex combination of sample points, thereby generating a Mixed-Integer Linear Programming (MILP) problem. The nonlinear methods rely on compact models, but can get stuck in local minima, whereas the piecewise-linear methods can reach globally optimal solutions, but their models tend to get very large. This work combines these methods, whereby piecewise-linear models are used to approximate production functions, which are then composed with convex-quadratic models that approximate pressure drops. The end result is a Mixed-Integer Convex Programming (MICP) problem which is more compact than the MILP model and for which globally optimal solutions can be reached.
Documentos Relacionados
- Application of mixed-integer linear programming in a car seats assembling process
- GLOBAL OPTIMIZATION OF THE LOCATION, TOPOLOGY AND CAPACITY OF A TRANSMISSION NETWORK: A MIXED-INTEGER NON-LINEAR PROGRAMMING APPROACH
- Integer linear models with a polynomial number of variables and constraints for some classical combinatorial optimization problems
- A Heuristic Algorithm Based on Line-up Competition and Generalized Pattern Search for Solving Integer and Mixed Integer Non-linear Optimization Problems
- OPTIMIZATION OF DEMULSIFIER FORMULATION FOR SEPARATION OF WATER FROM CRUDE OIL EMULSIONS