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公开(公告)号:US20230097426A1
公开(公告)日:2023-03-30
申请号:US17936737
申请日:2022-09-29
Applicant: Chevron U.S.A. Inc.
Inventor: Jianlei Sun , Brandon Francis Hruby , Cory Layne Miller , Arvind Reddy Battula
Abstract: A computing system includes a machine learning algorithm executing a machine learning model to predict a probability of a fracture driven interaction associated with a hydrocarbon well. The machine learning algorithm trains the machine learning model using well treatment pumping data, offset well production data, and well stage data. Feature extraction is performed on the pumping data, production data, and well stage data to produce a machine learning model that is used to predict the probability of a fracture driven interaction. The resulting machine learning model can be deployed for use in ongoing hydraulic fracturing operations to predict and reduce real-time fracture driven interactions.