Segment 1: Introduction to the Digital Oilfield 2.0
• A review of the objectives and results from the digital oilfield since 2000 and a discussion of what is new today (lower for much longer oil prices and emerging digital technologies)
• Convergence of OT (operational technology) and IT (information technology) systems. From sensors and control systems (SCADA), to remote decision support environments, to workflow automation, to process optimization
• The Industrial Internet of Things and Big Data Analytics for oil and gas, The search for the digital core and the five stages of digitization in oil and gas
Segment 2: Review of data analytics techniques, data management infrastructure, programming and technologies, artificial intelligence and machine learning
• Understanding of the data foundation for typical oil and gas exploration and production functions, data federation, data integration challenges, data modeling
• Review of often used analytical techniques (regression analysis, neural networks, machine learning, deep learning)
• Review of Business Intelligence (reporting), Data Visualization (dashboards, data story telling) and Artificial Intelligence approaches, the strengths and weaknesses of each.
Segment 3: Application of petroleum data analytics to upstream oil and gas used cases
• Information Intensity in Oil & Gas / Beyond Surveillance and Monitoring/ Digital Twin. Review of a practical use cases for oil and gas (predictive analytics for critical equipment, use of analytics to drill complex wellbores, optimization of completion techniques for unconventional reservoirs
• Application of cyber security issues to the digital oilfield
• System Challenges and Barriers to Adoption, what oil and gas can learn from other industries
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