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ahmedsahernouh/README.md

Ahmed Saher Nouh

I’m an exploration geophysicist with experience in seismic interpretation, reservoir characterization and prospect evaluation. I also hold a master’s degree in data analytics and use Python to work through practical subsurface problems.

My recent projects range from machine-learning experiments to tools for extracting and checking Petrel data. I’m especially interested in AI when the work can still be inspected, tested and traced back to the source data.

Selected work

  • Petrel Headless Extractor — extracts supported Petrel project data and metadata into open formats, with reports and QC.
  • Petrel Agent MCP — a version-scoped set of MCP tools for Petrel inspection, export and QC experiments.
  • 3D Seismic Attribute Analytics — notebooks exploring seismic attributes, well controls and porosity modelling.
  • STOIIP Monte Carlo Study — a notebook study of volumetric uncertainty and input sensitivity; the Streamlit interface is still in progress.
  • Data Analytics Capstone — tests whether Bitcoin tweet sentiment was associated with minute-level price changes. The tested models found no practically useful relationship.
  • LLM-assisted Petroleum Review — a controlled text-to-SQL demo with visible schema and query checks.

Data and tools

Python, SQL, pandas, NumPy, scikit-learn, statsmodels, XGBoost, TensorFlow/Keras, Tableau and Power BI.

Pinned Loading

  1. petrel-headless-extractor petrel-headless-extractor Public

    Standalone Windows tool for extracting supported Petrel project data and metadata into open formats, with reports, hashes and QC.

    Python 1

  2. petrel-agent-mcp petrel-agent-mcp Public

    MCP tools for inspecting, exporting and checking Petrel project data without the Ocean SDK, with explicit safety and validation limits.

    Python 3

  3. Seismic_Attributes_3D Seismic_Attributes_3D Public

    Notebook record of seismic-attribute and well-control experiments for porosity modelling, 3D property-volume QC and SEG-Y export.

    Jupyter Notebook

  4. stoiip_app stoiip_app Public

    Notebook-based STOIIP Monte Carlo study with sensitivity analysis and sample ZMAP grids; the Streamlit interface is still a placeholder.

    Jupyter Notebook

  5. LLM-assisted-petroleum-review LLM-assisted-petroleum-review Public

    A controlled text-to-SQL demo for petroleum data, with visible schema limits, query checks and an offline fallback.

    Python