Development of an Intelligent Oil Field Management System based on Digital Twin and Machine Learning
Tasmurzayev N. Amangeldy B. Nurakhov Y. Shinassylov S. Bekele S.D.
2023World Scientific and Engineering Academy and Society
WSEAS Transactions on Electronics
2023#14104 - 111 pp.
This article introduces an innovative approach to oil field management using digital twin technology and machine learning. A detailed experimental setup was designed using oil displacement techniques, equipped with sensors, actuators, flow meters, and solenoid valves. The experiments focused on displacing oil using water, polymer, and oil, from which valuable data was gathered. This data was pivotal in crafting a digital twin model of the oil field. Utilizing the digital twin, ML algorithms were trained to predict oil production rates, detect potential equipment malfunctions, and prevent operational issues. Our findings highlight a notable 10-15% improvement in oil production efficiency, underscoring the transformative potential of merging DT and ML in the petroleum industry.
Artificial Neural Networks , Digital Twin , Energy Efficiency , Industrial Internet of Things , Intelligent Control System , Machine learning , Oil displacement , SCADA , Sensor Network
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