首页|Researchers from China University of Petroleum Describe Findingss in Machine Learning (A Real-time Drilling Parameters Optimizations Method for Offshore Large-scale Cluster Extended Reach Drillings Based On Intelligent Optimization Algorithm and …)
Researchers from China University of Petroleum Describe Findingss in Machine Learning (A Real-time Drilling Parameters Optimizations Method for Offshore Large-scale Cluster Extended Reach Drillings Based On Intelligent Optimization Algorithm and …)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – Data detailed on Machine Learning have been presented. According to news reporting out ofBeijing, People’s Republic of China, by NewsRx editors, research stated, “Offshore large-scale clusterextended reach wells (ERWs) are widely used to develop offshore oil & gas resources. Due to the complexdownhole environments and complicated geological conditions, drilling parameters real-time optimizationis challenging in offshore large-scale cluster ERWs drilling.”
BeijingPeople’s Republic of ChinaAsiaAlgorithmsCyborgss Emerging TechnologiesMachine LearningChina University of Petroleum
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