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|12/1/2023||5 Days||7350 AED||Dubai, United Arab Emirates||Register|
|11/1/2023||5 Days||7350 AED||Dubai, United Arab Emirates||Register|
|10/1/2023||5 Days||7350 AED||Dubai, United Arab Emirates||Register|
|9/1/2023||5 Days||7350 AED||Dubai, United Arab Emirates||Register|
|8/1/2023||5 Days||7350 AED||Dubai, United Arab Emirates||Register|
|7/1/2023||5 Days||7350 AED||Dubai, United Arab Emirates||Register|
The course is a short course that focuses on the impact of digitization that has profoundly affected the energy industry including oil and gas (digital oilfield) supply chains and utilities (smart grids). More data is available from field and process instrumentation and control systems for detailed analysis to improve decision making at all levels, from the field to the board room. The Digital Oilfield is a reality. Lower commodity prices have added the need to improve efficiency of operations, to the existing drivers of a safe and environmentally benign operations footprint, effective recovery of reserves and an attractive return on investment for shareholders.
The course is highly recommended for managers of newly formed data analytics, digital oilfield or data science programs and are developing their strategies and road maps.
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