Machine Learning and Data Management in the Oil and Gas Industry
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Machine Learning and Data Management in the Oil and Gas Industry Course
Introduction:
As the oil and gas industry is evolving and changing the necessity of bringing together leadership power, domain expertise, knowledge, and many data silos that still exist within the organizations. This course focuses on a fundamental understanding of the petroleum industry and machine learning, as well as data management, helping organizations within the industry to achieve success by using the data they possess and reducing the risk and uncertainty that is omnipresent in the oil and gas industry.
Course Objectives:
This course focuses on presenting the delegates with the opportunity to learn the essentials of data governance, data collection and management, data security, data analysis, Machine Learning algorithms, and their implementation within the oil and gas industry.
By the end of this Machine Learning and Data Management in the Oil and Gas Industry training course, participants will learn to:
- Learn to identify the impact of data quality and data management on the success of oil and gas enterprise
- Acquire knowledge about data management framework across enterprises
- Identify the machine learning algorithms applied within the oil and gas industry
- Learn how to gather, transform, and use spatial, seismic, production, and other data
- Identify the relations between the master data management process optimization
Who Should Attend?
The training course has been designed for professionals whose jobs involve data gathering, data analysis, and decision-making.
This training course is suitable for a wide range of professionals but will greatly benefit:
- Petroleum Data Analysts
- CEOs, CIOs, COOs
- Systems analysts
- Programmers
- Data analysts
- Database administrators
- Project leaders
- Software engineers
Course Outlines:
Data gathering and data quality within the oil and gas industry
- Data sources
- Data rules for good identification and classification
- PPDM data model
- Geospatial data storage, analysis, and use
- Machine learning in geospatial data
Machine learning in the oil and gas industry
- Machine learning algorithms
- Python Programming
- R programming
- Use of existing software and its combination with Python and R
- TensorFlow
Areas where machine learning can be implemented within the oil and gas industry
- Forecasting
- Anomaly detection
- Process control
- Optimization
- Maintenance
- HSE
- Other areas
Data collection and analysis using machine learning
- Data from SCADA
- Data from sensors
- Data from ECM
- Data visualization
- Data Analytics techniques for immediate insights
Technologies in use
- Digital core
- Digital oilfield
- Machine learning in predictive maintenance
- Use of soft sensors
- Example cases and the way forward
