Predictive Approach to Perform Fault Detection in Electrical Submersible Pump Systems-Reference-Cited by-同舟云学术

Predictive Approach to Perform Fault Detection in Electrical Submersible Pump Systems

Published:2021-03-16 Issue:12 Volume:6 Page:8104-8111
ISSN:2470-1343
Container-title:ACS Omega
language:en
Short-container-title:ACS Omega

Author:

Peng Long¹²^ORCID,Han Guoqing¹²,Sui Xianfu³,Pagou Arnold Landjobo¹²,Zhu Liying¹²,Shu Jin¹²

Affiliation:

1. State Key Laboratory of Petroleum Resources and Prospecting, China University of Petroleum (Beijing), Beijing 102249, China

2. Shaanxi Key Laboratory of Carbon Dioxide Sequestration and Enhanced Oil Recovery, Xi’an 710075, China

3. China National Offshore Oil Corporation (CNOOC) Research Institute, Beijing 100027, China

Funder

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Subject

General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acsomega.0c05808

Reference19 articles.

1. Dunham, C. 27th ESP Workshop: Summary of Presentations; Oilfield Automation Consulting, 2013; p 1. Retrieved from https://www.spegcs.org/media/files/files/cebfcc3a/2013-ESP-Workshop-Summary-of-Presentations.pdf.

2. Alamu, O. A.; Pandya, D. A.; Warner, O.; Debacker, I. ESP Data Analytics: Use of Deep Autoencoders for Intelligent Surveillance of Electric Submersible Pumps. Offshore Technology Conference, Houston, Texas, USA, May 2020.

3. Awaid, A.; Al-Muqbali, H.; Al-Bimani, A.; Al-Yazeedi, Z.; Al-Sukaity, H.; Al-Harthy, K.; Baillie, A. ESP Well Surveillance using Pattern Recognition Analysis, Oil Wells, Petroleum Development Oman. International Petroleum Technology Conference, Doha, Qatar, January 2014.

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