Global Learning for Operational Leaders
Classroom
16 sessions
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Online / Live
16 sessions
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Introduction
Course overview
Oil and gas companies generate enormous volumes of seismic, well, production, maintenance and commercial data. Artificial intelligence and analytics can turn this data into faster decisions, higher recovery and lower costs.
This Aractech course explains machine learning, generative AI and analytics applications across exploration, drilling, production, maintenance, HSE and trading. Participants learn how to identify high-value use cases, prepare data, evaluate models, manage risks and scale AI solutions.
Hands-on demonstrations and case studies make the content practical for engineers and managers without advanced programming skills.
What you will achieve
Learning objectives
- Explain AI, machine learning and analytics concepts
- Identify AI use cases across the oil and gas value chain
- Prepare and assess data for analytics
- Evaluate model performance and limitations
- Manage AI risks and governance
- Plan and scale AI initiatives
Who should attend
Target audience
- Engineers and geoscientists
- Data analysts and data scientists in energy
- Operations and maintenance managers
- Digital transformation teams
- HSE and planning professionals
- Managers sponsoring AI projects
Methodology
Learning approach
- Concept explanations
- Demonstrations and guided exercises
- Industry case studies
- Use-case workshops
- Group presentations
Complete course outline
Five focused days of learning and application
The timings provided are estimates and may vary depending on the number of participants and the discussions taking place during the sessions. They are indicative only and do not constitute a binding commitment.
Day 1
AI and Analytics Fundamentals
- Data in oil and gas
- Analytics types
- Machine learning basics
- Generative AI
- Coffee break
- Generative AI (continued)
- Limitations
- Exercise: Identifying data assets
Day 2
Subsurface and Drilling Applications
- Seismic interpretation
- Reservoir characterisation
- Drilling optimisation
- Well planning
- Coffee break
- Well planning (continued)
- Case study: ML in drilling
- Exercise: Use-case scoring
Day 3
Production and Maintenance Applications
- Production forecasting
- Anomaly detection
- Predictive maintenance
- Energy optimisation
- Coffee break
- Energy optimisation (continued)
- HSE analytics
- Lab: Analysing production data
Day 4
Data and Model Management
- Data preparation
- Feature engineering basics
- Model evaluation
- Explainability
- Coffee break
- Explainability (continued)
- MLOps overview
- Workshop: Model evaluation
Day 5
Scaling AI
- Governance and ethics
- Skills and organisation
- Vendor selection
- Coffee break
- Vendor selection (continued)
- Value measurement
- Roadmap
- Capstone: AI use-case proposal
FAQ
Frequently asked questions
What does Artificial Intelligence and Data Analytics in Oil and Gas (OG-060) cover?
This course covers Oil and Gas through a structured five-day outline focused on practical application, discussion, and implementation planning.
When is the next available session?
The next scheduled session starts on 9 - 13 November 2026. See the course schedules section for the available dates and delivery formats.
Who should attend this course?
Engineers and geoscientists, Data analysts and data scientists in energy, Operations and maintenance managers
Is bilingual course delivery available?
Yes. All course materials and presentations are provided in English, while bilingual explanation and discussion support may be available depending on the selected location and trainer availability. For example, when attending a course in Istanbul, you may request a Turkish-speaking trainer to explain the English course content in Turkish. Arabic explanation support may also be requested at this location. Other languages are available in selected cities. You can choose your preferred language support as an optional preference during registration.
How can I register for a session?
Use any Register button next to the available course dates to open the participant registration page and submit your booking request for the selected session.
Is this course available online as well as classroom-based?
Check the course schedules section for currently published classroom and Online / Live sessions.
Where are classroom sessions delivered?
Current classroom venues include Rome, Kuala lumpur, Barcelona, Istanbul, London, Munich, Amsterdam, Paris, Frankfurt.
How long is the training programme?
The programme runs for five days from 09:00 to 14:00, which gives 25 contact hours, including a daily 30-minute break (22.5 hours of instruction).
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