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Gas Injection Optimization and Shrinkage Control for Salt Cavern CO 2 Storage (SCCS) Based on Creep-Shrinkage Sensitivity Analysis.

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Title: Gas Injection Optimization and Shrinkage Control for Salt Cavern CO 2 Storage (SCCS) Based on Creep-Shrinkage Sensitivity Analysis.
Authors: Jiang, Tingting1 (AUTHOR), Zhang, Yiyun1,2 (AUTHOR), Liao, Youqiang1,2 (AUTHOR) liaoyq2018@126.com, Xie, Dongzhou1,2 (AUTHOR), He, Tao2 (AUTHOR)
Source: Energies (19961073). Apr2026, Vol. 19 Issue 8, p1970. 17p.
Subject Terms: *Sensitivity analysis, *Multi-objective optimization, *Computer simulation, *Carbon sequestration, *Mathematical optimization
Abstract: Salt cavern CO2 storage (SCCS) technology represents a crucial pathway for achieving large-scale carbon sequestration. However, its long-term operation faces the challenge of cavern shrinkage due to surrounding rock creep, which directly impacts storage safety and stability. Despite its importance, there is currently a lack of research focusing on the proactive control of SCCS cavern shrinkage and its collaborative optimization with operational economy. To fill this gap, this paper first investigated the effects of the stress state (f1), height-to-diameter ratio (f2), symmetry factor (f3), and cavern volume (f4) on the volumetric shrinkage rate through numerical simulations of regular caverns and univariate sensitivity analysis. The sensitivity ranking and quantitative relationships of these factors were clarified as f 1 (2.31) > f 4 (0.309) > f 2 (0.166) > f 3 (0) . Subsequently, a multi-objective nonlinear optimization model was established, and the primal-dual interior-point method was adopted as the solution algorithm. Using actual cavern data as a case study for the solution, the results demonstrate that the optimization model converges stably in approximately 1.1 s. The resulting optimal gas injection allocation scheme achieves a 14.77% improvement in the comprehensive score compared to the baseline scheme. This study provides a theoretical basis and a practical tool for the rapid generation of SCCS gas injection allocation schemes. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
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Header DbId: enr
DbLabel: Energy & Power Source
An: 193438310
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  Label: Title
  Group: Ti
  Data: Gas Injection Optimization and Shrinkage Control for Salt Cavern CO 2 Storage (SCCS) Based on Creep-Shrinkage Sensitivity Analysis.
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  Data: <searchLink fieldCode="AR" term="%22Jiang%2C+Tingting%22">Jiang, Tingting</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhang%2C+Yiyun%22">Zhang, Yiyun</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liao%2C+Youqiang%22">Liao, Youqiang</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> liaoyq2018@126.com</i><br /><searchLink fieldCode="AR" term="%22Xie%2C+Dongzhou%22">Xie, Dongzhou</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22He%2C+Tao%22">He, Tao</searchLink><relatesTo>2</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Energies+%2819961073%29%22">Energies (19961073)</searchLink>. Apr2026, Vol. 19 Issue 8, p1970. 17p.
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  Data: *<searchLink fieldCode="DE" term="%22Sensitivity+analysis%22">Sensitivity analysis</searchLink><br />*<searchLink fieldCode="DE" term="%22Multi-objective+optimization%22">Multi-objective optimization</searchLink><br />*<searchLink fieldCode="DE" term="%22Computer+simulation%22">Computer simulation</searchLink><br />*<searchLink fieldCode="DE" term="%22Carbon+sequestration%22">Carbon sequestration</searchLink><br />*<searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Salt cavern CO2 storage (SCCS) technology represents a crucial pathway for achieving large-scale carbon sequestration. However, its long-term operation faces the challenge of cavern shrinkage due to surrounding rock creep, which directly impacts storage safety and stability. Despite its importance, there is currently a lack of research focusing on the proactive control of SCCS cavern shrinkage and its collaborative optimization with operational economy. To fill this gap, this paper first investigated the effects of the stress state (f1), height-to-diameter ratio (f2), symmetry factor (f3), and cavern volume (f4) on the volumetric shrinkage rate through numerical simulations of regular caverns and univariate sensitivity analysis. The sensitivity ranking and quantitative relationships of these factors were clarified as f 1 (2.31) > f 4 (0.309) > f 2 (0.166) > f 3 (0) . Subsequently, a multi-objective nonlinear optimization model was established, and the primal-dual interior-point method was adopted as the solution algorithm. Using actual cavern data as a case study for the solution, the results demonstrate that the optimization model converges stably in approximately 1.1 s. The resulting optimal gas injection allocation scheme achieves a 14.77% improvement in the comprehensive score compared to the baseline scheme. This study provides a theoretical basis and a practical tool for the rapid generation of SCCS gas injection allocation schemes. [ABSTRACT FROM AUTHOR]
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.3390/en19081970
    Languages:
      – Code: eng
        Text: English
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        PageCount: 17
        StartPage: 1970
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      – SubjectFull: Sensitivity analysis
        Type: general
      – SubjectFull: Multi-objective optimization
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      – SubjectFull: Computer simulation
        Type: general
      – SubjectFull: Carbon sequestration
        Type: general
      – SubjectFull: Mathematical optimization
        Type: general
    Titles:
      – TitleFull: Gas Injection Optimization and Shrinkage Control for Salt Cavern CO 2 Storage (SCCS) Based on Creep-Shrinkage Sensitivity Analysis.
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            NameFull: Jiang, Tingting
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            NameFull: Zhang, Yiyun
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            NameFull: Xie, Dongzhou
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            NameFull: He, Tao
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            – D: 15
              M: 04
              Text: Apr2026
              Type: published
              Y: 2026
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              Value: 19
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              Value: 8
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            – TitleFull: Energies (19961073)
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