Machine Learning and Data Management in the Oil and Gas Industry

What are the Goals?

• Learn to identify the impact of data quality and data management on success of oil and gas enterprise
• Acquire the knowledge about data management framework across the enterprises
• Identify the machine learning algorithms applied within the oil and gas industry
• Learn how to gather, transform and use the spatial, seismic, production and other data
• Identify the relations between the master data management process optimization

Who is this Training Course for?

• Petroleum Data Analysts
• CEOs, CIOs, COOs
• Systems Analysts
• Programmers
• Data Analysts
• Database Administrators
• Project Leaders
• Software Engineers

Daily Agenda

Day One: Data gathering and data quality within oil and gas industry

• Data sources
• Data rules for well identification and classification
• PPDM data model
• Geospatial data storage, analysis and use
• Machine learning in geospatial data

Day Two: Machine learning in oil and gas industry

• Machine learning algorithms
• Python programming
• R programming
• Use of existing software and its combination with Python and R
• Tensorflow

Day Three: Areas where machine learning can be implemented within oil and gas industry

• Forecasting
• Anomaly detection
• Process control
• Optimization
• Maintenance
• HSE
• Other areas

Day Four: Data collection and analysis using machine learning

• Data from SCADA
• Data from sensors
• Data from ECM
• Data visualization
• Data Analytics techniques for immediate insights

Day Five: Technologies in use

• Digital core
• Digital oilfield
• Machine learning in predictive maintenance
• Use of soft sensors
• Example cases and way forward