Optimal Waterflood Management Under Geologic Uncertainty Using Rate Control: Theory and Field Applications

Abstract

Waterflood optimization via rate control is receiving increased interest because of rapid developments in the smart well completions and I-field technology. The use of inflow control valves (ICV) allows us to optimize the production/injection rates of various segments along the wellbore, thereby maximizing sweep efficiency and delaying water breakthrough. It is well recognized that field scale rate optimization problems are difficult because they often involve highly complex reservoir models, production and facilities related constraints and a large number of unknowns. Some aspects of the optimization problem have been studied before using mainly optimal control theory.However, the applications to-date have been limited to rather small problems because of the computation time and the complexities associated with the formulation and solution of adjoint equations. Field-scale rate optimization for maximizing waterflood sweep efficiency under realistic field conditions has still remained largely unexplored.We propose a practical and efficient approach for computing optimal injection and production rates and thereby manage the waterflood front to maximize sweep efficiency and delay the arrival time to minimize water cycling. Our work relies on equalizing the arrival times of the waterfront at all producers within selected sub-regions of a water flood project. The arrival time optimization has favorable quasi-linear properties and the optimization proceeds smoothly even if our initial conditions are far from the solution. We account for geologic uncertainty using two optimization schemes.The first one is to formulate the objective function in a stochastic form which relies on a combination of expected value and standard deviation combined with a risk attitude iv coefficient. The second one is to minimize the worst case scenario using a min-max problem formulation. The optimization is performed under operational and facility constraints using a sequential quadratic programming approach. A major advantage of our approach is the analytical computation of the gradient and Hessian of the objective which makes it computationally efficient and suitable for large field cases.Multiple examples are presented to support the robustness and efficiency of the proposed optimization scheme. These include several 2D synthetic examples for validation purposes and 3D field applications.

Optimum design of CO2 storage and oil recovery under geological uncertainty

“…Gharbi [26] presented an EOR expert approach to optimize reservoir management and CO 2 floods in carbonate reservoirs. Several studies have focused on optimizing NPV of EOR projects under uncertainty [27][28][29]. These studies only focused on optimizing oil recovery rather than CO 2 storage.…”

Dimethyl Ether Enhanced Oil Recovery in Fractured Reservoirs and Aspects of Phase Behavior

“…It is worth noting that at least half of the world’s oil reserves occur in carbonate reservoirs , with many of them being highly fractured or heterogeneous with complex pore systems. Fractures provide high permeability pathways in a usually low permeability matrix of carbonate rocks. Waterflooding such reservoirs often leads to several issues such as low sweep efficiency of the matrix block and water management difficulties. − Fractures establish high permeability conduits from the injector to producer, which shortens the water retention time in the reservoir; hence, a large portion of the reservoir may remain unswept by the injected water. Moreover, the early breakthrough of the injected water leads to an undesirably high water cut, which creates technical and economic challenges.…”