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Artificial intelligence in drilling and completion operations

AIDC-EN-P
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Who should attend?

  • This course presents comprehensive training in Machine Learning (ML), Data Science (DS) and Artificial Intelligence (AI) applications in drilling operations for engineers in the oil & gas industry. The course focuses on integrating these advanced technologies into the day-to-day work of simulation, well monitoring and drilling optimization. It aims to equip professionals with the knowledge and tools to improve efficiency, reduce risk and enhance real-time decision-making in drilling practices.
Public :
  • Petroleum industry engineers with experience in well monitoring, simulation and drilling & Completion operations.
  • Professionals seeking to understand the value of machine learning and data science to solve industry-specific problems and optimize operations.

Level :Awareness

Prerequisite :
  • No prerequisites are necessary to follow this course.

Course Content

  • INTRODUCTION TO MACHINE LEARNING (ML) AND DATA SCIENCE IN PETROLEUM ENGINEERING - Duration : 1.5 Days

      • Overview of ML/AI concepts (supervised, unsupervised learning, deep learning). Data Science workflow and how it integrates with petroleum engineering practices. Examples of applications of ML/AI in drilling, reservoir modeling, and production forecasting.

  • DATA COLLECTION AND INTEGRATION IN DRILLING OPERATIONS - Duration : 0.25 Day

      • Handling and integrating data from sensors, logging tools, and simulation outputs. Real-time data acquisition and preprocessing for drilling optimization. Understanding the role of Big Data and its potential to transform drilling.

  • TOOLS AND PLATFORMS FOR ML IN DRILLING - Duration : 0.25 Day

      • Overview of software tools and platforms like TensorFlow, Keras, PyTorch, and Scikit-learn for building ML models.

  • PREDICTIVE ANALYTICS IN DRILLING OPERATIONS - Duration : 0.5 Day

      • Using machine learning models to:
      • predict drilling parameters such as rate of penetration (ROP), formation pressure,..
      • improve predictive maintenance for drilling equipment using sensor data and AI models to reduce unplanned downtime.
      • enhance anomaly detection in drilling operations for early identification of risks (e.g., stuck pipe, lost circulation).

  • DRILLING OPTIMIZATION USING MACHINE LEARNING - Duration : 0.5 Day

      • Learn how to define and use:
      • Supervised learning models to optimize drill bit selection, mud weight, and drilling speed.
      • Reinforcement learning for dynamic adjustments in drilling based on environmental and operational data.
      • Real-time decision support systems powered by machine learning to improve wellbore stability and minimize drilling hazards.

  • SIMULATION-DRIVEN ML MODELS FOR DRILLING - Duration : 1 Day

      • Integration of simulation results with machine learning to build better predictive models.
      • Creating virtual models of the wellbore or drilling environment.
      • Case studies on using ML models to analyze and enhance drilling simulation results.

  • AUTOMATING WELL MONITORING AND RISK ASSESSMENT - Duration : 0.5 Day

      • Automating well monitoring with:
      • AI models that continuously assess well health and recommend corrective actions.
      • AI-enhanced risk assessment tools that predict potential blowouts or formation damage.
      • Case studies on how machine learning reduces risks and improve outcomes in drilling projects.

  • AI IN DRILLING AUTOMATION AND CONTROL - Duration : 0.5 Day

      • Future trends in automated drilling systems and robotics in well construction.
      • The role of AI in autonomous drilling: reducing human intervention and increasing efficiency.
      • Smart rigs and how machine learning could enable the automation of routine tasks.

Learning Objectives

  • Attendees will be able to implement the following skills:
  • Understand the fundamentals of machine learning and its relevance to drilling & completion,
  • Learn how to apply data science techniques to well monitoring and real-time decision making,
  • Learn how to use software tools and platforms for building ML models,
  • Discover how AI-driven models can improve operational efficiency, reduce downtime and enhance predictive maintenance,
  • Integrate data from sensors and simulation tools to build predictive drilling performance models.

Ways & Means

  • Highly interactive course delivered by experts of the E&P industry.
  • Numerous examples and feedbacks from the industry. Numerous videos and animations.

Learning assessment

  • Table game in small groups.

More

Additional information :Other training duration availability on request.

Coordinator :IFP Training instructors, with expertise in the field and trained in modern teaching methods adapted to the specific needs of learners from the professional world.

To French entities : IFP Training is referenced to DataDock ; you may contact your OPCO about potential funding. Please contact our disabled persons referent to check the accessibility of this training program : referent.handicap@ifptraining.com