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.
1. What is Agentic AI in the oil and gas industry?
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.
2. How is Agentic AI different from Generative AI?
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.
3. What upstream oil and gas tasks can Agentic AI support?
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.
4. Who should attend this Agentic AI course?
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.
5. Do I need coding experience to attend?
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.
6. What will I learn from this course?
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.
7. How does the course cover safe AI use?
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.