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Machine Learning Unlocks Potential of Mud Logs, LWD in the Gulf of Thailand

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Application of machine learning predicts well logs in the Gulf of Thailand, suggesting potential cost savings.

Predictive models using machine learning can significantly reduce well-log fees and rig time.
Analyzing mud logs and LWD data aims to forecast bulk density, neutron porosity, and compressional sonic travel time.
Data preprocessing and model selection are crucial steps for enhancing the predictive performance of machine learning techniques.
Evaluation metrics like R-squared and mean absolute error determine the effectiveness of the predictive models.

Chris Carpenter (2025) studied this question.

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