公开(公告)号：US20220335253A1

公开(公告)日：2022-10-20

申请号：US17659215

申请日：2022-04-14

Applicant: Saudi Arabian Oil Company

Inventor： Chicheng Xu ,  Weichang Li ,  Olanrewaju A. Abudu ,  Shouxiang Mark Ma

IPC: G06K9/62 ,  G06F16/55 ,  G06T7/00 ,  G06V10/82 ,  G06V10/764

Abstract: A computer-implemented method includes: accessing a first database holding information encoding a set of labels that specify a condition of at least one of: a surface pipe, or an underground enclosure that runs at a plurality of depth locations; accessing a second database holding a plurality of inspection logs that record measurement data of the surface pipe or underground enclosure; based on, at least in part, the labeling information and the plurality of inspection logs, training a deep learning model configured to classify, into the set of labels, the condition of the surface pipe or underground enclosure when presented with the inspection logs; applying the deep learning model to one or more newly received inspection logs containing measurement data of a new surface pipe or a new underground enclosure; and subsequently classifying, into the set of labels, the condition of the new surface pipe or the new underground enclosure.

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：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.

公开(公告)号：US20220325613A1

公开(公告)日：2022-10-13

申请号：US17715208

申请日：2022-04-07

Applicant: Saudi Arabian Oil Company

Inventor： Chicheng Xu ,  Weichang Li ,  Majed Fareed Kanfar ,  Christon Achong

IPC: E21B43/30 ,  E21B47/12 ,  E21B49/02 ,  G06N20/00

Abstract: Implementations provide a computer-implemented method that includes: accessing a first pool of input data encoding a plurality of petrophysical properties of a first set wells of a reservoir; performing one or more petro-rock type (PRT) labeling at least in part based on the first pool of input data; at least in part based on the one or more petro-rock type (PRT) labeling, training one or more models for the reservoir using one or more machine learning algorithms; accessing a second pool of input data encoding the plurality of petrophysical properties of a second set of wells of the reservoir, and applying the one or more models to a second pool of input data to determine a characteristic of the reservoir, wherein the second set of wells are different from the first set of wells.

公开(公告)号：US20250077956A1

公开(公告)日：2025-03-06

申请号：US18459382

申请日：2023-08-31

Applicant: SAUDI ARABIAN OIL COMPANY

Inventor： Mohamed Larbi Zeghlache ,  Chicheng Xu ,  Yahia Ahmed Eltaher

IPC: G06N20/00

Abstract: Systems and methods for automatic well integrity log interpretation verification are disclosed. The methods include obtaining a first dataset comprising casing thickness profiles and associated electromagnetic [EM]data from at least a first hydrocarbon well having a casing; selecting a training dataset using at least a subset of the casing thickness profiles and a subset of the associated EM data; and training, using the training dataset, a machine learning network to produce a predicted corrosion log of a target section of a second hydrocarbon well from measured EM data from the second hydrocarbon well.

公开(公告)号：US12223016B2

公开(公告)日：2025-02-11

申请号：US17659215

申请日：2022-04-14

Applicant: Saudi Arabian Oil Company

Inventor： Chicheng Xu ,  Weichang Li ,  Olanrewaju A. Abudu ,  Shouxiang Mark Ma

IPC: G06K9/62 ,  G06F16/55 ,  G06F18/2431 ,  G06T7/00 ,  G06V10/764 ,  G06V10/82

Abstract: A computer-implemented method includes: accessing a first database holding information encoding a set of labels that specify a condition of at least one of: a surface pipe, or an underground enclosure that runs at a plurality of depth locations; accessing a second database holding a plurality of inspection logs that record measurement data of the surface pipe or underground enclosure; based on, at least in part, the labeling information and the plurality of inspection logs, training a deep learning model configured to classify, into the set of labels, the condition of the surface pipe or underground enclosure when presented with the inspection logs; applying the deep learning model to one or more newly received inspection logs containing measurement data of a new surface pipe or a new underground enclosure; and subsequently classifying, into the set of labels, the condition of the new surface pipe or the new underground enclosure.

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.

公开(公告)号：US11459873B2

公开(公告)日：2022-10-04

申请号：US17004692

申请日：2020-08-27

Applicant: Saudi Arabian Oil Company

Inventor： Chicheng Xu ,  Shuo Zhang ,  Jay Vogt ,  Troy W. Thompson

IPC: E21B47/022 ,  G06F17/10 ,  G01V99/00 ,  E21B44/02

Abstract: Systems and methods of optimizing a new well path using a minimum curvature method are disclosed. An arc of the new well path may include a change in curvature at a point along the length of the arc. The arc of the new well path may be determined by iteratively: selecting a length of a first arc portion of the arc; determining a length of a second arc portion of the arc according to a minimum curvature method; combining the first arc portion and the second arc portion to form an arc; determining a deviation of the arc relative to a planned well trajectory; and selecting the arc with the lowest deviation from the planned well trajectory.

公开(公告)号：US20250043681A1

公开(公告)日：2025-02-06

申请号：US18788947

申请日：2024-07-30

Applicant: SAUDI ARABIAN OIL COMPANY

Inventor： Martin E. Poitzsch ,  Chicheng Xu ,  Shouxiang Ma

IPC: E21B49/00

Abstract: A method for constructing a high fidelity logging while drilling (LWD) log that includes obtaining a temporal well depth log and a plurality of temporal LWD logs from a drilling operation. The method further includes obtaining a temporal record of operational drilling parameters from the drilling operation. The method further includes determining, using a first machine-learning model, a temporal history of the drilling operation and constructing, using the temporal well depth log and the plurality of temporal LWD logs, a plurality of temporal property logs at each depth in the plurality of depths. The method further includes processing the plurality of temporal property logs with, at least, a second machine-learning model to form a plurality of corrected temporal property logs and aggregating the plurality of corrected temporal property logs to form a plurality of high fidelity LWD logs.