In the S Field described in the complete paper, a major control mechanism applied to optimize waterflooded reservoirs is controlling the water injection and pumping rates of producers. The reservoir surveillance team has been using a simple, spreadsheet-based analytical approach that proved limiting as the number of injection patterns increased. The complete paper presents various innovations in bringing real applications of artificial intelligence (AI) for waterflooding management. The AI-based solution combines cloud technologies, data processing, data analytics, machine-learning algorithms, robotics, sensor and monitoring systems, automation, edge gateways, and augmented and virtual reality.
Application of AI to Waterflood-Performance Management
The authors devote a subsection of the complete paper to a description of a process they term “Design Thinking.” The main steps in the Design Thinking process are discover, define, ideate, experiment, build prototype, and test.
