Dong Guo Phones & Addresses
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616 Alliston Ct, Las Vegas, NV 89144 (702) 286-3398
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61L Alliston Ct, Las Vegas, NV 89134
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Hot Springs Village, AR
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North Las Vegas, NV
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Rosemead, CA
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San Gabriel, CA
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San Francisco, CA
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Saline, AR
Business Records
Name / Title
Company / Classification
Phones & Addresses
Director, Treasurer
Eac Developer & Investment Inc
616 Alliston Ct, Las Vegas, NV 89144
President
AMERICAN EAGLE BRAND INTERNATIONAL INVEST ENTERPRISE LTD
4301 E Vly Blvd D2, Los Angeles, CA 90032
4301 Vly Blvd, Los Angeles, CA 90032
4301 Vly Blvd, Los Angeles, CA 90032
President
HUADONG TECHNOLOGY MANAGEMENT INSTITUTE
445 S Figueroa St, Los Angeles, CA 90071
President
D&Y LUCKY INTERNATIONAL INC
903 S Walnut St, Inglewood, CA 90301
Manager
Lucky Investment LC
4215 Spg Mtn Rd, Las Vegas, NV 89102
M
Eastern Tobacco LLC
4425 Spg Mtn Rd, Las Vegas, NV 89102
616 Alliston Ct, Las Vegas, NV 89144
6315 Pinion Jay St, Las Vegas, NV 89148
616 Alliston Ct, Las Vegas, NV 89144
6315 Pinion Jay St, Las Vegas, NV 89148
Secretary, Treasurer, President
Lucky Entertainment USA Inc
4215 Spg Mtn Rd, Las Vegas, NV 89102
Publications
Us Patents
Global Model For Failure Prediction For Artificial Lift Systems
View pageUS Patent:
20140244552, Aug 28, 2014
Filed:
Mar 14, 2013
Appl. No.:
13/830875
Inventors:
Yintao Liu - Los Angeles CA, US
Ke-Thia Yao - Los Angeles CA, US
Anqi Wu - Los Angeles CA, US
Dong Guo - Los Angeles CA, US
Jingwen Zheng - Los Angeles CA, US
Lanre Olabinjo - San Ramon CA, US
Oluwafemi Balogun - San Ramon CA, US
Iraj Ershaghi - Los Angeles CA, US
Ke-Thia Yao - Los Angeles CA, US
Anqi Wu - Los Angeles CA, US
Dong Guo - Los Angeles CA, US
Jingwen Zheng - Los Angeles CA, US
Lanre Olabinjo - San Ramon CA, US
Oluwafemi Balogun - San Ramon CA, US
Iraj Ershaghi - Los Angeles CA, US
Assignee:
University of Southern California - Los Angeles CA
Chevron U.S.A. Inc. - San Ramon CA
Chevron U.S.A. Inc. - San Ramon CA
International Classification:
G06N 99/00
US Classification:
706 12
Abstract:
Methods and systems for predicting failures in an artificial lift system are disclosed. One method includes extracting one or more features from a dataset including time sampled performance of a plurality of artificial lift systems disposed across a plurality of different oil fields, the dataset including data from failed and normally operating artificial lift systems. The method also includes forming a learning model based on identified pre-failure signatures in the extracted features, the learning model configured to predict a failure of an artificial lift system based on observation of one of the identified pre-failure signatures in operational data received from the artificial lift system.