首页|Findings from Northeast Petroleum University Yields New Data on Machine Learning (Statistical and Machine Learning Hybridization for Predicting Shear Wave Velocity In Tight Sand Reservoirs: a Case Study)
Findings from Northeast Petroleum University Yields New Data on Machine Learning (Statistical and Machine Learning Hybridization for Predicting Shear Wave Velocity In Tight Sand Reservoirs: a Case Study)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Data detailed on Machine Learning have been presented. According to news reportingoriginating in Daqing, People’s Republic of China, by NewsRx journalists, research stated, “Shear wavevelocity plays an important role in describing the reservoir’s petrophysical and geomechanical characteristics.It is also important to understand the mechanical behavior of the reservoir since it is closely related to rockstrength and stiffness.”
DaqingPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningNortheast Petroleum University
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