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.
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.
This Month’s Technical Papers
Recommended Additional Reading
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.
Reza Fassihi, SPE, is the founder of Beyond Carbon. Before starting his company, he was a distinguished adviser emeritus with BHP Billiton, where his primary responsibilities included technical assurance, competency development within the company, identification and development of emerging technology, and provision of technological advice to senior management. Fassihi was a technical liaison for joint-industry projects on carbon dioxide sequestration, alternative energy including geothermal, and innovative technologies for mineral extraction. He has more than 41 years of experience in petroleum research, development, and management of both conventional and unconventional reservoirs. Before joining BHP Billiton, Fassihi worked with Arco, Amoco, and BP. He has served as a member of several SPE committees, including the 2022 IOR Technical Program Committee, the steering committee for SPE Forums, and the SPE Reservoir Description and Dynamics Advisory Committee. Fassihi was an SPE Distinguished Lecturer in 2003. He is an executive editor for the SPE Journal Editorial Board and was named an SPE Distinguished Member in 2018. Fassihi has published more than 45 peer-reviewed papers and is the author of the SPE monograph Low-Energy Processes for Unconventional Oil Recovery.