首页|Reports Summarize Machine Learning Study Results from University of Oklahoma (Re al-Time Lithology Prediction at the Bit Using Machine Learning)
Reports Summarize Machine Learning Study Results from University of Oklahoma (Re al-Time Lithology Prediction at the Bit Using Machine Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New study results on artificial intell igence have been published. According to news reporting originating from Norman, Oklahoma, by NewsRx correspondents, research stated, “Real-time drilling analys is requires knowledge of lithology at the drill bit. However, logging-while-dril ling (LWD) sensors in the bottom hole assembly (BHA) are usually positioned 2-50 m (7-164 ft) above the bit (called the sensor offset), leading to a delay in re al-time drilling analysis.” Financial supporters for this research include Akerbp Asa; University of Oklahom a’s Office of The Vice President For Research And Partnerships And The Office of The Provost.
University of OklahomaNormanOklahomaUnited StatesNorth and Central AmericaCyborgsEmerging TechnologiesMach ine Learning
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