How can reservoir engineers make practical use of Generative AI without compromising engineering judgment?
Fabian Camilo Yatte Garzon’s new course explores how AI can support real-world technical workflows while keeping evidence, validation and human expertise at the centre.
Join this free preview webinar to get a taste of the course!
About the course
Using a reservoir-surveillance scenario focused on water-production diagnosis, the course will introduce how Generative AI can help engineers organise technical information, explore possible explanations and identify gaps in the available evidence. The example will also highlight the importance of critically reviewing AI-generated outputs. While AI can help structure information and support the investigation of technical problems, its suggestions need to be checked against the available data, physical principles and sound engineering judgment.
The programme will build on this approach, exploring how engineers can incorporate Generative AI into their workflows, evaluate AI-generated results and use AI-assisted tools to support technical decisions while retaining control over the analysis.
Join the free course preview webinar
Date: 16 November 2026
Time: 15:00 – 16:00 CET
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Who should attend?
The course is designed for reservoir engineers, reservoir simulation engineers, reservoir surveillance professionals, production engineers, and related subsurface professionals who want to integrate Generative AI into practical technical workflows.
No prior programming experience is required, and no formal AI training is assumed.
The instructor
Fabian Yatte is a senior reservoir and simulation engineer with more than 17 years of experience in reservoir engineering, numerical simulation, reservoir management, enhanced oil recovery, and technical decision support. His career combines experience with operating companies, applied research, professional education, customer-facing technical advisory work, and engineering technology innovation. In his current role at Computer Modelling Group (CMG), Fabian works closely with reservoir and simulation engineers through technical training, application support, and engineering advisory activities. He also contributes to the development and exploration of engineering application concepts and prototypes, including frontend and UX/UI workflows, AI-assisted prototyping, and the incorporation of Generative AI assistants into technical applications. Fabian previously held reservoir-engineering positions with operating companies in Colombia and worked as a researcher and university lecturer, teaching Advanced Reservoir Simulation and Hydrocarbon Thermodynamics. His broader technical experience includes heavy-oil and thermal EOR, reservoir surveillance, water injection, gas and compositional simulation, uncertainty analysis, integrated reservoir-production modelling, and CCUS-related studies. Alongside his reservoir-engineering training activities, Fabian has developed and delivered Generative AI training for technical professionals. His recent Applied AI work includes AI-assisted research, grounded knowledge workflows, reusable assistants, engineering data analysis, technical prototyping, and exploration of connected and agentic AI-enabled engineering workflows. His technical contributions also include work combining AI and CCUS, including algorithm-assisted analysis of CO₂ storage mechanisms and agentic workflow concepts for CCUS assessment.
Interested in customized training?
This course can also be requested for in-house training. Interested in booking customized training for your team or organization? Contact us via education@eage.org
