Real-time monitoring and predictive analytics are transforming digital twin & smart oilfields for sustainable operations, improving efficiency and reducing environmental impact. Digital twin technology integrates AI, IoT, and cloud computing to create virtual replicas of oilfield assets, enabling predictive maintenance and optimized production planning. Smart oilfields utilize automated data collection from sensors and drones to enhance safety and reduce downtime. AI-driven analytics are identifying energy savings and emission reduction opportunities. The increasing reliance on real-time data and machine learning is streamlining decision-making. By enhancing asset performance and minimizing operational risks, digitalization is ensuring the long-term sustainability of hydrocarbon production.
Selim Sanad Shaker
Geopressure Analysis Services, United States
John W Sheffield
Purdue University, United States
Michael Radicone
Heat Transfer Research, Inc, United States
William Gothard
Ahmic Aerospace, United States
Guido Gabriel Piccone
ADNOC Onshore, United Arab Emirates
Andrey Yugay
ADNOC Onshore, United Arab Emirates
Pranay Asthana
Saudi Aramco, Saudi ArabiaSubmit your abstract Today
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