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公开(公告)号：US20200309982A1
公开(公告)日：2020-10-01
申请号：US16815378
申请日：2020-03-11
Applicant: ConocoPhillips Company
Inventor： Ge Jin , Kevin Mendoza , Baishali Roy , Darryl G. Buswell
Abstract: Various aspects described herein relate to a machine learning based detecting of fracture hits in offset monitoring wells when designing hydraulic fracturing processes for a particular well. In one example, a computer-implemented method includes receiving a set of features for a first well proximate to a second well, the second well undergoing a hydraulic fracturing process for extraction of natural resources from underground formations; inputting the set of features into a trained neural network; and providing, as output of the trained neural network, a probability of a fracture hit at a location associated with the set of features in the first well during a given completion stage of the hydraulic fracturing process in the second well.
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公开(公告)号：US11768307B2
公开(公告)日：2023-09-26
申请号：US16815378
申请日：2020-03-11
Applicant: ConocoPhillips Company
Inventor： Ge Jin , Kevin Mendoza , Baishali Roy , Darryl G. Buswell
CPC classification number: G01V1/50 , E21B47/14 , G02B6/4401 , G06F17/18 , G06N3/084 , G06N20/00 , G01V2210/646
Abstract: Various aspects described herein relate to a machine learning based detecting of fracture hits in offset monitoring wells when designing hydraulic fracturing processes for a particular well. In one example, a computer-implemented method includes receiving a set of features for a first well proximate to a second well, the second well undergoing a hydraulic fracturing process for extraction of natural resources from underground formations; inputting the set of features into a trained neural network; and providing, as output of the trained neural network, a probability of a fracture hit at a location associated with the set of features in the first well during a given completion stage of the hydraulic fracturing process in the second well.
