In the 2024 Chevron Rice Datathon, my team and I tackled the challenge of predicting peak oil production rates. We developed a sophisticated Artificial Neural Network using TensorFlow and Keras, focusing on minimizing the Root Mean Squared Error (RMSE). Our approach included meticulous data preprocessing and feature normalization to prepare the dataset, KerasTuner for hyperparameter tuning to optimize the model's performance, and key techniques like dropout regularization and early stopping to enhance accuracy and prevent overfitting.
Predicting Peak Oil Production Rates For Chevron
Developed a neural network to predict peak oil production rates for Chevron. Used TensorFlow/Keras with hyperparameter tuning and achieved high accuracy through feature engineering and regularization techniques.
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