OPTIMIZING VOLUMETRIC SWEEP EFFICIENCY IN WATERFLOODS BY INTEGRATING STREAMLINES, DESIGN OF EXPERIMENTS, AND HYDROCARBON F PHI CURVES

Waterflooding is by far the most commonly used method to improve oil recovery. Success of a waterflood depends on its ability to sweep remaining oil efficiently. Incorrect or insufficient design may lead to increases in cost associated with water cycling and poor sweep. Most waterflood management is restricted to classical surveillance methods or sensitivity studies centered on finite difference simulation. Classical surveillance methods fail to account for subsurface heterogeneity, while optimizing sweep via conventional modeling is time consuming in big waterfloods with large number of wells or a relatively high‑resolution numerical grid. We propose a practical and efficient approach for rapid and full‑field optimization of waterfloods. Our method focuses on optimizing volumetric sweep efficiency using streamlines. We introduce two new concepts: the Hydrocarbon F‑Phi Curve and Dynamic Lorenz Coefficient (DLC). We show that these concepts can be easily derived from streamline simulation and can be used for optimum waterflood management. The DLC serves as a unique measure of the flow ‑ or dynamic ‑ heterogeneity, and we show that minimizing DLC results in optimal volumetric sweep efficiency. The method is straightforward: we evaluate the sensitivity of DLC to variations in operating conditions in a design of experiment (DoE) study, and then select the conditions that minimize DLC. The main advantages of our method are its speed, flexibility to start optimizing at any arbitrary time regardless of the history, and ability to handle large problems. The new approach requires running a streamline simulator only a few time steps, so multi‑million cell models are optimized in minutes. We verified our approach with several synthetic examples. These examples showed that a 1,000,000 cell, complex reservoir with 13 wells, and 29 completions can be optimized in less than 45 minutes. Finally, a field application validates our approach.