公开(公告)号：US20220180029A1

公开(公告)日：2022-06-09

申请号：US17543287

申请日：2021-12-06

Applicant: CHEVRON U.S.A. INC.

Inventor： Yuanbo LIN ,  Hussein ALBOUDWAREJ ,  Baosheng LIANG

IPC: G06F30/28

Abstract: Embodiments of generating values for property parameters are provided. One embodiment comprises obtaining values for a plurality of samples. The values correspond to a set of property parameters. The embodiment comprises identifying a first subset of property parameters from the set of property parameters that correlate to substantially all property parameters of the set of property parameters; and generating at least one model using the first subset of property parameters and a database corresponding to the at least one model, and using the at least one model for generating a value for at least one other property parameter of the set of property parameters. The first subset of property parameters and the at least one other property parameter are different. Another embodiment comprises generating a value for at least one other property for an additional sample using the at least one model.

公开(公告)号：US20220180030A1

公开(公告)日：2022-06-09

申请号：US17543324

申请日：2021-12-06

Applicant: CHEVRON U.S.A. INC.

Inventor： Yuanbo LIN ,  Hussein ALBOUDWAREJ ,  Baosheng LIANG

IPC: G06F30/28

Abstract: Embodiments generating values for property parameters are provided herein. One embodiment comprises obtaining values for a plurality of samples. The values correspond to a set of property parameters. The embodiment comprises performing bi-variate modelling on the set of property parameters to generate bi-variate relationships for the set of property parameters and selecting the bi-variate relationships that satisfy correlation criteria; performing multi-variate modelling on the property parameters corresponding to the unselected bi-variate relationships to generate multi-variate relationships for the unselected bi-variate relationships and selecting the multi-variate relationships that satisfy the correlation criteria; and combining the bi-variate models corresponding to the selected bi-variate relationships and the multi-variate models corresponding to the selected multi-variate relationships to generate a combined model comprising the corresponding parameters. Another embodiment comprises using a value of a particular parameter for an additional sample in the combined model to generate a value for at least one other property parameter.

公开(公告)号：US20230235660A1

公开(公告)日：2023-07-27

申请号：US18159626

申请日：2023-01-25

Applicant: Chevron U.S.A. Inc.

Inventor： Han-Young PARK ,  Baosheng LIANG ,  Yunhui TAN

IPC: E21B47/022

CPC classification number: E21B47/022 ,  E21B2200/20 ,  E21B2200/22

Abstract: A system and method for uncertainty estimation of reservoir parameters in unconventional reservoirs using a physics-guided convolutional neural network to generate a plurality of reservoir models, a data analysis step, and an uncertainty step is disclosed. The method is a computationally efficient method to estimate uncertainties in models of unconventional reservoirs.

公开(公告)号：US20210097390A1

公开(公告)日：2021-04-01

申请号：US17039403

申请日：2020-09-30

Applicant: Chevron U.S.A. Inc.

Inventor： Baosheng LIANG ,  Chaoshun HU ,  Min LI

IPC: G06N3/08 ,  G01V99/00 ,  G06N3/04

Abstract: A method is described for predicting permeability including receiving a 3-D earth model including a volume of interest; generating 2-D property images; receiving 2-D fracture images; training a physics-guided neural network using the 2-D fracture images; and predicting permeability using the physics-guided neural network applied to the 2-D property images. The method is executed by a computer system.