A streamline-based production optimization method for waterflooding reservoirs

Waterflooding, the predominant secondary recovery method in global sandstone and carbonate reservoirs, faces challenges including premature water breakthroughs, rapid water cut rise, limited well pattern adjustments and restricted stimulation treatments due to complex geological constraints. This demands enhanced optimization techniques. Leveraging streamline simulation's flow diagnostic capabilities, this study introduces two novel metrics: "real-time streamline revenue" (RTSR), quantifying the economic effectiveness via flux, time of flight and saturation data integration along streamlines, and "well-pair revenue efficiency" for injection-production unit characterization. Integrating corresponding rate optimization criteria, we develop an RTSR-based production optimization methodology which enables rapid generation of optimal injection-production schedules, improving recovery while controlling water production. Validation using synthetic and field-scale models (Reservoir M) demonstrated significant improvements by the proposed method: Synthetic case achieved 29.42% NPV increase, 26.88% oil production rise, and 8.60% water reduction compared to the base schedule; Reservoir M yielded 20.80% higher NPV, 20.41% more oil, and 72.69% less water. The approach outperforms existing streamline methods, proving effective for stabilizing/enhancing oil production and reducing water cut. Future work can refine weighting functions within optimization criteria using surrogate-optimization algorithms and extend the framework to integrate layer series, well patterns, or well placement with injection-production control.