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Digital Horizons: Energizing Transformation in Oil and Gas, & Beyond > Program > Short Course: Demystifying AI in Oil and Gas

Short Course: Demystifying AI in Oil and Gas

Wednesday, October 29, 2025
8:00am – 2:00pm

Admission to this Short Course is available as an add-on or a single day registration item. The fee is in addition to or separate from conference registration.

Instructors:

  • Dr. Matthew Franchek
  • Dr. Ed Marotta
  • Dr. Rafik Borji

Tentative Outline:

  1. Introduction to AI in Oil and Gas (30 minutes)
    • Overview of AI: Brief introduction to AI and its significance in the oil and gas industry.
    • Current Trends: Discuss the latest trends and advancements in AI technologies impacting the sector.
    • Real-World Examples: Highlight key use cases such as seismic data analysis, predictive maintenance, and drilling optimization.

  2. Data Preparation for AI (1 hour)
    • Importance of Data: Explain why high-quality data is crucial for AI applications.
    • Data Collection and Standardization: Techniques for collecting and standardizing data.
    • Data Cleaning and Preprocessing: Methods to ensure data completeness, accuracy, and readiness for AI models.

  3. Classical Machine Learning (1.5 hours)
    • Introduction to ML: Basics of machine learning and its applications in oil and gas.
    • ML Algorithms: Overview of common algorithms (e.g., regression, classification, clustering) and their use cases.
    • Hands-On Session: Practical exercise using Python to build and evaluate a simple ML model (e.g., predictive maintenance).
    • Case Studies: Discuss successful ML implementations in the industry.

  4. Generative AI (1 hour)
    • Introduction to Generative AI: Explain generative AI and its capabilities.
    • Applications in Oil and Gas: Explore how generative AI can be used for predictive maintenance, reservoir modeling, and simulation.
    • Hands-On Session: Demonstrate generative AI techniques.
    • Future Trends: Discuss the potential future impact of generative AI on the industry.

  5. Integration and Real-World Applications (1 hour)
    • Combining AI Techniques: How to integrate data preparation, classical ML, and generative AI for comprehensive solutions.
    • Interactive Discussion: Engage participants in discussing challenges and opportunities in implementing AI in their operations.
    • Q&A Session: Open floor for questions and further discussion on specific topics of interest.