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Gas Storage Wellbore Temperature Prediction Based on Advanced Spatiotemporal Graph Convolutional Neural Networks
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Zhi-qiang HE1, Jie-xue CHEN1, Jian TAN1, Ai-jun YIN2, *, Quan HE2
Science Technology and Engineering | 2025, 25(15) : 6304 - 6309
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Science Technology and Engineering | 2025, 25(15): 6304-6309
• Papers·Petroleum and Natural Gas Industry •
Gas Storage Wellbore Temperature Prediction Based on Advanced Spatiotemporal Graph Convolutional Neural Networks
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Zhi-qiang HE1, Jie-xue CHEN1, Jian TAN1, Ai-jun YIN2, *, Quan HE2
Affiliations
  • 1 Chongqing Gas Field, PetroChina Southwest Oil and Gas Field Company, Chongqing 400021, China
  • 2 College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044, China
Published: 2025-05-28 doi: 10.12404/j.issn.1671-1815.2404595
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Gas storage operations can be significantly impacted by abnormal wellbore temperatures at natural gas storage sites. Accurately predicting wellbore temperatures is of paramount importance for enhancing the safety and efficiency of these operations. Based on the analysis of operational parameter correlations, a gas storage wellbore temperature prediction method was proposed using advanced spatiotemporal graph convolutional neural network (A-SGCN). Both GCN and long short-term memory (LSTM) networks were employed by A-SGCN to capture spatial and temporal dependencies, respectively. Based on this framework, an adaptive residual attention mechanism was incorporated to effectively capture the intricate relationships between spatiotemporal data, ultimately enabling accurate temperature prediction. The effectiveness of the method is validated through its application at the Huangcaoxia gas storage No.2 injection-production station. Accurate prediction of wellhead temperature at Well No.1 is achieved through the association of monitoring parameters between Well No. 1 and Well No.6.

natural gas  /  gas storage  /  wellbore  /  temperature prediction  /  graph convolutional neural network
Zhi-qiang HE, Jie-xue CHEN, Jian TAN, Ai-jun YIN, Quan HE. Gas Storage Wellbore Temperature Prediction Based on Advanced Spatiotemporal Graph Convolutional Neural Networks[J]. Science Technology and Engineering, 2025 , 25 (15) : 6304 -6309 . DOI: 10.12404/j.issn.1671-1815.2404595
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Year 2025 volume 25 Issue 15
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Article Info
doi: 10.12404/j.issn.1671-1815.2404595
  • Receive Date：2024-06-19
  • Online Date：2025-07-09
  • Published：2025-05-28
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History
  • Received：2024-06-19
  • Revised：2024-11-24
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Affiliations
    1 Chongqing Gas Field, PetroChina Southwest Oil and Gas Field Company, Chongqing 400021, China
    2 College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400044, China
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