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Simulation and Optimization of Surface Gas Injection Systems for Underground Gas Storage
[Image: see text] With the rapid development and popularization of sensing technology and information technology, the demand for intelligence in the oil and gas industry and gas storage has increased. The optimized operation of surface engineering is an important part of intelligence. To master the...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10483671/ https://www.ncbi.nlm.nih.gov/pubmed/37692256 http://dx.doi.org/10.1021/acsomega.3c04321 |
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author | Lin, Mingzhen Yan, Guanghong Liu, Ting Wu, Xiayue Yu, Pengpeng |
author_facet | Lin, Mingzhen Yan, Guanghong Liu, Ting Wu, Xiayue Yu, Pengpeng |
author_sort | Lin, Mingzhen |
collection | PubMed |
description | [Image: see text] With the rapid development and popularization of sensing technology and information technology, the demand for intelligence in the oil and gas industry and gas storage has increased. The optimized operation of surface engineering is an important part of intelligence. To master the operation law of the surface engineering of gas storage, improve the production management level, and reduce the cost of gas injection, we investigated the simulation and optimization of a surface gas injection system for practical underground gas storage. We propose calculation formulas for gas injection well pressure separately according to the ideal gas equation of state, the van der Waals equation, and the R-K equation and verify them using actual data. By comparing the calculation error of the data and the complexities for both the equation and the calculation process, we finally choose the formula derived from the ideal gas equation of state as the constraint condition for our research. Moreover, we model the surface gas injection system by using the Aspen HYSYS simulation software. From the variation in the compressor power, we determine that the equalizing pressure injection pattern is the optimal injection pattern and the optimal number of injection wells is three. In addition, we examine the relationship between injection flow and well pressure with injection time under the optimal injection pattern. Finally, we obtain the functional formula of well pressure and injection flow with injection time. The results can provide not only a basis for the gas injection decision making of production systems but also a basic guarantee for the digital transformation and intelligent operation of enterprises. |
format | Online Article Text |
id | pubmed-10483671 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-104836712023-09-08 Simulation and Optimization of Surface Gas Injection Systems for Underground Gas Storage Lin, Mingzhen Yan, Guanghong Liu, Ting Wu, Xiayue Yu, Pengpeng ACS Omega [Image: see text] With the rapid development and popularization of sensing technology and information technology, the demand for intelligence in the oil and gas industry and gas storage has increased. The optimized operation of surface engineering is an important part of intelligence. To master the operation law of the surface engineering of gas storage, improve the production management level, and reduce the cost of gas injection, we investigated the simulation and optimization of a surface gas injection system for practical underground gas storage. We propose calculation formulas for gas injection well pressure separately according to the ideal gas equation of state, the van der Waals equation, and the R-K equation and verify them using actual data. By comparing the calculation error of the data and the complexities for both the equation and the calculation process, we finally choose the formula derived from the ideal gas equation of state as the constraint condition for our research. Moreover, we model the surface gas injection system by using the Aspen HYSYS simulation software. From the variation in the compressor power, we determine that the equalizing pressure injection pattern is the optimal injection pattern and the optimal number of injection wells is three. In addition, we examine the relationship between injection flow and well pressure with injection time under the optimal injection pattern. Finally, we obtain the functional formula of well pressure and injection flow with injection time. The results can provide not only a basis for the gas injection decision making of production systems but also a basic guarantee for the digital transformation and intelligent operation of enterprises. American Chemical Society 2023-08-23 /pmc/articles/PMC10483671/ /pubmed/37692256 http://dx.doi.org/10.1021/acsomega.3c04321 Text en © 2023 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Lin, Mingzhen Yan, Guanghong Liu, Ting Wu, Xiayue Yu, Pengpeng Simulation and Optimization of Surface Gas Injection Systems for Underground Gas Storage |
title | Simulation and Optimization of Surface Gas Injection
Systems for Underground Gas Storage |
title_full | Simulation and Optimization of Surface Gas Injection
Systems for Underground Gas Storage |
title_fullStr | Simulation and Optimization of Surface Gas Injection
Systems for Underground Gas Storage |
title_full_unstemmed | Simulation and Optimization of Surface Gas Injection
Systems for Underground Gas Storage |
title_short | Simulation and Optimization of Surface Gas Injection
Systems for Underground Gas Storage |
title_sort | simulation and optimization of surface gas injection
systems for underground gas storage |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10483671/ https://www.ncbi.nlm.nih.gov/pubmed/37692256 http://dx.doi.org/10.1021/acsomega.3c04321 |
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