公开(公告)号：US20230408327A1

公开(公告)日：2023-12-21

申请号：US17804511

申请日：2022-05-27

Applicant: ARAMCO SERVICES COMPANY

Inventor： Lei Fu ,  Weichang Li

IPC: G01H9/00 ,  G01V1/22 ,  G01V1/28 ,  G01V1/30 ,  G06N3/04

CPC classification number: G01H9/004 ,  G01V1/226 ,  G06N3/0445 ,  G01V1/307 ,  G01V1/288

Abstract: A method for mapping fiber optic distributed acoustic sensing (DAS) measurements to particle motion involves obtaining, from a fiber optic DAS system in a wellbore, a first set of DAS data associated with a first seismic wave; obtaining, from a discrete seismic receiver in the wellbore, measured particle motion data associated with the first seismic wave; generating training data from the first set of DAS data and the measured particle motion data; training a machine learning model using the training data; obtaining a second set of DAS data associated with a second seismic wave; and determining a predicted particle motion in response to the second seismic wave using the machine learning model applied to the second set of DAS data.

公开(公告)号：US20250059864A1

公开(公告)日：2025-02-20

申请号：US18450108

申请日：2023-08-15

Applicant: ARAMCO SERVICES COMPANY

Inventor： Lei Fu ,  Weichang Li ,  Abdulaziz N. Almutairi

IPC: E21B43/25

Abstract: A method for determining drilling fluid properties. The method includes obtaining current drilling fluid properties for a drilling fluid used in a drilling operation, obtaining operational parameters related to the drilling operation, and obtaining a treatment, wherein the treatment describes one or more additives or processes to be applied the drilling fluid. The method further includes processing the current drilling fluid properties, the operational parameters, and the treatment with a treatment prediction system to determine a prediction for drilling fluid properties after treatment. The method further includes applying the treatment to the drilling fluid and using the drilling fluid, after application of the treatment, in the drilling operation.

公开(公告)号：US20250044469A1

公开(公告)日：2025-02-06

申请号：US18362720

申请日：2023-07-31

Applicant: ARAMCO SERVICES COMPANY

Inventor： Yong Ma ,  Weichang Li ,  Lei Fu

IPC: G01V1/28 ,  E21B44/00 ,  G01V1/30 ,  G06F30/27

Abstract: A system for enhancing traveltime information in a seismic dataset and determining a velocity model. The system includes a first initial velocity model, a forward modelling procedure, a machine-learned model, a drilling system with a wellbore planning system, and a computer. The computer is configured to: receive a non-synthetic seismic data set for a subsurface region of interest; perturb the first initial velocity model forming a first plurality of velocity models; simulate, with the forward modelling procedure, a first plurality of seismic data sets; form a first plurality of transformed seismic data sets with enhanced traveltime; train the machine-learned model using the first plurality of velocity models and the first plurality of transformed seismic data sets; transform the non-synthetic seismic data set to a non-synthetic transformed seismic data set; and process the non-synthetic seismic data set with the trained machine-learned model to predict a velocity model for the subsurface region.

公开(公告)号：US11898901B2

公开(公告)日：2024-02-13

申请号：US17804511

申请日：2022-05-27

Applicant: ARAMCO SERVICES COMPANY

Inventor： Lei Fu ,  Weichang Li

IPC: G06N3/044 ,  G01H9/00 ,  G01V1/22 ,  G01V1/30 ,  G01V1/28

CPC classification number: G01H9/004 ,  G01V1/226 ,  G01V1/288 ,  G01V1/307 ,  G06N3/044

Abstract: A method for mapping fiber optic distributed acoustic sensing (DAS) measurements to particle motion involves obtaining, from a fiber optic DAS system in a wellbore, a first set of DAS data associated with a first seismic wave; obtaining, from a discrete seismic receiver in the wellbore, measured particle motion data associated with the first seismic wave; generating training data from the first set of DAS data and the measured particle motion data; training a machine learning model using the training data; obtaining a second set of DAS data associated with a second seismic wave; and determining a predicted particle motion in response to the second seismic wave using the machine learning model applied to the second set of DAS data.

公开(公告)号：US20250101850A1

公开(公告)日：2025-03-27

申请号：US18474986

申请日：2023-09-26

Applicant: ARAMCO SERVICES COMPANY

Inventor： Chicheng Xu ,  Tao Lin ,  Zainab Al Ibrahim ,  Yaser Abdullah Alzayer ,  Weichang Li ,  Lei Fu

IPC: E21B44/00 ,  G01N33/24 ,  G01V5/06 ,  G06T7/32

Abstract: A method may use a core sampling system for collecting a core sample with a reference log of a first property. The method may use a wellbore logging system for recording uncalibrated well logs with a target log of the first property. The method may use a computer processor for obtaining an uncalibrated geological model, determining a bulk-shift depth correction based on a first cost function, forming a bulk-shifted log by applying the bulk-shift depth correction to the target log, identifying a plurality of log event pairs, determining, for each of the log event pairs, a local-shift depth correction based on a second cost function, forming a local-shift depth correction table from the local-shift depth correction for the log event pairs, and forming a calibrated geological model based, at least in part, on the uncalibrated geological model and the local-shift depth correction table.

公开(公告)号：US20250067172A1

公开(公告)日：2025-02-27

申请号：US18453768

申请日：2023-08-22

Applicant: ARAMCO SERVICES COMPANY

Inventor： Chicheng Xu ,  Tao Lin ,  Lei Fu ,  Yaser Abdullah Alzayer ,  Weichang Li

IPC: E21B49/00

Abstract: Systems and methods for automatic well log normalization are disclosed. The methods include acquiring a target log in a target well and a reference log in a reference well; identifying a stratigraphic interval in the target well and in the reference well; projecting the target log from the target well onto a pseudo target log in a pseudo target well and projecting the reference log from the reference well onto a pseudo reference log in a pseudo reference well; identifying lithologies from a first histogram of the pseudo target log and a second histogram of the pseudo reference log; determining, using the first histogram and the second histogram a regression relationship between the pseudo target log and the pseudo reference log; applying the regression relationship to the pseudo target log to generate a normalized pseudo target log; and determining a reservoir quality of the reservoir that produces hydrocarbons.