Production Forecast Modeling

A data-driven approach to predict future oil & gas output using historical production, upstream KPIs, and statistical/ML models for better planning and decision-making.

Project Overview:

Build a reproducible pipeline that ingests historical production + upstream KPIs, fits a hybrid forecasting model (physics-informed decline curve + ML/time-series), and exposes scenario-driven forecasts and visual storytelling in a Power BI dashboard.

Tech Stack

1. Data science: Python (pandas, numpy, scikit-learn, xgboost/lightgbm,prophet/NeuralProphet)
2. Dashboard: Matplotlib
3. API / deployment (optional): FastAPI + Docker
4. Storage: CSV / SQL (Postgres) for demo
5. Versioning: Git + GitHub (with clear README)

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