WSEAS Transactions on Electronics
Print ISSN: 1109-9445, E-ISSN: 2415-1513
Volume 14, 2023
Development of an Intelligent Oil Field Management System based on Digital Twin and Machine Learning
Authors: , , , ,
Abstract: 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.
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Keywords: Digital Twin, Machine learning, Artificial Neural Networks, Oil displacement, Intelligent Control System, Industrial Internet of Things, Sensor Network, SCADA, Energy Efficiency
Pages: 104-111
DOI: 10.37394/232017.2023.14.12