-
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.
-
2.发明申请公开(公告)号：US20220290553A1
公开(公告)日：2022-09-15
申请号：US17201618
申请日：2021-03-15
Applicant: Saudi Arabian Oil Company
Inventor： Damian Pablo San Roman Alerigi , Weichang Li , Sameeh Issa Batarseh
IPC: E21B47/002 , G01N33/24 , E21B47/26
Abstract: Some implementations of the present disclosure provide a method that includes: irradiating a target surface with a process beam during a drilling process; in response to irradiating with the process beam, receiving a signal beam that contains light scattered from the target surface as well as light radiating from the target surface; splitting the signal beam into a first portion on a polarization arm and a second portion on a non-polarization arm; performing, on the polarization arm, a first plurality of polarization-dependent intensity and spectrum measurements of the first portion; performing, on the non-polarization arm, a second plurality of intensity and spectrum measurements of the second portion; and based on applying one or more machine learning techniques to at least portions of (i) the first plurality of polarization-dependent intensity and spectrum measurements, and (ii) the second plurality of intensity and spectrum measurements, determining a classification of the target surface.
-
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.
-
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.
-
公开(公告)号：US20220187492A1
公开(公告)日：2022-06-16
申请号：US17121042
申请日：2020-12-14
Applicant: SAUDI ARABIAN OIL COMPANY
Inventor： Daniele Colombo , Weichang Li , Ernesto Sandoval-Curiel
Abstract: A method for a physics-driven deep learning-based inversion coupled to fluid flow simulators may include obtaining measured data for a subsurface region, obtaining prior subsurface data for the subsurface region, and obtaining a physics-driven standard regularized joint inversion for at least two model parameters. The method may further include obtaining a case-based deep learning inversion characterized by a contracting path and an expansive path. The method may further include forming the physics-driven deep learning inversion with the physics-driven standard regularized joint inversion, the case-based deep learning inversion, and a coupling operator based on a penalty function. The method may further include forming a feedback loop between the physics-driven standard regularized joint inversion and the case-based deep learning inversion for re-training the case-based deep learning inversion. The method may further include generating an inversion solution for reservoir monitoring.
-
Patent Agency Ranking
公开(公告)号：US20190145935A1
公开(公告)日：2019-05-16
申请号：US16232249
申请日：2018-12-26
Applicant: Saudi Arabian Oil Company
Inventor： Sebastian Csutak , Weichang Li , Angelo Sampaolo , Gregory Ham
Abstract: A downhole system includes a quartz enhanced photoacoustic spectrometer (QEPAS) configured to be positioned within a wellbore formed in a subterranean zone of a hydrocarbon formation, a sampling system coupled to the QEPAS, and a computer system connected to the QEPAS. The sampling system is configured to be positioned in the wellbore and obtain a sample of a wellbore fluid at a downhole location in the subterranean zone. The QEPAS is configured to spectroscopically scan the sample and to determine a plurality of quantities of a corresponding plurality of hydrocarbons in the same. The computer system includes one or more processors to perform operations including receiving the plurality of quantities of the plurality of hydrocarbons in the sample and determining a plurality of ratios, where each ratio is a ratio of one of the plurality of hydrocarbons with another of the plurality of hydrocarbons.
-
公开(公告)号：US20190017966A1
公开(公告)日：2019-01-17
申请号：US16031790
申请日：2018-07-10
Applicant: Saudi Arabian Oil Company
Inventor： Sebastian Csutak , Weichang Li , Angelo Sampaolo , Gregory Ham
CPC classification number: G01N29/022 , E21B49/081 , G01N21/1702 , G01N29/228 , G01N29/2418 , G01N29/46 , G01N2021/1704 , G01V1/44
Abstract: A downhole system includes a quartz enhanced photoacoustic spectrometer (QEPAS) configured to be positioned within a wellbore formed in a subterranean zone of a hydrocarbon formation, a sampling system coupled to the QEPAS, and a computer system connected to the QEPAS. The sampling system is configured to be positioned in the wellbore and obtain a sample of a wellbore fluid at a downhole location in the subterranean zone. The QEPAS is configured to spectroscopically scan the sample and to determine a plurality of quantities of a corresponding plurality of hydrocarbons in the same. The computer system includes one or more processors to perform operations including receiving the plurality of quantities of the plurality of hydrocarbons in the sample and determining a plurality of ratios, where each ratio is a ratio of one of the plurality of hydrocarbons with another of the plurality of hydrocarbons.
-
公开(公告)号：US20180347354A1
公开(公告)日：2018-12-06
申请号：US15921003
申请日：2018-03-14
Applicant: Saudi Arabian Oil Company
Inventor： Weichang Li , Sebastian Csutak , David Jacobi , Tiffany Dawn McAlpin , Max Deffenbaugh , Shannon Lee Eichmann
IPC: E21B49/00 , G01N33/24 , G01N21/3563 , G06N5/04 , G06F15/18
CPC classification number: G06F19/704 , G01N33/24 , G06F19/707
Abstract: Systems, apparatuses, and computer-implemented methods are provided for the sensing and prediction of properties of source rock. Disclosed here is a method of predicting the maturity of a source rock that includes obtaining a plurality of data of a sample source rock from a plurality of data acquisition devices placed in vicinity of the sample source rock and analyzing the received data using a predictive correlation to determine maturity of the sample source rock. The predictive correlation is generated by applying a machine learning model to correlate the plurality of data acquired from a plurality of representative source rocks with a plurality of properties of the plurality of representative source rocks.
-
公开(公告)号：US20180136353A1
公开(公告)日：2018-05-17
申请号：US15809744
申请日：2017-11-10
Applicant: Saudi Arabian Oil Company
Inventor： Yang Zhao , Weichang Li
CPC classification number: G01V1/366 , G01V1/28 , G01V1/32 , G01V1/36 , G01V2210/23 , G01V2210/242 , G01V2210/25 , G01V2210/26 , G01V2210/44 , G01V2210/48 , G01V2210/57
Abstract: Seismic shot gather data is received from a computer data store for processing. The received seismic shot gather data is separated into downgoing and upgoing wavefields, a time-frequency-wavenumber (t-f-k) three-dimensional (3D) data cube comprising multiple time-frequency (t-f) slices is formed. The downgoing wavefields are wavelet transformed from a time (t) domain to a t-f domain and the upgoing wavefields are wavelet transformed from the t domain to the t-f domain. A wavelet cross-correlation is performed between the downgoing wavefields in the t-f domain and the upgoing wavefields in a t-f-k domain to generate wavelet cross-correlated data. Soft-threshold filtering if performed for each t-f slice of the t-f-k 3D data cube. An inverse wavelet transform is performed to bring wavelet cross-correlated data from the t-f-k domain to a time-receiver (t-x) domain. All seismic shots of the received seismic shot gather data are looped over and the wavelet cross-correlated data is stacked as a virtual source gather.
-
10.发明公开公开(公告)号：US20240093600A1
公开(公告)日：2024-03-21
申请号：US17946346
申请日：2022-09-16
Applicant: Saudi Arabian Oil Company
Inventor： Weichang Li , Katherine Leigh Hull , Younane N. Abousleiman
IPC: E21B47/12
CPC classification number: E21B47/12 , E21B2200/20 , E21B2200/22
Abstract: A computer-implemented method for quantitative prediction and sorting of carbon underground treatment and sequestration is described. The method includes preprocessing multiple data sets, wherein the multiple datasets are multi-modal and multiscale data sets. The method also includes predicting geological structural properties, chemical properties, and geological properties by inputting the preprocessed multiple data sets into trained machine learning models. Additionally, the method includes ranking the storage and treatment potential of a formation based on the predicted geological structural properties, chemical properties, and geological properties.
-
-
-
-
-
-
-
-
-
Search Results
36
records
(took 0.021 seconds)
