Hharkheem/SPE-DSEAT-Africa-Datathon-2024-

This project is a submission for the SPE Data Science and Engineering Analytics Technical Section (DSEAT) Africa Datathon 2024. The goal of the competition is to build a robust machine learning model that accurately predicts oil, gas, and water production based on historical well production data. # SPE DSEAT Africa Datathon 2024 Submission **Author**: Hakeem Salifu **SPE Number**: 5554170 **Category**: Student **Affiliation**: KNUST **Course of Study**: Petroleum Engineering **Date**: July 2024 --- ## 🔍 Project Title **Prediction of Oil, Gas & Water Production in the DSEATS Field Using Machine Learning** --- ## 📘 Overview This project is a submission for the **SPE Data Science and Engineering Analytics Technical Section (DSEAT) Africa Datathon 2024**. The goal of the competition is to build a robust machine learning model that accurately predicts oil, gas, and water production based on historical well production data. --- ## 📊 Challenge Objective The main objective of this datathon is to: - Analyze historical production data from a synthetic oil field. - Develop a machine learning model that can predict oil, gas, and water production. - Evaluate the model based on prediction accuracy, innovation, and creativity. --- ## 🧠 Machine Learning Approach The approach follows a complete ML workflow: 1. **Data Preprocessing**: Cleaning and preparing training and validation datasets. 2. **Exploratory Data Analysis (EDA)**: Understanding feature distributions and correlations. 3. **Feature Engineering**: Transforming and creating features to improve model performance. 4. **Model Development**: Training multiple regression models and tuning hyperparameters. 5. **Evaluation**: Using metrics like RMSE, MAE, and R² to assess performance. 6. **Prediction**: Generating forecasts for the validation dataset. --- ## 📁 Repository Contents | File Name | Description | |----------|-------------| | `Hakeem_Salifu_2024_DSEATS_Datathon_5554170.ipynb` | Jupyter notebook containing full ML pipeline | | `Hakeem_Salifu_2024_DSEATS_Datathon_5554170.csv` | Final predicted production results (oil, gas, water) | --- ## 📈 Model Evaluation Criteria - **Effectiveness of ML techniques** - **Prediction accuracy (RMSE, MAE, R²)** - **Total production estimation (forecast + histor …