Predicting well cement integrity using open-hole logging and borehole survey data: a novel machine learning approach

Puntos clave

• To predict the integrity of well cement utilizing open-hole logging and borehole survey data through machine learning techniques.
• Implemented a machine learning algorithm to analyze data from open-hole logging and borehole surveys.
• Collected and processed input features relevant to cement integrity.
• Evaluated model performance against traditional prediction methods.
• Achieved higher prediction accuracy compared to conventional methods.
• Identified key variables impacting well cement integrity.
• Demonstrated the feasibility of using machine learning for real-time assessments.