The optimization of parameters for a circulation loss accident classification model

Mud leakage poses a persistent challenge in drilling operations, necessitating innovative solutions for improved sealing and circulation efficiency. This paper leverages data from the Mullen Field to categorize mud loss severity levels. Employing the Optuna framework, hyperparameter optimization enhances model performance metrics such as precision, recall, and F1-score. Our study underscores the efficacy of hyperparameter tuning in refining predictive models for mud loss severity.