Proceedings of the 2023 3rd International Conference on Public Management and Intelligent Society (PMIS 2023)

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RBI Risk Assessment of Gas Field Stations Based on Improved CRITIC Method and Cloud Model

Authors
He Zheng1, Zhan Wen3, Songzhu Qing3, Shaolong Liu4, Shanbi Peng2, *
1Petrochina Southwest Oil and Gas Field Company Natural Gas Research Institute, Beijing, China
2Southwest Petroleum University, Chengdu, China
3Sichuan Changning Natural Gas Development Co, Ltd., Chengdu, China
4Chuanzhong Oil and Gas Mine of Southwest Oil and Gas Field Company, Suining, China
*Corresponding author. Email: shanbipeng@swpu.edu.cn
Corresponding Author
Shanbi Peng
Available Online 26 July 2023.
DOI
10.2991/978-94-6463-200-2_38How to use a DOI?
Keywords
Class III station; regional division indicator system; improved CRITIC; Cloud model
Abstract

Pipeline integrity management technology has become increasingly mature, however, as an important part of pipeline system integrity management, station integrity management is still in infancy. On the basis of considering the volume and work type of various gas field stations, the gas field stations are divided into three categories: Class I, Class II, and Class III. Different mixed risk assessment schemes are adopted to deal with equipment in different stations. After the index weight is determined based on the improved Criteria Importance Though Intercrieria Correlation (CRITIC) method, the similarity between the standard cloud and the evaluation cloud is further calculated through the cloud model theory, and Class III stations are classified, the applicability of the method is verified through case analysis, which can provide reference for RBI evaluation of Class III stations.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2023 3rd International Conference on Public Management and Intelligent Society (PMIS 2023)
Series
Atlantis Highlights in Intelligent Systems
Publication Date
26 July 2023
ISBN
978-94-6463-200-2
ISSN
2589-4919
DOI
10.2991/978-94-6463-200-2_38How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - He Zheng
AU  - Zhan Wen
AU  - Songzhu Qing
AU  - Shaolong Liu
AU  - Shanbi Peng
PY  - 2023
DA  - 2023/07/26
TI  - RBI Risk Assessment of Gas Field Stations Based on Improved CRITIC Method and Cloud Model
BT  - Proceedings of the 2023 3rd International Conference on Public Management and Intelligent Society (PMIS 2023)
PB  - Atlantis Press
SP  - 365
EP  - 375
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-200-2_38
DO  - 10.2991/978-94-6463-200-2_38
ID  - Zheng2023
ER  -