Yulman Perez Reservoir Engineering & Energy Research

From the subsurface to energy decisions.

Deepwater assets are capital-intensive, operationally complex and shaped by subsurface uncertainty. Yulman Perez works across reservoir engineering, computational research and decision support to strengthen technical understanding for consequential engineering decisions.

Experience

Education
PhD in Energy ResourcesStanford University
Current role
Deepwater Reservoir EngineerShell, 2026–present
Start a conversation Publications on Google Scholar

Professional interests

  • AI + Subsurface

    Physics-informed AI applied to operational workflows.

  • Technical Asset Evaluation

    What determines how an energy asset is designed, how it performs and where its risks lie.

Working principles

Engineering decisions with a deep physical understanding, uncertainty range and their evaluation.

  • Data

    Document data sources, quality and gaps.

  • Models & physics

    Match models to the physical world, make assumptions explicit and state limitations.

  • Uncertainty

    Explain uncertainty, its drivers and its implications.

  • Decision quality

    Connect technical evidence with the outcome of every decision.

Start a conversation

For questions on reservoir engineering and the subsurface or research collaboration, a short email with some context is enough to start.

Conversations are held in a personal capacity.

yulman@stanford.eduPublications on Google Scholar