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1.发明授权公开(公告)号：US11790170B2
公开(公告)日：2023-10-17
申请号：US16740066
申请日：2020-01-10
Applicant: Chevron U.S.A. Inc. , CALIFORNIA INSTITUTE OF TECHNOLOGY
Inventor： Asitang Mishra , Shuxing Cheng , Annie Didier , Chris Mattmann , Hamsa Shwetha Venkataram , Grant Lee , Wayne Moses Burke , Vishal Lall
IPC: G06F40/295 , G06N20/00 , G06F40/205 , G06F40/284 , G06F40/30
CPC classification number: G06F40/295 , G06F40/205 , G06F40/284 , G06N20/00 , G06F40/30
Abstract: A computer-implemented, machine learning-based method of converting an unstructured technical report into a structured technical report includes obtaining an unstructured technical report, tokenizing the unstructured technical report into an n-gram array, identifying and filtering non-interesting n-grams from the first n-gram array based on common language usage of the non-interesting n-grams and a determination that the non-interesting n-grams do not appear on a confirmed technical entity database, generating and displaying a technical entity candidate list from the filtered n-gram array, displaying, obtaining, from a pattern matching model and/or a graphical user interface, an indication that a technical entity candidate is a technical entity of interest, appending the technical entity of interest to the confirmed technical entity database, generating and displaying a structured technical report with the confirmed technical entities and corresponding technical entity value parameters, and iterating the process to refine the pattern matching model.
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2.发明申请公开(公告)号：US20200226325A1
公开(公告)日：2020-07-16
申请号：US16740066
申请日：2020-01-10
Applicant: Chevron U.S.A. Inc. , CALIFORNIA INSTITUTE OF TECHNOLOGY
Inventor： Asitang Mishra , Shuxing Cheng , Annie Didier , Chris Mattmann , Hamsa Shwetha Venkataram , Grant Lee , Wayne Moses Burke , Vishal Lall
IPC: G06F40/295 , G06N20/00 , G06F40/284 , G06F40/205
Abstract: A computer-implemented, machine learning-based method of converting an unstructured technical report into a structured technical report includes obtaining an unstructured technical report, tokenizing the unstructured technical report into an n-gram array, identifying and filtering non-interesting n-grams from the first n-gram array based on common language usage of the non-interesting n-grams and a determination that the non-interesting n-grams do not appear on a confirmed technical entity database, generating and displaying a technical entity candidate list from the filtered n-gram array, displaying, obtaining, from a pattern matching model and/or a graphical user interface, an indication that a technical entity candidate is a technical entity of interest, appending the technical entity of interest to the confirmed technical entity database, generating and displaying a structured technical report with the confirmed technical entities and corresponding technical entity value parameters, and iterating the process to refine the pattern matching model.
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公开(公告)号：US11231513B2
公开(公告)日：2022-01-25
申请号：US15833203
申请日：2017-12-06
Applicant: CHEVRON U.S.A. INC.
Inventor： Adam Dean Halpert , Laura L. Bandura , Shuxing Cheng , Konstantin Osypov
Abstract: Systems and methods for training a model that refines estimated parameter values include computer processors and non-transitory electronic storage that stores subsurface map data sets that correspond to different subsurface volumes of interest, the system configured to obtain training data including unrefined subsurface map data sets specifying estimated parameter values of a first parameter as a function of position within corresponding subsurface volumes of interest, obtain an initial seismic mapping model, generate a conditioned seismic mapping model, and store the conditioned seismic mapping model in the electronic storage.
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公开(公告)号：US11295123B2
公开(公告)日：2022-04-05
申请号：US16131946
申请日：2018-09-14
Applicant: CHEVRON U.S.A. INC.
Inventor： Paul Duke , Shuxing Cheng
Abstract: Systems and methods for categorizing patterns of characters in a document by utilizing machine based learning techniques include generating character classification training data, building a character classification model based on the character classification training data; obtaining an image that includes a pattern of characters, the characters including one or more contours, applying the character classification model to the image to classify the contours, and applying the labels to clusters of the contours.
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公开(公告)号：US20210390335A1
公开(公告)日：2021-12-16
申请号：US17344033
申请日：2021-06-10
Applicant: Chevron U.S.A. Inc. , University of Houston System
Inventor： Xunsheng Du , Shuxing Cheng , Christian E. Haselwimmer , Zhu Han
Abstract: A synthetic image of a target is generated and combined with an image of a background to generate a synthetic training image for the target. The synthetic image of the target is inserted as a patch into the background image. The synthetic training image for the target is labeled as including a depiction of the target based on insertion of the synthetic training image into the background image. The location in which the target is depicted in the synthetic training image is automatically determined based on the location into which the synthetic image of the target is inserted into the background image.
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Patent Agency Ranking
公开(公告)号：US11195007B2
公开(公告)日：2021-12-07
申请号：US16376827
申请日：2019-04-05
Applicant: CHEVRON U.S.A. INC.
Inventor： Paul Duke , Shuxing Cheng
Abstract: Systems and methods for identifying patterns of symbols in standardized system diagrams are disclosed. Disclosed implementations obtain or synthetically generate a symbol recognition training data set including multiple training images, generate a symbol recognition model based on the symbol recognition training data set, obtain an image comprising a pattern of symbols, group symbols into process loops based on the logical relationships captured by process loop identification algorithm, apply a character classification model to image contours to identify the characters and group characters into tags via hierarchical clustering, and store the identified tags, symbols and identified process loops in a relational database.
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公开(公告)号：US20240427968A1
公开(公告)日：2024-12-26
申请号：US18338972
申请日：2023-06-21
Applicant: Chevron U.S.A. Inc.
Inventor： Yixiong Ma , Shuxing Cheng , Wangming Lu
Abstract: Metocean conditions for a wellhead, such as current profile and wave characteristics, are used to determine wellhead fatigue damage rate for the wellhead. The wellhead fatigue damage rate is determined using an interpolation approach or an extrapolation approach. In the interpolation approach, the metocean conditions of the wellhead are input into one of multiple clustered machine learning models to determine the wellhead fatigue damage rate. In the extrapolation approach, a curve is generated to fit cluster centers of the multiple clustered machine learning models, and the wellhead fatigue damage rate is determined based on the curve and the distance between the metocean conditions of the wellhead and null metocean conditions.
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公开(公告)号：US20210312311A1
公开(公告)日：2021-10-07
申请号：US16837774
申请日：2020-04-01
Applicant: Chevron U.S.A. Inc.
Inventor： Larry A. Bowden, JR. , Juan Esteban E. Montero , Shuxing Cheng , Adam M. Reeder , Xin Feng , Steven R. Szabo
IPC: G06N7/00 , G06F16/901 , G06F30/17 , G06F30/20 , G06N20/00
Abstract: A requirements knowledge graph may include nodes for different elements of a requirement's relationship to physical characteristics, such as the requirement and the associated unsafe conditions, control objects, and hazards. A connection between nodes may define a relationship between the corresponding elements. The requirement, that is decomposed into a subject, an object, a predicate, and a context, may define a rule for the control object in the unsafe condition to avoid the hazard. A model for a plan (e.g., drilling plan for a well, design for a drilling tool) may be constructed based on the requirements knowledge graph. The plan may be generated based on the model.
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公开(公告)号：US20220035069A1
公开(公告)日：2022-02-03
申请号：US16945517
申请日：2020-07-31
Applicant: CHEVRON U.S.A. INC. , THE TEXAS A&M UNIVERSITY SYSTEM
Inventor： Shuxing Cheng , Zhao Zhang , Kellen Leigh Gunderson , Reynaldo Cardona , Zhangyang Wang , Ziyu Jiang
Abstract: Systems and methods are disclosed for identifying subsurface features as a function of position in a subsurface volume of interest. Exemplary implementations may include obtaining target subsurface data; obtaining a conditioned subsurface feature model; applying the conditioned subsurface feature model to the target subsurface data, which may include generating convoluted target subsurface data by convoluting the target subsurface data; generating target subsurface feature map layers by applying filters to the convoluted target subsurface data; detecting potential target subsurface features in the target subsurface feature map layers; masking the target subsurface features; and estimating target subsurface feature data by linking the masked subsurface features to the target subsurface feature data.
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公开(公告)号：US20220035068A1
公开(公告)日：2022-02-03
申请号：US16945486
申请日：2020-07-31
Applicant: CHEVRON U.S.A. INC.
Inventor： Shuxing Cheng , Zhao Zhang , Kellen Leigh Gunderson , Reynaldo Cardona
Abstract: Systems, devices, and methods are disclosed for identifying subsurface features as a function of position in a subsurface volume of interest. A computer-implemented method may include obtaining training subsurface data and corresponding training subsurface feature data; obtaining an initial subsurface feature model including tiers of elements; generating a conditioned subsurface feature model by training the initial subsurface feature model using the training subsurface data and the corresponding training subsurface feature data; and storing the conditioned subsurface feature model in the non-transient electronic storage.
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