首页|Recent Research from Northeast Petroleum University Highlight Findings in Machin e Learning (Machine Learning for Optimal Ultrafine Cement Plugging System In Si mulated High Permeability Sandstone Reservoirs)
Recent Research from Northeast Petroleum University Highlight Findings in Machin e Learning (Machine Learning for Optimal Ultrafine Cement Plugging System In Si mulated High Permeability Sandstone Reservoirs)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on Machine Learning are pre sented in a new report. According to news reporting from Daqing, People’s Republ ic of China, by NewsRx journalists, research stated, “The properties of a cement system dictate its potential applications, yet creating a reliable cement plugg ing system with controllable setting times, robust injection capacity, and high compressive strength often requires a lot of time and resources in advanced oilf ield development. To address this issue, a machine learningbased XGBoost model was created to optimize plugging system performance, reduce costs, and enhance e fficiency by analysing the initial setting time, final setting time, viscosity, and compressive strength of ultra-fine cement.” Financial supporters for this research include PetroChina Innovation Foundation, Opening Project Foundation of State Key Laboratory of Inorganic Synthesis and P reparative Chemistry of Jilin University.
DaqingPeople’s Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine LearningNortheast Petroleum Universi ty
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