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@CytiVen @TCDAG

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misaelmmorales/README.md

Hola! 👋

  • 🏝 My name is Misael Morales, I am from Venezuela, and I am currently a PhD candidate at The University of Texas at Austin
  • 💻 My research is focused on the computational description of subsurface energy systems. I combine domain-specific knowledge with tools from machine learning, applied math, and statistics, for accurate characterization and forecasting of complex dynamical systems in the subsurface
  • 🎓 M.S. in Mathematics, B.S. in Applied Math and B.S. in Petroleum Engineering, all from the University of Tulsa
  • 🌐 Website | Linkedin | ORCID | ResearchGate | Google Scholar
Reduced-order modeling Forward & Inverse modeling Physics-informed machine learning Uncertainty Quantification Data Assimilation Control & Optimization

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  1. Stochastic-pix2vid Stochastic-pix2vid Public

    Spatiotemporal forward proxy model for CO2 storage prediction

    Python 2 2

  2. Anisotropic-Resistivity-Inversion Anisotropic-Resistivity-Inversion Public

    PINN-based inversion algorithm for parallel- and perpendicular-to-bedding plane resistivity

    Python 1 2

  3. Placement-Control-Optim-CO2 Placement-Control-Optim-CO2 Public

    Well placement and control optimization for CO2 sequestration

    Python 1 1

  4. Ensemble-Model-Calibration-CO2 Ensemble-Model-Calibration-CO2 Public

    Ensemble modeling calibration for CO2 storage under geologic uncertainty

    Python

  5. AutoPetrophysics-GOM-CCS AutoPetrophysics-GOM-CCS Public

    Automatic well-log baseline correction and core2log rock classification for potential CO2 storage site characterization in the Gulf of Mexico.

    Python 2

  6. Drone-Rock-Classification Drone-Rock-Classification Public

    Automatic rock classification via deep learning image segmentation for core images from drones

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