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One of the main challenges in the oil industry is to optimize production while reducing the development cost and maximizing reserves. Real-time optimization has been gaining ground to effectively face the challenge, and it has been applied in the Smart field or Digital field technology. Literature references two optimization loops, the reservoir- centric slow loop and the well-centric fast loop. Intelligent wells are focused on the fast loop and combine well-centric technologies with monitoring, data analysis, modeling, interpretation and automation to accelerate production, maximize recovery and reduce operating and capital expenditure cost. Their benefits include increased ultimate recovery, accelerated production and cost reduction. Intelligent well equipment can include intelligent completion system, artificial lift system, and automated chemical injection system.
Information regarding the optimal intelligent equipment configuration for a well at various points in its life requires the convergence of multiple talents pools. It is discovered in the well design process but it is unreasonable to expect all the relevant talent to be available during actual well operations. As a result, the well may not optimize production or add the value that was expected unless the knowledge is captured and used to assist making optimization decisions in real time. This knowledge is the linked to improved use of the data that is recorded and transmitted by downhole and surface sensors. Instead of closing the loop by human intervention, an intelligent optimization system will link stored knowledge to measurements. This will change the optimization activities from polling to interrupt-driven, and will advise when wells deviate from their expected behavior in ways that prompt diagnosis of problems early enough to avoid them.
This paper presents the technologies and capabilities come together to achieve intelligent optimization system.