| Code | Date | Format | Currency | Team of 10 Per Person* |
Team of 7 Per Person* |
Early Bird Fee Per Person |
Normal Fee Per Person |
|---|---|---|---|---|---|---|---|
| PE2337 | 22 - 26 Mar 2027 | Virtual Instructor Led Training (VILT) | SGD | 2,278 | 3,224 | 4,099 | 4,299 |
| PE2337 | 22 - 26 Mar 2027 | Virtual Instructor Led Training (VILT) | USD | 1,854 | 2,624 | 3,299 | 3,499 |
| PE2338 | 19 - 23 Jul 2027 | Virtual Instructor Led Training (VILT) | SGD | 2,278 | 3,224 | 4,099 | 4,299 |
| PE2338 | 19 - 23 Jul 2027 | Virtual Instructor Led Training (VILT) | USD | 1,854 | 2,624 | 3,299 | 3,499 |
| PE2339 | 06 - 10 Dec 2027 | Virtual Instructor Led Training (VILT) | SGD | 2,278 | 3,224 | 4,099 | 4,299 |
| PE2339 | 06 - 10 Dec 2027 | Virtual Instructor Led Training (VILT) | USD | 1,854 | 2,624 | 3,299 | 3,499 |
*Fee per person in a team of 7 or 10 participating from the same organisation, registering 6 weeks before the course dateRequest for a quote if you have different team sizes, content customisation, alternative dates or course timing requirements Request for in-person classroom training or online (VILT) training format
Learn in teams and save more! Enjoy group discounts of up to 50% off normal fees for team based learning. Contact us on [email protected] to learn more today!
Code
PE2337Date
22 - 26 Mar 2027Format
Virtual Instructor Led Training (VILT)Currency
SGDTeam of 10
Per Person*
2,278
Team of 7
Per Person*
3,224
Early Bird Fee
Per Person
4,099
Normal Fee
Per Person
4,299
Code
PE2337Date
22 - 26 Mar 2027Format
Virtual Instructor Led Training (VILT)Currency
USDTeam of 10
Per Person*
1,854
Team of 7
Per Person*
2,624
Early Bird Fee
Per Person
3,299
Normal Fee
Per Person
3,499
Code
PE2338Date
19 - 23 Jul 2027Format
Virtual Instructor Led Training (VILT)Currency
SGDTeam of 10
Per Person*
2,278
Team of 7
Per Person*
3,224
Early Bird Fee
Per Person
4,099
Normal Fee
Per Person
4,299
Code
PE2338Date
19 - 23 Jul 2027Format
Virtual Instructor Led Training (VILT)Currency
USDTeam of 10
Per Person*
1,854
Team of 7
Per Person*
2,624
Early Bird Fee
Per Person
3,299
Normal Fee
Per Person
3,499
Code
PE2339Date
06 - 10 Dec 2027Format
Virtual Instructor Led Training (VILT)Currency
SGDTeam of 10
Per Person*
2,278
Team of 7
Per Person*
3,224
Early Bird Fee
Per Person
4,099
Normal Fee
Per Person
4,299
Code
PE2339Date
06 - 10 Dec 2027Format
Virtual Instructor Led Training (VILT)Currency
USDTeam of 10
Per Person*
1,854
Team of 7
Per Person*
2,624
Early Bird Fee
Per Person
3,299
Normal Fee
Per Person
3,499
*Fee per person in a team of 7 or 10 participating from the same organisation, registering 6 weeks before the course dateRequest for a quote if you have different team sizes, content customisation, alternative dates or course timing requirements Request for in-person classroom training or online (VILT) training format
About this Virtual Instructor Led Training (VILT)
Agentic AI represents an evolution of artificial intelligence in which autonomous agents can reason, plan, retrieve knowledge, execute workflows, use tools, and interact with enterprise systems to address engineering problems. Unlike conventional generative AI applications that primarily generate responses, agentic systems can coordinate specialised agents to perform technical tasks while maintaining human authority over consequential decisions. This course introduces the concepts, architectures, and practical applications of agentic AI across the upstream oil and gas value chain.
The course examines how agentic AI can be applied across exploration, drilling, reservoir characterisation, production optimisation, asset management, and technical decision support. Participants explore multi-agent systems, retrieval-augmented generation (RAG), Model Context Protocol (MCP), engineering tool integration, digital twins, human-in-the-loop workflows, governance, and enterprise deployment. The course also addresses important considerations such as data quality, uncertainty, explainability, auditability, cybersecurity, model monitoring, and the boundaries between advisory systems and autonomous action.
The emphasis is on practical engineering application rather than AI theory. Participants work through live demonstrations, realistic upstream case studies, browser-based hands-on exercises, and a capstone exercise in which they design an agentic solution for a selected upstream challenge. The course applies a “trust spine” throughout the programme, focusing on physics-first reasoning, validation, explainable attribution, calibrated uncertainty, failure-mode identification, and human authority over consequential decisions. No programming experience is required.
Upon completion of this VILT course, participants will be able to:
- Distinguish agentic AI from generative AI and conventional machine learning by understanding how autonomous agents use planning, reasoning, tools, memory, retrieval, reflection, and agent-to-agent collaboration to perform multi-step engineering workflows.
- Design multi-agent workflows for upstream engineering applications by defining specialised agents, their responsibilities, decision rights, handoffs, arbitration mechanisms, escalation rules, and human approval points.
- Apply agentic AI to practical upstream use cases including exploration, drilling optimisation, reservoir surveillance, production optimisation, well diagnostics, artificial lift, workover prioritisation, and integrated asset management.
- Design the data, retrieval, integration, and governance foundations for agentic systems including RAG, engineering data management, MCP-based tool integration, digital twins, explainability, uncertainty reporting, audit trails, cybersecurity, and model monitoring.
- Develop a practical implementation roadmap for agentic AI in an upstream organisation by evaluating use-case value, data readiness, organisational difficulty, governance requirements, KPIs, pilot selection, and the conditions required for scaling towards greater levels of autonomy.
This course is designed for oil and gas professionals who have a working knowledge of upstream operations and engineering data and want to understand how agentic AI can be applied to real engineering workflows. It is particularly relevant for professionals involved in technical decision-making, engineering analysis, digital transformation, advanced analytics, and the development or implementation of AI-enabled solutions across the upstream value chain.
- Geologist
- Geophysicist
- Petrophysicist
- Data Scientist
- Drilling Engineer
- Petroleum Engineer
- Reservoir Engineer
- Production Engineer
- Completion Engineer
- Technical Manager
- Engineering Manager
- Digitalisation Manager
- Advanced Analytics Specialist
- Drilling Optimisation Specialist
- Production Optimisation Specialist
- AI/ Machine Learning Engineer
- Digital Transformation Manager
- Asset Management Professional
- Integrated Operations Professional
- Reservoir Characterisation Specialist
- Technical Data / Engineering Data Specialist
- Digital Oilfield/ Digital Operation Specialist
- Intermediate
The course uses a practical, application-focused learning approach combining instructor-led sessions, live demonstrations, realistic upstream case studies, browser-based hands-on labs, group exercises, technical discussions, and a final capstone exercise. Each half-day includes a combination of technical modules, a live demonstration, and a worked case study or hands-on activity. Participants work with supplied datasets and case materials through a browser-based Streamlit exercise environment, allowing them to explore agentic workflows without requiring local software installation or programming.
Unlock the potential of your workforce with customized in-house training programs designed specifically for the energy sector. Our tailored, in-house courses not only enhance employee skills and engagement but also offer significant cost savings by eliminating travel expenses. Invest in your team’s success and achieve specific outcomes aligned with your organization’s goals through our expert training solutions. Request for further information regarding our on-site or in-house training opportunities.
In our ongoing commitment to sustainability and environmental responsibility, we will no longer providing hard copy training materials. Instead, all training content and resources will be delivered in digital format. Inspired by the oil and energy industry’s best practices, we are leveraging on digital technologies to reduce waste, lower our carbon emissions, ensuring our training content is always up-to-date and accessible. Click here to learn more.
Agentic AI uses AI agents to complete tasks by planning, finding data, using tools, and following steps. Unlike basic AI chatbots, these systems can work through larger tasks from start to finish. In oil and gas, teams can use Agentic AI to support drilling, reservoir studies, production monitoring, and daily operations. Engineers still review and approve important decisions.
Generative AI creates content such as reports, summaries, and answers. However, Agentic AI can do more than create content. It can gather data, use software tools, check results, and complete work steps. For example, generative AI may explain a drop in production. In contrast, Agentic AI can review well data, find possible causes, and suggest actions.
Agentic AI can support many upstream tasks. These include seismic interpretation, prospect ranking, drilling support, reservoir monitoring, production forecasting, artificial lift support, and workover planning. It can also help teams find missed opportunities and manage field operations. As a result, engineers can save time and focus on higher-value work.
This course is for oil and gas professionals who want to learn how AI can support engineering work. It is suitable for petroleum engineers, reservoir engineers, geologists, geophysicists, drilling engineers, production engineers, petrophysicists, and data scientists. In addition, managers and digital teams can gain useful knowledge from the course.
No. You do not need coding skills to join this course. Instead, the programme focuses on practical examples and business use cases. Participants take part in live sessions, hands-on activities, case studies, and group discussions. In addition, the browser-based learning tools require no software installation.
You will learn how Agentic AI works in upstream oil and gas. The course covers AI agents, multi-agent workflows, data access, tool connections, digital twins, and safe AI use. In addition, you will take part in case studies and exercises that show how companies can apply AI to real engineering tasks.
The course teaches how to use AI safely in oil and gas operations. Participants learn about data quality, cyber security, review processes, audit trails, and human approval steps. In addition, the course explains how companies can monitor AI systems and reduce risk. These practices help teams use AI with greater confidence.


