Machine learning - based shale wettability prediction: Implications for H₂, CH₄ and CO₂ geo-storage

Keyphrases

• Machine Learning Based 100%
• CO2 Geo-storage 100%
• Shale Wettability 100%
• Brine 33%
• Shapley Additive Explanations 33%
• Storage Methods 16%
• Prediction Accuracy 16%
• Hydrophobicity 16%
• Contact Angle 16%
• Energy Security 16%
• Machine Learning Techniques 16%
• Ionic Strength 16%
• Sensitivity Analysis 16%
• Total Organic Carbon 16%
• Shale 16%
• Shale Gas 16%
• Multiple Linear Regression 16%
• Climate Change Mitigation 16%
• Partial Least Squares Regression Model 16%
• Storage Efficiency 16%
• Extreme Gradient Boosting(XGBoost) 16%
• Gas Recovery 16%
• XGBoost Model 16%
• Geo-storage 16%
• Calcite Content 16%
• Quartz Content 16%
• Multi-influencing Factor 16%
• Gas Productivity 16%
• Carbon Gases 16%

Engineering

• Methane 100%
• Influencing Factor 100%
• Energy Security 50%
• Ionic Strength 50%
• Climate Change 50%
• Machine Learning Method 50%
• Molecular Weight 50%
• Total Organic Carbon 50%
• Shale Gas 50%
• Partial Least-Squares Regression Model 50%

Chemical Engineering

• Learning System 100%
• Methane 100%
• Organic Carbon 50%
• Calcite 50%