An Interactive 5-Day Training Course

Agentic AI for Oil & Gas Operations

Designing Supervised AI Agents for Production, Maintenance and Operational Support

Agentic AI for Oil & Gas Operations

Scheduled Dates

24 - 28 May 2027
Dubai - UAE
$5,950
05 - 09 Jul 2027
Online
$4,950
30 Aug - 03 Sep 2027
London - UK
$5,950
06 - 10 Dec 2027
Dubai - UAE
$5,950

Why Choose this Training Course?

This Agentic AI for Oil & Gas Operations training course equips professionals to assess where supervised AI agents can support production, maintenance and day-to-day operational decisions. Participants learn to select tasks that match the quality of available information, the level of operational risk and the team's capacity to review AI outputs. The focus is on making technical information easier to use while preserving engineering judgement and accountability.

The training course develops the skills to design and evaluate AI agent workflows that use approved technical sources, operate within defined permissions and route exceptions to the right people. Participants learn to judge the accuracy and traceability of agent outputs, specify where human approval is required and assess whether a proposed workflow meets the reliability, cybersecurity and oversight requirements of an oil and gas operating environment.

This Agentic AI for Oil & Gas Operations training course will highlight:

  • Use case selection for production and maintenance support
  • Supervised AI agent design with defined approval points
  • Traceable retrieval from approved technical sources
  • Cybersecurity safeguards and industrial control boundaries
  • AI agent readiness and performance evaluation

What are the Goals?

By the end of this training course, participants will be able to:

  • Prioritise operational AI use cases by value, risk and data readiness.
  • Design agent workflows with defined tasks, permissions and approval points.
  • Specify approved information sources, source references and handovers.
  • Assess output accuracy and reliability against operational requirements.
  • Define escalation criteria for AI errors and security concerns.
  • Set performance measures and readiness criteria for supervised AI agents.

Who is this Training Course for?

This training course is suitable to a wide range of professionals but will greatly benefit:

  • Oil and Gas Operations Engineers
  • Production Engineers
  • Maintenance Planners
  • Reliability Engineers
  • Oil and Gas Facilities Managers
  • Digital Oilfield Specialists
  • Technical Services Engineers
  • Operational Excellence Managers
  • OT/IT Integration Leads

How will this Training Course be Presented?

The training course uses guided demonstrations and discussions based on oil and gas operating scenarios. Illustrative shift reports, maintenance records and technical procedures show how an AI agent retrieves information, presents evidence and routes exceptions for review. Participants examine sample outputs to assess accuracy, source traceability and compliance with approval rules.

Organisational Impact

  • Prioritise low-risk AI use cases with measurable value.
  • Standardise shift handovers and maintenance job preparation.
  • Clarify workflow ownership, access and approvals.
  • Track accuracy, exceptions and operator time.

Personal Impact

  • Verify AI outputs against approved records.
  • Identify conflicting information and escalate exceptions.
  • Explain task boundaries and approval requirements.
  • Recommend suitable AI uses for operational teams.

Daily Agenda

Day 1: Agentic AI in Oil & Gas Operations
  • AI agent capabilities and limitations
  • AI agents, conventional automation and control systems
  • Use cases across production, processing and maintenance
  • Information retrieval and supervised task coordination
  • Operational value, risk and operator workload
  • Use case selection and data readiness
Day 2: Designing Supervised AI Agent Workflows

  • Workflow mapping and task boundaries
  • Agent instructions and permitted actions
  • Approved technical documents and source traceability
  • CMMS, EAM and data historian interfaces
  • Identity, access permissions and approval checkpoints
  • Handovers, escalation triggers and safe-stop conditions
Day 3: AI Agents for Production and Maintenance Support

  • Production surveillance reports and exception summaries
  • Work order triage and maintenance job preparation
  • Retrieval of approved procedures and job plans
  • Shift handovers and operational action tracking
  • Inconsistent records and ambiguous instructions
  • Engineer review of AI-generated outputs
Day 4: Operational Safety, Cybersecurity and AI Assurance

  • AI agent boundaries for industrial control and safety systems
  • Data classification and least-privilege access
  • Third-party connections and data exposure risks
  • Hallucinations, prompt injection and unreliable retrieval
  • Scenario-based testing and audit trails
  • Incident escalation and rollback procedures
Day 5: AI Agent Readiness and Performance Evaluation

  • Operational ownership and approval responsibilities
  • Data quality and integration readiness
  • Vendor capability and oversight requirements
  • Accuracy, exception rates and operator time
  • Operating costs and service-level measures
  • Ongoing monitoring and reassessment

Certificate

  • Upon successful completion of this training course, delegates will be awarded an official PetroKnowledge Certificate of Completion, signed by the course facilitator. The certificate confirms successful participation and records the total learning hours completed.
  • Continuing Professional Education credits (CPE): In accordance with the standards of the National Registry of CPE Sponsors, one CPE credit is granted per 50 minutes of attendance.

Accreditation

NASBA Approved Training Courses

Would an alternative date be more suitable?

We offer a variety of tailored training options, customized to meet your organisation's needs. Delivered anytime, anywhere, we make it easy to bring expert training directly to your team.

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