Data-driven decision-making is reshaping artificial intelligence & big data analytics in oil & gas, optimizing operations and minimizing environmental impact. Machine learning algorithms are enhancing seismic data interpretation, improving reservoir management, and predicting equipment failures before breakdowns occur. Predictive analytics is reducing downtime in refineries and drilling operations, while AI-driven process control is improving efficiency and reducing energy consumption. Big data integration is facilitating real-time monitoring of pipelines and offshore platforms, ensuring safety and regulatory compliance. The integration of cloud computing and edge analytics is further enhancing operational efficiency. AI-based automation is expected to play a pivotal role in optimizing oilfield production while reducing emissions.
Anthony J Sadar
Environmental Science Communication, LLC, United States
Selim Sanad Shaker
Geopressure Analysis Services, United States
Sharma Dronamraju
AKD Professional Solutions Inc., United States
Ross Cygan Taylor
North Sea Transition Authority, United Kingdom
Saleh Alqahtani
Saudi Aramco, Saudi Arabia
Abdulrahman Bahashwan
Saudi Aramco, Saudi Arabia
Ganesh Markad
Proclink Consulting, IndiaSubmit your abstract Today
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