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公开(公告)号：US11674375B2
公开(公告)日：2023-06-13
申请号：US16636317
申请日：2018-11-15
Applicant: Schlumberger Technology Corporation
Inventor： Yingwei Yu , Qiuhua Liu , Richard John Meehan , Sylvain Chambon , Mohammad Khairi Hamzah
IPC: E21B44/00 , E21B21/08 , G06N7/00 , G01V1/50 , E21B49/00 , G01V11/00 , G06F30/20 , G06F17/15 , G06F17/16 , G06F30/27 , G06N3/044 , G06N3/047 , G06N3/08 , G06T13/80
CPC classification number: E21B44/00 , E21B21/08 , E21B49/003 , G01V1/50 , G01V11/00 , G06F17/15 , G06F17/16 , G06F30/20 , G06F30/27 , G06N3/044 , G06N3/047 , G06N3/08 , G06N7/00 , G01V2200/14 , G01V2200/16 , G06T13/80
Abstract: A method can include training a deep neural network to generate a trained deep neural network where the trained deep neural network represents functions of a nonlinear Kalman filter that represents a dynamic system of equipment and environment via an internal state vector of the dynamic system; generating a base internal state vector, that corresponds to a pre-defined operational procedure, using the trained deep neural network; receiving operation data from the equipment responsive to operation in the environment; generating an internal state vector using the operation data and the trained deep neural network; and comparing at least the internal state vector to at least the base internal state vector.
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公开(公告)号：US11421523B2
公开(公告)日：2022-08-23
申请号：US16605799
申请日：2018-06-27
Applicant: Schlumberger Technology Corporation
Inventor： Sai Venkatakrishnan , Sylvain Chambon , James P. Belaskie , Yingwei Yu , Mohammad Khairi Hamzah
Abstract: A method includes acquiring data during rig operations where the rig operations include operations that utilize a bit to drill rock and where the data include different types of data; analyzing the data utilizing a probabilistic mixture model for modes, a detection engine for trends and a network model for an inference based at least in part on at least one of a mode and a trend; and outputting information as to the inference where the inference characterizes a relationship between the bit and the rock.
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公开(公告)号：US20220195861A1
公开(公告)日：2022-06-23
申请号：US17451945
申请日：2021-10-22
Applicant: Schlumberger Technology Corporation
Inventor： Diego Fernando Patino Virano , Darine Mansour , Sai Venkatakrishnan Sankaranarayanan , Yingwei Yu
Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media for dynamically utilizing, in potentially real time, anomaly pattern detection to optimize operational processes relating to well construction or subterranean drilling. For example, the disclosed systems use time-series data combined with rig states to automatically detect and split similar operations. Subsequently, the disclosed systems identify operation anomalies from a field-data collection utilizing an automated anomaly detection workflow. The automated anomaly detection workflow can identify operation anomalies at a more granular level by determining which process behavior contributes to the operation anomaly (e.g., according to corresponding process probabilities for a given operation). In addition, the disclosed systems can present graphical representations of operation anomalies, process behaviors (procedural curves), and/or corresponding process probabilities in an intuitive, user-friendly manner.
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公开(公告)号：US11828155B2
公开(公告)日：2023-11-28
申请号：US16776373
申请日：2020-01-29
Applicant: Schlumberger Technology Corporation
Inventor： Yingwei Yu , Velizar Vesselinov , Richard Meehan , Qiuhua Liu , Wei Chen , Minh Trang Chau , Yuelin Shen , Sylvain Chambon
IPC: E21B44/00 , E21B47/024 , E21B7/04
CPC classification number: E21B44/00 , E21B7/04 , E21B47/024
Abstract: A method can include receiving sensor data during drilling of a portion of a borehole in a geologic environment; determining a drilling mode from a plurality of drilling modes using a trained neural network and at least a portion of the sensor data; and issuing a control instruction for drilling an additional portion of the borehole using the determined drilling mode.
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15.发明公开公开(公告)号：US20230212934A1
公开(公告)日：2023-07-06
申请号：US18000544
申请日：2021-05-27
Applicant: Schlumberger Technology Corporation
Inventor： Cheolkyun Jeong , Yingwei Yu , Velizar Vesselinov , Richard John Meehan , Priya Mishra
CPC classification number: E21B44/00 , E21B47/00 , G01V1/50 , E21B2200/20 , G01V2210/6652 , G01V99/005
Abstract: The present disclosure relates to systems, methods, and non-transitory computer-readable media for dynamically utilizing offset drill-well data generated within a threshold geographic area to determine formation-top trends and identify formation-top depths at a subject drill-well site. To do so, in some embodiments, the disclosed systems estimate a variogram for observed formation-top depths of a subset of offset drill-wells, and, in turn, map a predicted response from the estimated variogram. For example, using weighted combinations (e.g., with Kriging weights) of the formation-top depths of the subset of offset drill-wells, the disclosed systems can map a continuous surface of a formation and identify a top-depth thereof. Moreover, the disclosed system can do so for multiple formations at the subject drill-well site, and (in real-time in response to a user input) provide for display at a client device, the associated formation-top depths, various predicted drilling events and/or predicted drilling metrics.
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Patent Agency Ranking
公开(公告)号：US20230017966A1
公开(公告)日：2023-01-19
申请号：US17811931
申请日：2022-07-12
Applicant: Schlumberger Technology Corporation
Inventor： Gregory Michael Skoff , Crispin Chatar , Velizar Vesselinov , Cheolkyun Jeong , Yingwei Yu , Georgia Kouyialis , Fatma Mahfoudh
Abstract: A method can include receiving input for a drilling operation that utilizes a bottom hole assembly and drilling fluid; generating a set of offset drilling operations using historical feature data, where the historical feature data are processed by computing feature distances; performing an assessment of the offset drilling operations as characterized by at least feature distance-based similarity between the drilling operation and the offset drilling operations; and outputting at least one recommendation for selection of one or more of a component of the bottom hole assembly and the drilling fluid based on the assessment.
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公开(公告)号：US20210285316A1
公开(公告)日：2021-09-16
申请号：US16605799
申请日：2018-06-27
Applicant: Schlumberger Technology Corporation
Inventor： Sai Venkatakrishnan , Sylvain Chambon , James P. Belaskie , Yingwei Yu , Mohammad Khairi Hamzah
Abstract: A method includes acquiring data during rig operations where the rig operations include operations that utilize a bit to drill rock and where the data include different types of data; analyzing the data utilizing a probabilistic mixture model for modes, a detection engine for trends and a network model for an inference based at least in part on at least one of a mode and a trend; and outputting information as to the inference where the inference characterizes a relationship between the bit and the rock
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公开(公告)号：US20190147125A1
公开(公告)日：2019-05-16
申请号：US16192584
申请日：2018-11-15
Applicant: Schlumberger Technology Corporation
Inventor： Yingwei Yu , Sylvain Chambon , Qiuhua Liu
Abstract: A method can include receiving multi-channel time series data of drilling operations; training a deep neural network (DNN) using the multi-channel time series data to generate a trained deep neural network as part of a computational simulator where the deep neural network includes at least one recurrent unit; simulating a drilling operation using the computational simulator to generate a simulation result; and rendering the simulation result to a display.
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公开(公告)号：US20190145239A1
公开(公告)日：2019-05-16
申请号：US16192609
申请日：2018-11-15
Applicant: Schlumberger Technology Corporation
Inventor： Yingwei Yu , Qiuhua Liu , Richard Meehan , Sylvain Chambon , Mohammad Hamzah
Abstract: A method can include receiving channels of data from equipment responsive to operation of the equipment in an environment where the equipment and environment form a dynamic system; defining a particle filter that localizes a time window with respect to the channels of data; applying the particle filter at least in part by weighting particles of the particle filter using the channels of data, where each of the particles represents a corresponding time window; and selecting one of the particles according to its weight as being the time window of an operational state of the dynamic system.
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公开(公告)号：US12252975B2
公开(公告)日：2025-03-18
申请号：US18331269
申请日：2023-06-08
Applicant: Schlumberger Technology Corporation
Inventor： Yingwei Yu , Velizar Vesselinov , Richard Meehan , Qiuhua Liu , Wei Chen , Minh Trang Chau , Yuelin Shen , Sylvain Chambon
IPC: E21B44/00 , E21B7/04 , E21B47/024
Abstract: A system and method that include receiving sensor data during drilling of a portion of a borehole in a geologic environment. The system and method also include selecting a drilling mode from a plurality of drilling modes based at least on a portion of the sensor data. The system and method additionally include simulating drilling of the borehole using the selected drilling mode and generating a state of the borehole in the geologic environment based on the simulated drilling of the borehole. The system and method further include generating a reward using the state of the borehole and a planned borehole trajectory and using the reward through deep reinforcement learning to maximize future rewards for drilling actions.
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