Comparative analysis of intelligent algorithms to predict the minimum miscibility pressure for hydrocarbon gas flooding

Engineering

• Comparative Analysis 100%
• Natural Gas 100%
• Minimum Miscibility Pressure 100%
• Artificial Neural Network 66%
• Enhanced Oil Recovery 50%
• Support Vector Machine 50%
• Gas Injection 50%
• Reservoir Fluid 33%
• Machine Learning Algorithm 33%
• Microbial 16%
• Reservoir Temperature 16%
• Oil Composition 16%
• Injected Gas 16%
• Multiple Realisation 16%
• Vaporization 16%
• Average Absolute Error 16%
• Light Oil 16%
• Network Support 16%
• Temperature Reservoir 16%
• Tasks 16%
• Gas Composition 16%
• Local Minimum 16%
• Network Model 16%
• Learning Algorithm 16%

Keyphrases

• Hydrocarbon Gas Flooding 100%
• Backward Elimination 16%
• Kernel Parameter 16%
• Immiscible Gas Flooding 16%
• Neuron Weight 16%
• Thermal Injection 16%
• Development Testing 16%
• Chemical Injection 16%
• Correlation Development 16%

Chemical Engineering

• Neural Network 100%
• Support Vector Machine 75%
• Learning System 50%