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公开(公告)号:US20230349269A1
公开(公告)日:2023-11-02
申请号:US17730975
申请日:2022-04-27
CPC分类号: E21B43/123 , E21B33/10
摘要: A production well has nested casings including a first production casing and a first production tubing installed within the first production casing, which extends from a surface to a depth within the wellbore. Before implementing a gas-lift operation in the production well, the first production tubing is removed. A second production casing is lowered within the first production casing. The second production casing has a smaller outer diameter than an inner diameter of the first production casing. From the surface of the wellbore to the depth within the wellbore to which the second production casing extends, the inner diameter of the second production casing is expanded until an outer wall of the second production casing forms a gas-tight seal with an inner wall of the first production casing.
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公开(公告)号:US12000247B2
公开(公告)日:2024-06-04
申请号:US17730975
申请日:2022-04-27
CPC分类号: E21B43/103 , E21B33/10 , E21B43/123
摘要: A production well has nested casings including a first production casing and a first production tubing installed within the first production casing, which extends from a surface to a depth within the wellbore. Before implementing a gas-lift operation in the production well, the first production tubing is removed. A second production casing is lowered within the first production casing. The second production casing has a smaller outer diameter than an inner diameter of the first production casing. From the surface of the wellbore to the depth within the wellbore to which the second production casing extends, the inner diameter of the second production casing is expanded until an outer wall of the second production casing forms a gas-tight seal with an inner wall of the first production casing.
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3.
公开(公告)号:US20240328303A1
公开(公告)日:2024-10-03
申请号:US18194053
申请日:2023-03-31
IPC分类号: E21B47/008
CPC分类号: E21B47/008 , E21B2200/22
摘要: A method for predicting a lifespan of an electric submersible pump (ESP) involves obtaining data associated with the ESP, the data originating from different categories, predicting, using a machine learning model, based on the data, a remaining expected life of the ESP, and reporting the remaining expected life.
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