Optimizing CO2 Floods Using Rate Control with Smart Wells under Geologic Uncertainty Conference Paper uri icon


  • Copyright © 2016, Society of Petroleum Engineers. Carbon dioxide flooding (continuous or WAG) is a proven and effective EOR technique resulting in improved oil recovery in various types of reservoirs. However, the complex displacement mechanisms in CO2 flooding, in particular adverse mobility and gravity segregation can reduce its effectiveness. It has been demonstrated earlier that by adjusting the well rates, we can manage the flood front and improve the sweep during waterflooding. In this paper, we present the application of rate optimization to CO2 flooding in order to maximize areal and vertical sweep, and minimize CO2 recycling by delaying CO2 breakthrough. Field-scale rate optimization problem for CO2 EOR processes involve complex reservoir models, production and facility constraints and geological uncertainty. We propose an efficient approach for computing optimal rates for CO2 flooding with application to smart wells completed with inflow control valves (ICV). The approach is based on equalizing the arrival time of flood front at the producers within a selected sub-region to maximize the areal sweep efficiency under hierarchy of production and facility constraints. An additional 'norm' constraint on the arrival times is also included to achieve high viscous-to-gravity ratio (VGR) to minimize gravity segregation. The 'optimal' strategy is decided based upon the trade-off between maximizing sweep and accelerating production. We use streamlines to compute the analytical sensitivity of arrival times with respect to injection/production rates. Analytical gradient and Hessian of the objective function are also derived, making the approach computationally efficient for fieldscale applications. The approach has been demonstrated using a synthetic 2D example and a 3D benchmark field case. The results clearly demonstrate that rate optimization can improve sweep, delay CO2 breakthrough and increase oil recovery for the same amount of CO2 injection. In addition, we demonstrate the potential of our approach for WAG flooding in the 3D benchmark field case. We incorporate geological uncertainty via a stochastic optimization framework based on the combination of the expected value and variance of a performance measure from multiple realizations.

author list (cited authors)

  • Sharma, M., Taware, S. V., & Datta-Gupta, A.

citation count

  • 1

publication date

  • November 2015