首页|Findings from Texas A&M University Update Understanding of Machine Learning (Optimizing Minimum Miscibility Pressure Prediction Using Machine Learning: a Comprehensive Evaluation and Validation)
Findings from Texas A&M University Update Understanding of Machine Learning (Optimizing Minimum Miscibility Pressure Prediction Using Machine Learning: a Comprehensive Evaluation and Validation)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on Machine Learning is now available. According to news reporting out of College Station, Texas, by NewsRx editors, research stated, “This study provides the proof-of-concept for identifying the most suitable machine-learning (ML) model that predicts minimum miscibility pressure (MMP) based on temperature, crude oil, and injected fluid composition. MMP defined as the lowest pressure injected gas developing miscibility with reservoir oil is crucial for gas-enhanced oil recovery.”
College StationTexasUnited StatesNorth and Central AmericaCyborgsEmerging TechnologiesMachine LearningTexas A&M University
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