How agentic AI can support production and maintenance workflows, and what PetroKnowledge’s proposed training course with Excentra AI Academy will cover.
PetroKnowledge has announced Agentic AI for Oil & Gas Operations, a proposed five-day training course in association with Excentra AI Academy. It will help oil and gas professionals identify tasks an AI agent can support, define where engineering approval is needed and assess what evidence would justify a supervised pilot.
Why agentic AI matters for oil and gas operations
Oil and gas teams already use digital systems to monitor production, plan maintenance and manage technical records. Much of the work still involves finding the right procedure, interpreting a production report, gathering missing work-order information and coordinating the next step across teams and systems.
Agentic AI can support this work by carrying out a series of steps within a defined workflow. For example, an agent could retrieve an approved maintenance procedure, assemble the information needed for a draft request and pass it to an authorised engineer for review. If information is missing or instructions conflict, the workflow can require the agent to pause and escalate the request. excentra.com
What the proposed training course will cover
The training course focuses on operational support tasks with a clear scope and an output that staff can check. Examples include preparing a maintenance information pack, organising approved technical references, drafting a shift summary and triaging routine operational requests. Participants will examine which information and tools an agent should be allowed to use, who reviews its work and when a request requires escalation.
PetroKnowledge brings its perspective on petroleum operations, maintenance workflows and engineering decisions. Excentra AI Academy contributes expertise in AI agent design, governance and implementation. View the Agentic AI for Oil & Gas Operations course outline on Excentra AI Academy.
Five learning priorities
- Identify production and maintenance tasks that are suitable for supervised AI support.
- Design workflows with clear approval points and escalation routes.
- dentify the approved documents and enterprise information an agent needs for each task.
- Test how the agent handles incomplete information, exceptions and security restrictions.
- Develop a 90-day pilot proposal with clear responsibilities and criteria for evaluating results.
What participants will take back
Participants will develop a pilot proposal for a specific operational support task. They will define the task, identify the information and approvals it requires, and specify what the operations team would need to see before deciding whether to deploy the agent. The proposal gives operations, engineering and technology teams a concrete basis for reviewing the use case together.
Who should consider this training course?
The course is intended for production engineers, operations managers, maintenance planners, reliability professionals, digital oilfield specialists, technical knowledge managers, IT and operational technology specialists, and AI transformation leads working with oil and gas assets.
About the collaborators
PetroKnowledge provides professional and technical training for the petroleum and energy industries. Excentra AI Academy specialises in professional AI training, including agentic AI, governance, business applications and data analytics. Explore PetroKnowledge’s Big Data & Artificial Intelligence Training Courses.
