首页|Researchers from China University of Petroleum Detail Findings in Machine Learni ng (Machine Learning for Carbonate Formation Drilling: Mud Loss Prediction Using Seismic Attributes and Mud Loss Records)
Researchers from China University of Petroleum Detail Findings in Machine Learni ng (Machine Learning for Carbonate Formation Drilling: Mud Loss Prediction Using Seismic Attributes and Mud Loss Records)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Research findings on Machine Learning are discussed in a new report. According to news reporting originating in Beijin g, People’s Republic of China, by NewsRx journalists, research stated, “Due to t he complexity and variability of carbonate formation leakage zones, lost circula tion prediction and control is one of the major challenges of carbonate drilling . It raises well -control risks and production expenses.” Financial supporters for this research include National Natural Science Foundati on of China (NSFC), China Postdoctoral Science Foundation.
BeijingPeople’s Republic of ChinaAsiaAlkaliesAnionsCarbonatesCarbonic AcidCyborgsEmerging TechnologiesMachine LearningChina University of Petroleum
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