AI For Oil & Gas

Optimize reservoir management, drilling operations, and production forecasting through AI technologies that enhance decision-making and minimize downtime across upstream, midstream, and downstream operations

AI-Driven Operational Excellence in Oil & Gas: Unlocking Efficiency & Uptime

A practical, non-technical 2-day training to help oil & gas operations leaders identify high-impact AI use cases that enhance uptime, reduce OPEX, and prepare for digital transformation.

Key Topics:

  • Predictive Maintenance in Equipment & Assets
  • Anomaly Detection in Control Room Monitoring
  • AI-Augmented Process Optimization
  • Smart Scheduling & Workforce Utilization
  • Operational Data Mapping & AI Readiness

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Smarter Engineering Decisions with AI: From Design to Field Optimization

This 2-day course shows engineers how to enhance simulation, design, and field planning using AI—without needing coding skills. It covers AI’s role in forecasting, process modeling, and optimization through easy-to-use tools, frameworks, and real-world examples.

Key Topics:

  • AI vs Simulation: Understanding where AI fits in engineering workflows
  • Forecasting with AI: Smarter well and production predictions
  • Design optimization: Accelerating process design using AI models
  • Low-Code Tool Exploration: Hands-on with AI platforms engineers can use
  • AI Pilot Planning: Creating a tailored AI use case for engineering teams

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AI for Safer Sites: Transforming HSE Through Intelligent Automation

This 2-day course equips HSE professionals with practical AI tools to enhance safety, predict incidents, and improve compliance. It covers real-time hazard detection, predictive safety analytics, and AI's alignment with ESG goals—all in a non-technical, application-first format.

Key Topics:

  • Computer Vision in Safety: Detecting PPE non-compliance, hazards
  • Predictive Incident Analytics: Using data to prevent accidents
  • AI in ESG & Environmental Monitoring: Supporting audits and emissions tracking
  • Ethical AI in HSE: Privacy, trust, and fairness in monitoring
  • Pilot Design for Safety AI: Creating a risk-focused use case to test AI

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AI for Asset Integrity: Prolonging Lifespan, Preventing Failures, Maximizing ROI

Designed for integrity and maintenance professionals, this course introduces how AI predicts failures, optimizes inspection intervals, and models remaining useful life (RUL). It gives participants frameworks and tools to begin AI pilots focused on reducing risk and maximizing asset value.

Key Topics:

  • AI in Predictive Maintenance: Spotting failures before they occur
  • AI in Risk-Based Inspection (RBI): Enhancing prioritization
  • Lifecycle Prediction Models: Estimating remaining asset life with AI
  • Data Requirements for AI in Integrity: What data matters, what doesn’t
  • Business Case Development: Justifying AI through risk and cost savings

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