Research on data‐driven model for soft sensing of natural gas production system-Reference-Cited by-同舟云学术

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Research on data‐driven model for soft sensing of natural gas production system

Published:2022-03-28 Issue:6 Volume:4 Page:
ISSN:2577-8196
Container-title:Engineering Reports
language:en
Short-container-title:Engineering Reports

Author:

Wang Dan¹²^ORCID,Kang Qi³,Yang Juheng⁴,Gong Jing³,Zhang Qi¹

Affiliation:

1. School of Economics and Management China University of Petroleum (Beijing) Beijing China

2. CNPC Economics and Technology Research Institute Beijing China

3. National Engineering Laboratory for Pipeline Safety China University of Petroleum (Beijing) Beijing China

4. PetroChina International Co., Ltd. Beijing China

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/eng2.12495

Reference40 articles.

1. Modified genetic algorithm for nonlinear data reconciliation

2. HaoucheM TessierA DeffousY&AuthierJVirtual flow meter pilot: based on data validation and reconciliation approach. Proceedings of the SPE International Production and Operations Conference & Exhibition; 2012:SPE‐157283‐MS. DOI: 10.2118/157283‐MS

3. Soft sensing for two-phase flow using an ensemble Kalman filter

4. Development and application of a virtual flow metering system;Wu H;China Offshore Oil Gas,2015

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