Optimal Strategies for Carbon Dioxide Enhanced Oil Recovery under Uncertainty

DEMIAN J. PRESSER; VANINA G. CAFARO; MIGUEL A. ZAMARRIPA; DIEGO C. CAFARO

13TH INTERNATIONAL SYMPOSIUM ON PROCESS SYSTEMS ENGINEERING

Elsevier

Año: 2018; p. 1507 - 1512

This work presents a two-stage stochastic programming model to optimize the expectednet present value (ENPV) of CO2-EOR projects under uncertainty. The mathematicalformulation relies on a multi-period planning approach aimed to find the optimalexploitation strategy for a mature oil reservoir. Given uncertain prices and productivityscenarios, the model sets the most convenient time to launch the CO2-EOR project, andestablishes efficient operating conditions over the planning horizon. It determines thenumber of production and injection wells to operate at every period, the CO2 injectionrate in every well, and the timing for maintenance and conversion tasks. The problemcomplexity grows rapidly with the number of wells and scenarios considered, resultingin a large-scale decision-making problem. Well productivity forecast functions arenonlinear (typically hyperbolic), yielding a mixed integer nonlinear (MINLP),nonconvex formulation. A moving horizon framework is adopted to take recourseactions when uncertain production parameters are revealed. The proposed approachhelps operators to increase CO2-EOR profitability by minimizing losses in low-priceand productivity scenarios and maximizing the gain under more promising conditions.