Abstract

Among the different enhanced-oil-recover techniques, waterflooding is still commonly practiced in part because of its economic potential. During the past 2 years, many papers presented at SPE meetings have dealt with different aspects of waterflooding design, optimization, monitoring, and low-salinity applications. Understanding the injected-water preferential paths is a key aspect of waterflood optimization in reservoirs characterized by strong vertical and areal heterogeneities. Devising specific work flows for such applications is important. These can be easy but powerful tools for visualizing the complex dynamic connections between injectors/producers and aquifer influence areas. They can enable improving the business-time decision-making cycle, resulting in increased operational performance and lower waterflood operating costs by consolidating end-to-end optimization work flows in one platform. Using artificial intelligence (AI) and machine-learning (ML) approaches with reduced-physics models can reduce the time required for this task. Also, ML allows for fast screening of waterflood performance at diverse levels (e.g., reservoir, sector, pattern, and well), enabling prompt identification of opportunities for immediate uptake into an opportunity-management process and for evaluation in AI-driven production forecasting or in a reservoir simulator. As part of waterflood optimization, changing the chemistry of the injected water has been under investigation since early 2000. This process has been named differently in different laboratories (e.g., smart water and low-salinity waterflooding, or LoSal). The new studies are related to its field application. It is interesting that new hybrid applications such as low-salinity water with surfactant flooding and carbonated smart water injection are showing up in the literature. As we move forward, it is expected that the waterflooding recovery factor will increase with additional technology advancements. Recommended additional reading at OnePetro: www.onepetro.org SPE 209426 - Impact of Brine Chemistry on Waterflood Oil Recovery: Experimental Evaluation and Recovery Mechanisms by Behdad Aminzadeh, Chevron, et al. SPE 205426 - Pump Up the Volume—Massive Water-Injection Increase Through Open-Water Stimulations by Alistair Roy, BP, et al. SPE 210154 - Middle East Giant Carbonate Field: Integrated Water-Injection-Optimization Work Flow by Stefano Del Fraro, Eni, et al.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call