cv

General Information

Full Name Miguel Angel Corrales
Date of Birth 11 August 1994
Languages English, Spanish

Education

  • 2022 - Present
    PhD
    King Abdullah University of Science and Technology (KAUST), Kingdom of Saudi Arabia
    • Earth Sciences and Engineering Program (ErSE)
    • Machine Learning Track
    • Deep Reservoir characterization and Uncertainty Quantification from macro scale rock imaging to reservoir scale characterization using Deep Learning framework and Deep Generative Models
  • 2019-2021
    Master of Science
    King Abdullah University of Science and Technology (KAUST), Kingdom of Saudi Arabia
    • Energy Resources and Petroleum Engineering Program (ERPE)
    • Assessment of CO2 storage in saline aquifers in the Unayzah Reservoir, Central Arabia, Kingdom of Saudi Arabia.
  • 2012-2017
    Bachelor's degree
    Universidad Central del Ecuador (UCE), Ecuador
    • Strong Fundamentals about the different of Oil and Gas Supply Chain.
    • Waterflooding study for reservoir development in Coca-Payamino field.

Honors and Awards

  • 2022
    • Hackathon KAUST NVIDIA 2022 Winner, Accelerating Scientific applications using GPUs.
  • 2022
    • Petrobowl Team (KAUST) - Top 3 MENA Qualifiers.
  • 2022
    • BEST IN SHOW, Hackathon - Explainable A.I., EAGE ANNUAL 2022, Madrid-Spain.
  • 2021
    • Third Place e-Poster competition. KAUST Research Conference - Enabling CO2 Geological Storage Within a Low-Carbon Economy
  • 2020
    • Petrobowl Team (KAUST) - Top 3 MENA Qualifiers.
  • 2016
    • Academic Exchange Recognition, Universidad Central del Ecuador.
  • 2012-2017
    • Academic Excellence Scholarship, Universidad Central del Ecuador.

Academic Interests

  • Seismic Reservoir Characterization.
    • Elastic properties from pre-stack seismic data.
    • Petrophysical properties from pre-stack seismic data.
    • Cascade inversion, joint inversion, data-driven inversion.
    • CO2 monitoring.
  • Fluid Flow in Porous media.
    • Fluid flow in oil and gas reservoirs at darcy-scale.
    • Fluid flow in porous media.
    • Fluid flow in naturally fractured reservoirs.
    • Compositional fluid flow for CO2 sequestration in geological formations.
  • Deep Learning and Generative models.
    • Supervised Learning, Unsupervised Learning.
    • Generative adversarial networks and diffusion models.
    • Explainable Artificial intelligence.