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)
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.
Key words
Beijing/People’s Republic of China/Asia/Alkalies/Anions/Carbonates/Carbonic Acid/Cyborgs/Emerging Technologies/Machine Learning/China University of Petroleum
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