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公开(公告)号：US12229689B2
公开(公告)日：2025-02-18
申请号：US17248836
申请日：2021-02-10
Applicant: Schlumberger Technology Corporation
Inventor： Prasanna Amur Varadarajan , Maurice Ringer
Abstract: A method includes receiving first input values for a first parameter of a physical system, calculating first modeled values for a second parameter using a model that represents the physical system, based on the first input values, receiving measured values for the second parameter, training a machine learning model to adjust modeled values generated by the model based on a difference between the first modeled values and the measured values, receiving second input values for the first parameter, calculating second modeled values for the second parameter using the model, generating adjusted values for the second parameter by adjusting the second modeled values using the trained machine learning model, and visualizing the adjusted values for the second parameter as representing operation of the physical system.
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公开(公告)号：US20250052147A1
公开(公告)日：2025-02-13
申请号：US18720793
申请日：2023-01-30
Applicant: Schlumberger Technology Corporation
Inventor： Prashanth Pillai , Maurice Ringer , Purnaprajna Mangsuli , Vladimir Skvortsov
Abstract: A method includes receiving historical well data comprising trajectories, performance data, and one or more drilling parameters for a plurality of wells, clustering at least a portion of the plurality of wells into a plurality of clusters based on the trajectories, using a machine learning model, receiving trajectory data for a subject well, identifying one of the clusters based on the trajectory data of the subject well, using the machine learning model, selecting one or more of the plurality of wells, or one or more sections thereof, in the cluster that was identified based on the performance data associated with the one or more of the plurality of wells or the portion thereof, and visualizing the selected one or more of the plurality of wells or one or more sections thereof.
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公开(公告)号：US20150184504A1
公开(公告)日：2015-07-02
申请号：US14406223
申请日：2013-06-20
Applicant: Schlumberger Technology Corporation
Inventor： Maurice Ringer , Qiuhua Liu , Richard V.C. Wong , Jonathan Dunlop , Kais B. M. Gzara , Iain M. Cooper
CPC classification number: E21B47/10 , E21B4/02 , E21B21/08 , E21B47/1025
Abstract: A method for detecting a drill string washout event. The method includes locating a drill string in a wellbore formed in a subterranean formation. A drilling fluid is pumped into the drill string. The drill string includes a turbine that spins in response to the drilling fluid flowing therethrough. A comparison is made between a rate that the drilling fluid is pumped into the drill string and a spin rate of the turbine. A defect is determined to be formed in the drill string based upon the comparison.
Abstract translation: 一种用于检测钻柱冲洗事件的方法。 该方法包括将钻柱定位在形成于地层中的井眼中。 钻井液被泵送到钻柱中。 钻柱包括响应于钻进流体流过其而旋转的涡轮机。 比较钻井液被泵送到钻柱中的速率和涡轮的旋转速率。 基于比较，确定在钻柱中形成缺陷。
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公开(公告)号：US20250148319A1
公开(公告)日：2025-05-08
申请号：US19012975
申请日：2025-01-08
Applicant: Schlumberger Technology Corporation
Inventor： Prasanna Amur Varadarajan , Maurice Ringer
Abstract: A method includes receiving first input values for a first parameter of a physical system, calculating first modeled values for a second parameter using a model that represents the physical system, based on the first input values, receiving measured values for the second parameter, training a machine learning model to adjust modeled values generated by the model based on a difference between the first modeled values and the measured values, receiving second input values for the first parameter, calculating second modeled values for the second parameter using the model, generating adjusted values for the second parameter by adjusting the second modeled values using the trained machine learning model, and visualizing the adjusted values for the second parameter as representing operation of the physical system.
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公开(公告)号：US20220341308A1
公开(公告)日：2022-10-27
申请号：US17812204
申请日：2022-07-13
Applicant: Schlumberger Technology Corporation
Inventor： Samba Ba , Conie Chiock , Ginger Hildebrand , Maurice Ringer
IPC: E21B44/00 , E21B7/04 , E21B47/024
Abstract: A computer-implemented method including receiving a steering command identifying a tool face orientation in which the steering command is expected to produce an intended steering response of an intended drilling trajectory. The method further includes receiving an actual steering response result of the steering command in which the actual steering response result identifies an actual drilling trajectory. The method further includes storing a dataset comparing the actual steering response result in relation to the intended steering response, determining an uncertainty level of the tool face orientation based on the stored dataset, and outputting a visual representation of steering response with the uncertainty level.
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Patent Agency Ranking
公开(公告)号：US20210108511A1
公开(公告)日：2021-04-15
申请号：US17037878
申请日：2020-09-30
Applicant: Schlumberger Technology Corporation
Inventor： Sophie Androvandi , Maurice Ringer , Karim Bondabou
Abstract: The disclosure relates to a first method for determining a lithology of a subterranean formation into which a wellbore has been drilled. The method comprises receiving a set of measurement logs comprising one or more measurement logs, each representing a measured characteristic of the wellbore plotted according to depth. The measured characteristic include at least cuttings percentage and one or more additional measured characteristics. The method also includes segmenting the wellbore into regions based on identified change of trend in one or more of the measurement logs of the set, and sub-segmenting at least one region into zones based on detection of appearance or disappearance of a rock type in the cuttings percentage log, The method also includes determining, in each zone, a location, length and rock type of one or more layers based on a total percentage of each rock type in the zone in the cuttings percentage log and at least one of the additional measurement logs.
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公开(公告)号：US10473816B2
公开(公告)日：2019-11-12
申请号：US14763811
申请日：2014-03-24
Applicant: Schlumberger Technology Corporation
Inventor： James P Belaskie , Jonathan Dunlop , Jose Luis Sanchez , Richard John Harmer , Maurice Ringer , CuiLi Yang
IPC: G01V13/00 , E21B47/022 , E21B7/10 , E21B47/00 , E21B47/06
Abstract: A calibration quality associated with a well-drilling apparatus can be determined. A projected value and a calculated value based upon a data set corresponding to a time interval section of a rig state of the well-drilling apparatus can be determined. A difference can be calculated between the projected value and the calculated value. A quality indicator can be applied to the difference, and a calibration quality based upon the application of the quality indicator can be determined.
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公开(公告)号：US20180171774A1
公开(公告)日：2018-06-21
申请号：US15846661
申请日：2017-12-19
Applicant: Schlumberger Technology Corporation
Inventor： Maurice Ringer , Sophie Androvandi
IPC: E21B44/00 , E21B41/00 , E21B47/024 , E21B47/00
CPC classification number: E21B44/00 , E21B7/04 , E21B41/0092 , E21B47/0002 , E21B47/024 , E21B47/18 , E21B49/003
Abstract: A method includes receiving information during a drilling operation for a drillstring disposed in a bore in a formation; estimating uncertainty associated with the information; analyzing at least a portion of the information using a physics-based model to generate a result; computing, via a Bayesian network, a risk probability of the drilling string sticking in the bore in the formation based at least in part on the result and the estimated uncertainty; and, based at least in part on the risk probability, issuing a signal.
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公开(公告)号：US20220026596A1
公开(公告)日：2022-01-27
申请号：US17450419
申请日：2021-10-08
Applicant: Schlumberger Technology Corporation
Inventor： Cheolkyun Jeong , Francisco Jose Gomez , Maurice Ringer , Paul Bolchover , Paul Muller
Abstract: A method, computing system, and non-transitory computer-readable medium, of which the method includes receiving offset well data collected while drilling one or more offset wells, generating a machine learning model configured to predict drilling risks from drilling measurements or inferences, based on the offset well data, receiving drilling parameters for a new well, determining that the drilling parameters are within an engineering design window, generating a drilling risk profile for the new well using the machine learning model, and adjusting one or more of the drilling parameters for the new well, after determining the drilling parameters are within the engineering design window, and after determining the drilling risk profile, based on the drilling risk profile.
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公开(公告)号：US20210248500A1
公开(公告)日：2021-08-12
申请号：US17248836
申请日：2021-02-10
Applicant: Schlumberger Technology Corporation
Inventor： Prasanna Amur Varadarajan , Maurice Ringer
Abstract: A method includes receiving first input values for a first parameter of a physical system, calculating first modeled values for a second parameter using a model that represents the physical system, based on the first input values, receiving measured values for the second parameter, training a machine learning model to adjust modeled values generated by the model based on a difference between the first modeled values and the measured values, receiving second input values for the first parameter, calculating second modeled values for the second parameter using the model, generating adjusted values for the second parameter by adjusting the second modeled values using the trained machine learning model, and visualizing the adjusted values for the second parameter as representing operation of the physical system.
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