Oil production optimization - A piecewise linear model, solved with two decomposition strategies

This paper presents a new method for real-time optimization of process systems with a decentralized structure where the idea is to improve computational efficiency and transparency of a solution. The contribution lies in the application and assessment of the Lagrange relaxation and the Dantzig–Wolfe methods, which allows us to efficiently decompose a real-time optimization problem. Furthermore, all eywords: il production planning iecewise linearization ixed integer linear programming agrangian decomposition nonlinearities are modeled by piecewise linear models, resulting in amixed integer linear program, with the added benefit that error bounds on the solution can be computed. Themerits of themethod are studied by applying it to a semi-realistic model of the Troll west oil rim, a petroleum assetwith severe production optimization challenges due to rate dependent gas-coningwells. This study indicates thatboth theLagrange relaxationand inparticular theDantzig–Wolfe approachoffers an interesting option for complex production systems. Moreover, the method compares favorably with thod. antzig–Wolfe decomposition the non-decomposed me