Who is this program designed for?
- Engineers and technicians
- Operations and HSE staff
- Team leads
- Upstream, midstream and downstream professionals
FORMATIVELABZ INC
Energy and operations
AI for Oil and Gas
Registration is open · CAD 299 online (self-paced) / CAD 399 hybrid. Start date confirmed directly.
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The CPD Group Approved Provider #786002
Formativelabz Inc (earlier known as Formativelabz Learning & Research Academy). Explore our provider reference and ask about your chosen course.
Check the provider reference on the CPD Register
About the program
This course takes oil and gas professionals from understanding AI to leading its adoption on a real asset, in six modules that each end in a hands-on project. Every learner finishes with a six-piece portfolio, and the last piece is a full AI roadmap for one asset.
Your learning journey
- 01AI Foundations and Problem Framing
- 02Oil and Gas Data Engineering
- 03Predictive Maintenance and Digital Twins
- 04Generative and Agentic AI
- 05Automation, OT Cybersecurity and Safe AI
- 06Emissions, Governance and AI Adoption
What you will build
- A six-piece portfolio
- An asset AI roadmap
- A capstone panel presentation
Putting the learning to work
Explain AI in plain language, map use cases and recognise when AI is the wrong approach.
Practice areas
- Problem framing
- Field data preparation
- Failure prediction
- Document assistants
- Operational safeguards
- Emissions and governance
Why choose this program
A clear learning path
Six practical modules.
Work you can review
A six-piece portfolio
A practical focus
Explain AI in plain language, map use cases and recognise when AI is the wrong approach.
Learning with context
Engineers and technicians
Evidence of learning
Assess projects against four questions: does it solve a real oil and gas problem, does it work with evidence, are its limits and risks honest, and could a colleague use it? Your course assessment details are confirmed before enrollment.
A final piece of work
Choose one asset and propose priority use cases, data readiness, risks, safeguards, costs, benefits and a rollout plan. Present it to a mock leadership panel.
Completion and evidence of learning
Assess projects against four questions: does it solve a real oil and gas problem, does it work with evidence, are its limits and risks honest, and could a colleague use it? Your course assessment details are confirmed before enrollment.
- A six-piece portfolio
- An asset AI roadmap
- A capstone panel presentation
Learning path
Module01
AI Foundations and Problem Framing
Explain AI in plain language, map use cases and recognise when AI is the wrong approach.
Project: Use-Case Canvas: a one-page problem, data, value and risk assessment.
Module02
Oil and Gas Data Engineering
Prepare messy field data through quality checks, time-series alignment and data governance.
Project: Clean the Field: a working data pipeline and quality report.
Module03
Predictive Maintenance and Digital Twins
Read false alarms and missed failures, test a prediction model and explain equipment health results.
Project: Predict the Failure: a model and equipment health dashboard.
Module04
Generative and Agentic AI
Build an assistant that answers from drilling documents and cites the report it used.
Project: Drilling Report Assistant: an assistant with a documented task.
Module05
Automation, OT Cybersecurity and Safe AI
Map operational risks, human oversight and safeguards around physical processes.
Project: AI Risk Map: risks and safeguards for a sample plant network.
Module06
Emissions, Governance and AI Adoption
Lead an asset-level adoption decision, including an emissions use case and a rollout plan.
Project: Asset AI Roadmap: a full proposal and panel presentation.
Preparation and entry requirements
Entry requirements will be confirmed before enrollment
Discuss your learning schedule and format with us
Where the learning fits
Engineers and technicians
Operations and HSE staff
Team leads
Upstream, midstream and downstream professionals
Build practical skills and a body of work you can explain and apply.
Projects and use cases
Capstone project
Asset AI Roadmap
Choose one asset and propose priority use cases, data readiness, risks, safeguards, costs, benefits and a rollout plan. Present it to a mock leadership panel.
AI Foundations and Problem Framing
Use-Case Canvas: a one-page problem, data, value and risk assessment.
Oil and Gas Data Engineering
Clean the Field: a working data pipeline and quality report.
Predictive Maintenance and Digital Twins
Predict the Failure: a model and equipment health dashboard.
Generative and Agentic AI
Drilling Report Assistant: an assistant with a documented task.
Automation, OT Cybersecurity and Safe AI
AI Risk Map: risks and safeguards for a sample plant network.
Emissions, Governance and AI Adoption
Asset AI Roadmap: a full proposal and panel presentation.
Practical learning for Calgary energy professionals
Start with one asset-level problem. The outline covers field data, maintenance, document assistants, safeguards and governance. Practise problem framing and data checks before deciding whether a tool is suitable.
A proposed exercise can use fictional maintenance records to compare a failure signal with a human review. Do not upload confidential asset records or connect a training project to live operations.
Does this replace site safety training?
No. Follow your workplace safety rules, role permissions and approved systems. This course is skills education, not permission to deploy an operational tool.
Your questions, answered
Who is this course for?
Engineers, technicians, operations and HSE staff, team leads and oil-and-gas professionals.
How much does it cost?
CAD 299 online (self-paced) / CAD 399 hybrid. Our team confirms payment arrangements directly. Fees may vary for international students outside Canada.
How long is the course?
Six modules. Ask our team about the learning-time commitment.
What will I work on?
A six-piece portfolio and an AI adoption roadmap for one asset.
Can I register now?
Yes. Registration is open. Register now and we confirm your place, fee, start date and access directly.
What happens after I register?
Register now, then confirm your course format, start date and access with Formativelabz. Review final delivery details, total cost and terms before enrollment. Enrollment and access are confirmed separately.
Free virtual job simulations
APA Group: Engineering for New Energy
Practise company-designed renewable-energy project tasks through a free, self-paced job simulation on Forage. Follow example answers, build confidence in around 3-4 hours, and earn a Forage program certificate.
Start the free APA Group simulation
Enroll yourself on Forage and explore its current program details.
Enrollment and program information
Registration is open
We reply within 1 business day with your start date and payment details.
Self-paced: start within 24 hours of payment. Hybrid: next cohort confirmed on registration.
Registration is open. Choose Register now; we confirm your place, fee, start date and access directly. Your registration is reviewed by our team before payment.
Register nowProgram fees
CAD 299 online (self-paced) / CAD 399 hybrid.
Fees may vary for international students outside Canada.
Intended participants
- Engineers and technicians
- Operations and HSE staff
- Team leads
- Upstream, midstream and downstream professionals