AAPG Webinar Nov 2020 — Machine Learning for Geoscientists

This repository contains materials shared for the AAPG Webinar held in November 2020, focusing on Machine Learning applications in geoscience.

Contents

• AAPG Webinar Machine Learning for Geoscientists.pdf
  — The complete slide deck from the webinar presentation.

• AAPG_Facies_Classification.ipynb
  — Jupyter Notebook demonstrating facies classification workflows (e.g., clustering or mapping lithofacies using geological attributes).

• AAPG_Simple_Seismic_Modeling_.ipynb
  — Jupyter Notebook illustrating basic seismic modeling techniques, potentially using synthetic or real datasets.

• LICENSE
  — MIT License specifying usage rights.

How to Use This Repository

1. View the slides: Open the PDF to follow concepts, theory, and context presented during the webinar.
2. Run the notebooks:
   • Clone this repository:

     git clone https://github.com/Amrmoslim/AAPG_Webinar_Nov2020.git

   • Navigate inside:

     cd AAPG_Webinar_Nov2020

   • Launch Jupyter Notebook:

     jupyter notebook

   • Open the .ipynb files to explore code and outputs. Ensure you have Python (ideally 3.x) and libraries like numpy, pandas, matplotlib, and scikit-learn (or similar geoscience/ML packages) installed.

License

This project is open source under the MIT License — see the LICENSE file for full details.

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Contribution

Contributions, clarifications, or improvements to these materials are welcome! Please fork the repo, make your changes, and open a pull request.