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公开(公告)号：US20250005443A1
公开(公告)日：2025-01-02
申请号：US18345113
申请日：2023-06-30
Applicant: SAUDI ARABIAN OIL COMPANY
Inventor： Mokhles M. Mezghani , Tao Lin , Chicheng Xu , Weichang Li
IPC: G06N20/00
Abstract: A method for analyzing rock cores of a subterranean formation is disclosed. The method includes capturing core images of the rock cores that are collected from geographical locations in the subterranean formation, generating, by a computer processor and from the core images, sub-images by sub-dividing each of the core images, classifying, using a secondary machine learning model that automatically identifies artifacts induced from preparation of the rock cores, the sub-images into artifact-free sub-images and artifact-containing sub-images, and analyzing, using a primary machine learning model, the artifact-free sub-images to generate a core analysis result.
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公开(公告)号：US20250129704A1
公开(公告)日：2025-04-24
申请号：US18490457
申请日：2023-10-19
Applicant: Saudi Arabian Oil Company
Inventor： Weichang Li , Chicheng Xu , Tao Lin
IPC: E21B47/002 , G06T7/00
Abstract: Example computer-implemented methods, media, and systems for identification and characterization of geologic features in carbonate reservoir are disclosed. One example computer-implemented method includes obtaining multiple core sample images of a carbonate reservoir. The multiple core sample images are labeled using multiple feature classes, where the multiple feature classes include at least one of a vug or fracture. Multiple image patches are generated using the labeled plurality of core sample images. A machine learning model is applied to the multiple image patches to identify one or more vugs or fractures in the multiple core sample images. At least one of porosity or permeability of the carbonate reservoir is predicted using the identified one or more vugs or fractures in the multiple core sample images.
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公开(公告)号：US20230186069A1
公开(公告)日：2023-06-15
申请号：US17547112
申请日：2021-12-09
Applicant: Saudi Arabian Oil Company
Inventor： Chicheng Xu , Tao Lin , Lei Fu , Weichang Li , Yaser Alzayer
IPC: G06N3/08 , G06N3/04 , G06K9/62 , G06F16/9035 , G06F16/909
CPC classification number: G06N3/08 , G06N3/0454 , G06K9/6228 , G06F16/9035 , G06F16/909
Abstract: Systems, methods, and apparatus including computer-readable mediums for managing training wells for target wells in machine learning are provided. In one aspect, a method includes: for each training well of a plurality of training wells, building a training network for the training well based on well log data of the training well, predicting a target well log of a target well using the training network built for the training well, determining a relevancy level between the training well and the target well based on the predicted target well log of the target well and a measured target well log of the target well, and selecting relevant training wells among the plurality of training wells based on the relevancy levels associated with the plurality of training wells.
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Patent Agency Ranking
4.发明公开公开(公告)号：US20230221460A1
公开(公告)日：2023-07-13
申请号：US17571907
申请日：2022-01-10
Applicant: Saudi Arabian Oil Company
Inventor： Tao Lin , Weichang Li , Muhammad Arsalan , Abdulla Al Sarraf
CPC classification number: G01V99/005 , G06F30/28 , G06F30/27 , G06N20/00 , G06F2113/08
Abstract: A computer-implemented method for constrained multi-phase virtual flow metering and forecasting is described. The method includes predicting instantaneous flow rates and forecasting future target flow rates and well dynamics. The method includes constructing a virtual sensing model trained using forecasted target flow rates and well dynamics. The method includes building a constrained forecasting model by combining unconstrained flow forecasting models, well dynamics models, and virtual sensing models, wherein the constrained forecasting model forecasts multi-phase flow rates.
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5.发明公开公开(公告)号：US20230184087A1
公开(公告)日：2023-06-15
申请号：US17549743
申请日：2021-12-13
Applicant: Saudi Arabian Oil Company
Inventor： Tao Lin , Mokhles Mustapha Mezghani , Chicheng Xu , Weichang Li
IPC: E21B47/002 , E21B47/04 , E21B47/12
CPC classification number: E21B47/0025 , E21B47/04 , E21B47/138 , E21B2200/22
Abstract: A computer-implemented method, medium, and system for geological core property prediction using machine learning modeling are disclosed. In one computer-implemented method, multiple imagery data of a core sample of a wellbore are received. The multiple imagery data are partitioned into multiple image patches. Multiple first vectors of encoded features in a latent space are generated based on the multiple image patches. Multiple image features of the core sample of the wellbore are generated based on the multiple imagery data. Multiple second vectors of encoded features in the latent space are generated based on the multiple image features. Multiple rock properties associated with the core sample of the wellbore are predicted by running a regressor in the DFCN based on the multiple first vectors and the multiple second vectors. The multiple rock properties are provided for determining multiple properties of a subsurface reservoir that includes the wellbore.
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公开(公告)号：US20230142742A1
公开(公告)日：2023-05-11
申请号：US17983037
申请日：2022-11-08
Applicant: Saudi Arabian Oil Company
Inventor： Tao Lin , Weichang Li , Muhammad Arsalan
Abstract: Techniques include flowing a multiphase fluid from a hydrocarbon production well through a conduit; measuring, with an ultrasonic tomographic multiphase flow meter (UMM), ultrasonic waveforms generated by the UMM from the multiphase fluid; measuring properties of the multiphase fluid with fluid measurement sensors coupled to the conduit; identifying the ultrasonic waveforms and the properties with a machine-learning control system; determining multiphase fractions of the multiphase fluid from the one or more ultrasonic waveforms with a first ML model; determining a total flow rate of the multiphase fluid from the measured properties of the multiphase fluid with a second ML model; and determining a volumetric flow rate of a liquid phase or a gas phase based on the determined multiphase fraction and the determined total flow rate.
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7.发明授权公开(公告)号：US12085687B2
公开(公告)日：2024-09-10
申请号：US17571907
申请日：2022-01-10
Applicant: Saudi Arabian Oil Company
Inventor： Tao Lin , Weichang Li , Muhammad Arsalan , Abdulla Al Sarraf
IPC: G01V20/00 , G06F30/27 , G06F30/28 , G06N20/00 , G06F113/08
CPC classification number: G01V20/00 , G06F30/27 , G06F30/28 , G06N20/00 , G06F2113/08
Abstract: A computer-implemented method for constrained multi-phase virtual flow metering and forecasting is described. The method includes predicting instantaneous flow rates and forecasting future target flow rates and well dynamics. The method includes constructing a virtual sensing model trained using forecasted target flow rates and well dynamics. The method includes building a constrained forecasting model by combining unconstrained flow forecasting models, well dynamics models, and virtual sensing models, wherein the constrained forecasting model forecasts multi-phase flow rates.
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公开(公告)号：US20240143564A1
公开(公告)日：2024-05-02
申请号：US18391363
申请日：2023-12-20
Applicant: SAUDI ARABIAN OIL COMPANY
Inventor： Chicheng Xu , Mohamed Larbi Zeghlache , Tao Lin , Yuchen Jin , Weichang Li
IPC: G06F16/215 , E21B49/00 , G06F16/25
CPC classification number: G06F16/215 , E21B49/00 , G06F16/25
Abstract: A method and a system for well log data quality control is disclosed. The method includes obtaining a well log data regarding a geological region of interest, verifying an integrity and a quality of the well log data, determining the quality of the well log data based on a quality score of the well log data and making a determination regarding the access to the databases based on the quality of data. Additionally, the method includes performing the statistical analysis and the classification of well log data, a predictive and a prescriptive analysis of trends and predictions of the well log data, and generating an action plan for datasets with unsatisfactory quality scores.
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