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1.发明公开公开(公告)号：US20240287860A1
公开(公告)日：2024-08-29
申请号：US18572551
申请日：2022-06-20
发明人： Tianxiang SU , Philippe Michel Jacques TARDY , Vassilis VARVEROPOULOS , Laurence Cathy FOSSATI , Jordi Juan SEGURA DOMINGUEZ , Stephane GEORGET , Filip DVORAK
摘要： Systems and methods presented herein facilitate coiled tubing operations, and generally relate to the use of mechanical models for the automation of such coiled tubing operations in the oil and gas industry. In particular, a framework is presented that includes three main building blocks: (1) a probabilistic tubing force and depth estimation package; (2) an anomaly detection package; and (3) a mechanical failure check package, each of which are software packages executable by a surface processing system.
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公开(公告)号：US20240287883A1
公开(公告)日：2024-08-29
申请号：US18570709
申请日：2022-06-20
发明人： Philippe Michel Jacques TARDY , Jordi Juan SEGURA DOMINGUEZ , Vassilis VARVEROPOULOS , Tianxiang SU , Laurence Cathy FOSSATI , Filip DVORAK , Stephane GEORGET
IPC分类号： E21B43/12
CPC分类号： E21B43/129 , E21B2200/20
摘要： Systems and methods presented herein facilitate coiled tubing operations, and generally relate to the use of flow modeling to generate flow-related data that cannot be measured in order to take re-al-time decisions and real-time predictions on the outcome of future potential actions to be taken by engineers or artificial intelligence to optimize operation performance together with a general method for parameter inference for any uncertain parameters deemed important when designing cleanout operations. In certain situations, a pre-conditioning method for the determination of a reservoir pressure parameter may be used to reduce the effect of its uncertainty on design fidelity. In addition, in certain situations, a pre-conditioning method for the determination of a reservoir inflow performance parameter may be used to reduce the effect of its uncertainty on design fidelity.
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3.发明公开公开(公告)号：US20240287859A1
公开(公告)日：2024-08-29
申请号：US18572457
申请日：2022-06-20
发明人： Filip DVORAK , Vassilis VARVEROPOULOS , Philippe Michel Jacques TARDY , Jordi Juan SEGURA DOMINGUEZ , Tianxiang SU , Laurence Cathy FOSSATI , Stephane GEORGET
CPC分类号： E21B19/22 , G06F30/28 , E21B2200/20
摘要： Systems and methods presented herein facilitate coiled tubing operations, and generally relate to coiled tubing simulators that capture decades of expertise. In particular, the various simulators are formulated as a simulator graph search problem that enables optimal querying of the simulators (e.g., maximizing confidence and efficiency). The representation for a simulator graph is built and integrated with AI planning, constraint satisfaction programming (CSP), reinforcement learning (RL), and execution, which includes three main steps: (1) creation of a simulator graph that encodes the relations between inputs and outputs of different simulators. (2) integration of the simulator graph with an AI planner, CSP and RL, and (3) plan execution and monitoring of the plan with dynamic re-planning, as needed.
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