A streamline-based production optimization method for waterflooding reservoirs.

Area of Science:

• Petroleum Engineering
• Reservoir Engineering
• Computational Geoscience

Background:

• Waterflooding is a key secondary oil recovery technique in sandstone and carbonate reservoirs.
• Challenges include premature water breakthrough, increased water cut, and limited operational flexibility due to geological complexity.
• Optimization is crucial for enhancing oil recovery and managing water production.

Purpose of the Study:

• To develop a novel production optimization methodology for waterflooding using streamline simulation.
• Introduce two new metrics: real-time streamline revenue (RTSR) and well-pair revenue efficiency.
• Improve oil recovery and control water production through optimized injection-production schedules.

Main Methods:

• Leveraging streamline simulation for flow diagnostics.
• Developing and applying the real-time streamline revenue (RTSR) metric.
• Integrating RTSR with rate optimization criteria for scheduling.

Main Results:

• Synthetic case: 29.42% NPV increase, 26.88% oil production rise, 8.60% water reduction.
• Field-scale Reservoir M: 20.80% higher NPV, 20.41% more oil, 72.69% less water.
• The RTSR-based method outperforms existing streamline approaches.

Conclusions:

• The RTSR-based methodology effectively optimizes injection-production schedules for enhanced oil recovery.
• This approach significantly improves economic performance and reduces water production in waterflooding operations.
• Future work may involve advanced optimization algorithms and integrated reservoir management strategies.