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.

Course Description:

This 2-day course introduces petroleum, process, and reservoir engineers to the transformative role of AI in enhancing design, simulation, and field performance decisions. Participants will learn how AI can be used to augment engineering intuition, streamline simulation iterations, and support faster, data-informed design optimization—without needing to code or become data scientists.

The course focuses on practical applications of AI such as field planning, well performance prediction, and smart design workflows using simplified, visual AI frameworks and use-case walkthroughs. Engineers will walk away with templates, tools, and strategic insights to start exploring AI in their existing workflows—while setting the stage for deeper technical integrations via L2 and L3 services.

Who Should Attend:

• Petroleum Engineers
• Process Engineers
• Reservoir Engineers
• Facilities and Production Engineers
• Engineering Managers and Technical Advisors
• Professionals involved in field development planning and design

Course Objectives:

Knowledge Acquisition:

• Understand how AI complements simulation, modeling, and engineering workflows
• Explore common use cases of AI in subsurface, surface, and facility design
• Learn where and how to source engineering data for AI insights

Skills Development:

• Translate engineering problems into AI opportunities
• Build simple frameworks to evaluate the
• ROI of AI-driven designs
• Select suitable low-code AI platforms for early experimentation

Practical Application:

• Apply AI to real-time well or process optimization
• Leverage AI for iterative design improvement and simulation analysis
• Design a proof-of-concept plan for one area of AI-enhanced engineering

What will I Learn From it:

• How to accelerate engineering decisions using AI-generated insights
• Which AI tools are best suited for well planning, production forecasting, and process improvement
• How to evaluate engineering workflows for automation or optimization
• Low-risk pathways to begin applying AI in current projects
• How to prepare your team for AI-augmented collaboration

Training Methodology

• Engineer-Friendly Language: Concepts are delivered using visual metaphors, analogies, and industry terminology
• Real-World Use Cases: All examples come from petroleum and process engineering applications
• Hands-On Planning: Participants use guided templates to develop pilot ideas they can take back to their teams
• Peer Exchange: Group activities foster collaboration and cross-pollination of use cases
• Low-Code Demos: Exposure to intuitive AI platforms like RapidMiner, Azure ML, or no-code simulation plugins

Requirement/
pre-requisites:

• Engineering background in upstream/midstream/downstream domains
• Familiarity with simulation tools like HYSYS, Eclipse, Pipesim, etc.
• No programming or data science knowledge required
• Willingness to explore new digital tools and analytical thinking