Wei J Shao

7253617, Aug 7, 2007

Mar 15, 2006

11/376046

Songhua Chen - Katy TX, US
Sheng Fang - Houston TX, US
Mike Gillen - The Woodlands TX, US
Mette Stengaard Munkholm - Vanloese, DK
Wei Shao - Conroe TX, US

Baker Hughes Incorporated - Houston TX

G01V 3/00

324303, 324300

A method for obtaining a parameter of interest relating to a region investigated by a nuclear magnetic resonance (NMR) tool and a non-NMR tool is disclosed. Data arising from the NMR tool is acquired, and data arising from the non-NMR tool is acquired. A solution equation is utilized for NMR signal intensity, the solution equation being functionally related to the NMR data, and a solution constraint is utilized based at least partially on the non-NMR data. The solution equation is solved for the signal intensity subject to the solution constraint, wherein the solving provides information relating to the parameter of interest.

8131469, Mar 6, 2012

Oct 3, 2008

12/245121

Songhua Chen - Katy TX, US
Wei Shao - Conroe TX, US

Baker Hughes Incorporated - Houston TX

G01V 1/40

702 8

A method for obtaining a parameter of interest related to an earth formation, the method including: obtaining nuclear magnetic resonance (NMR) data from an NMR tool investigating the earth formation with a plurality of pulse sequences of radio frequency energy, each pulse sequence having a unique frequency, a first train of pulses having a first interecho time (TE) and a second train of pulses having a second interecho time (TE) different from the first interecho time; relating the NMR data to a partial porosity at points to establish an NMR response model; solving the NMR response model to calculate the partial porosity at each of the points in the earth formation; summing the partial porosity for each of the points corresponding to each depth of investigation to provide a pore volume; and associating each pore volume with the corresponding depth of investigation to provide the parameter of interest.

20220381130, Dec 1, 2022

May 3, 2022

17/735727

- Houston TX, US
Wei Shao - Houston TX, US

E21B 44/00
G01N 33/24
G01V 11/00
E21B 49/00
G06F 30/10

System and methods of petrophysical modeling are disclosed. Training data for modeling a reservoir formation surrounding a wellbore drilled within the reservoir formation is received via a network from one or more data sources. A machine learning model is trained using symbolic regression to determine a formation model representing the reservoir formation, based on the training data received from the data source(s). At least one property of the reservoir formation is estimated, based on the formation model. A downhole operation is performed along the wellbore within the reservoir formation, based on the at least one estimated property.

20230068555, Mar 2, 2023

Aug 31, 2021

17/462968

- Houston TX, US
Wei Shao - Houston TX, US

E21B 49/00
G01V 3/32
G01V 3/38
G01V 99/00
G06F 30/28

Methods for correcting a gradient distribution in downhole NMR logging are described herein. NMR data is inverted using an effective gradient to obtain an apparent Tdistribution having a first main peak and a distortion caused by a second spurious peak. The first main peak corresponds to the effective gradient. The distortion in the apparent Tdistribution is then corrected by integrating the signal corresponding to the spurious peak into the signal corresponding to the main peak. The corrected apparent Tdistribution and the effective gradient are then used to interpret the NMR data. Thereafter, the interpreted data is used to determine one or more characteristics of the surrounding subsurface rock formation media.

20210090239, Mar 25, 2021

Sep 24, 2019

16/580595

- Houston TX, US
Songhua CHEN - Katy TX, US
Wei SHAO - Conroe TX, US
Adly HELBA - New Cairo, EG

G06T 7/00
G06N 3/08
G06K 9/62
G06T 7/174
G06T 7/11

Disclosed herein are methods and systems that determine a microfacies or a microfacies characteristic of a sample of a subterranean formation based on a segmented image of a petrographic image of the sample, wherein the segmented image is derived from the petrographic image using a machine-learning algorithm.

20200333501, Oct 22, 2020

Jan 17, 2020

16/746452

- Houston TX, US
MingJen Wang - Bellaire TX, US
Wei Shao - Conroe TX, US
Songhua Chen - Katy TX, US
Ronnel Charles Balliet - Houston TX, US

G01V 3/14
G01R 33/54

An NMR logging system is disclosed which continues logging without interruption despite switching activation sets to adapt to changes in formation properties. Based on detection of an approaching or encountered geological boundary, an appropriate activation set is transmitted to the downhole NMR tool while the NMR tool continues logging. This system optimizes NMR data collection for each formation and associated formation fluid properties while reducing the need to stop the tool string movement while switching the activation set, and reduces incomplete collection of NMR and non-NMR logging tool data.

20180164465, Jun 14, 2018

Jun 30, 2016

15/580583

- Houston TX, US
Wei SHAO - Conroe TX, US

HALLIBURTON ENERGY SERVICES, INC. - Houston TX

G01V 3/32
G01V 3/38

An apparatus comprising a data acquisition tool including NMR sensors, a data acquisition processor communicatively coupled with the NMR sensors, and a first memory storing instructions that cause the data acquisition processor to perform operations comprising acquiring data of earth formation fluid, varying at least one of a magnetic field gradient and an inter-echo time, and acquiring additional data. The apparatus further comprises a data processing unit comprising a second memory storing instructions that cause the data processor to perform operations comprising receiving data acquired by the data acquisition tool, constructing a mathematical model of the data, conducting a first inversion of the mathematical model to obtain a first set of NMR responses, performing a forward model of the first set of NMR responses obtained from the first inversion, conducting a second inversion to obtain a second set of NMR responses, and determining earth formation fluid properties.

20180120471, May 3, 2018

Apr 14, 2016

15/546173

- Houston TX, US
Wei SHAO - Conroe TX, US

HALLIBURTON ENERGY SERVICES, INC. - Houston TX

G01V 3/32
G01R 33/44

A method for determining earth formation rock and fluid properties comprising a data acquisition tool and a data acquisition processor, coupled with NMR sensors, and a first memory; transmitting acquired earth formation fluid data to a data processing unit comprising a processor and a second memory. Obtaining a fully polarized state echo train (E) and a partially polarized state echo train burst (E), wherein the Eincludes both partially polarized and fully polarized bins; inverting the Eto obtain an apparent transverse relaxation time (T) distribution, wherein the Tdistribution includes fully and partially polarized state echo train data; truncating the Tdistribution by discarding the partially polarized state echo train data; completing a forward model of the Eto obtain an additional echo train burst (E) performing a second inversion of the data set; determining earth formation fluid properties and displaying the properties on a display screen.