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Title:
OIL RESERVOIR PRODUCTION MACHINE LEARNING METHOD BASED ON PARALLEL AGENT MODEL
Document Type and Number:
WIPO Patent Application WO/2021/258525
Kind Code:
A1
Abstract:
An oil reservoir production machine learning method based on a parallel agent model. According to a parallel oilfield production optimization method based on an agent model, a plurality of better candidate schemes can be simultaneously obtained in each iteration, and MATLAB is then used to call oil reservoir numerical simulation software Eclipse in parallel to simultaneously perform real evaluation on the schemes, such that the optimization time of complex problems can be greatly reduced. By means of the method, the oilfield production optimization speed can be greatly increased, and the optimization efficiency and a final optimization effect are improved. Moreover, in addition to adjusting a production system of an oil well and a water well of an oilfield, the method can also be used for optimizing a well pattern, history matching, etc.

Inventors:
ZHANG KAI (CN)
ZHONG CHAO (CN)
CHEN GUODONG (CN)
XUE XIAOMING (CN)
ZHANG LIMING (CN)
YAO CHUANJIN (CN)
WANG JIAN (CN)
YANG YONGFEI (CN)
SUN ZHIXUE (CN)
Application Number:
PCT/CN2020/110264
Publication Date:
December 30, 2021
Filing Date:
August 20, 2020
Export Citation:
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Assignee:
UNIV CHINA PETROLEUM EAST CHINA (CN)
International Classes:
G06Q50/02
Foreign References:
CN109872007A2019-06-11
CN109236258A2019-01-18
CN102279419A2011-12-14
CN109063266A2018-12-21
US20070118346A12007-05-24
Other References:
ZHANG KAI, CHEN GUODONG; XUE XIAOMING; ZHANG LIMING; SUN HAI; YAO CHUANJIN: "A reservoir production optimization method based on principal component analysis and surrogate model", ZHONGGUO SHIYOU DAXUE XUEBAO, vol. 44, no. 3, 1 June 2020 (2020-06-01), pages 90 - 97, XP055882896, ISSN: 1673-5005, DOI: 10.3969/j.iss.1673-5005.2020.03.010
Attorney, Agent or Firm:
QINGDAO ZHIDILINGCHUANG PATENT AGENCY CO., LTD (CN)
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