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Shale Gas Transition in China: Evidence Based on System Dynamics Model for Production Prediction

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  • Yingchao Chen

    (School of Economics, Shandong Technology and Business University, Yantai 265600, China)

  • Yang Zhang

    (School of Management Science and Engineering, Shandong Technology and Business University, Yantai 265600, China)

Abstract

As a clean energy source, shale gas plays a crucial role in mitigating the supply–demand imbalance of natural gas and in facilitating the transition to a low-carbon economy. This study employs a system dynamics model to forecast future production trends in shale gas in China, analyze its implications for the natural gas supply–demand structure, and explore pathways for sustainable development. Firstly, by integrating the characteristics of China’s shale gas resources, market dynamics, and policy frameworks, the key factors influencing production are identified, and their interrelationships are systematically analyzed. Subsequently, a causal loop diagram is constructed using the VENSIM software(VENSIM PLE 9.3.5 x64), a set of representative variables is selected, and the logical relationships among these variables are established through a multivariate statistical analysis, culminating in the development of a production forecasting model for China’s shale gas (stock and flow diagram). Finally, based on parameter assumptions, this study predicts the production trends in shale gas in China under multiple scenarios. The forecasting results reveal that China’s shale gas production is expected to grow at an average annual rate of 3.32% to 8.02%, with production under the reference scenario projected to reach 724.22 × 10 8 m 3 by 2040. However, the growth of shale gas production over the next two decades remains limited, accounting for a maximum of 12.07% of the total natural gas consumption, underscoring its transitional role in the low-carbon transformation. To address these challenges, this study proposes four policy recommendations: (1) prioritize the development of shallow, high-quality gas-bearing blocks while gradually transitioning to deeper formations; (2) intensify technological innovation in deep shale gas extraction to enhance recovery rates and mitigate production decline rates; (3) implement flexible production subsidies and moderately increase natural gas sales prices to incentivize production and optimize resource allocation; and (4) strengthen ecological conservation and improve water resource management to ensure the sustainable development of shale gas.

Suggested Citation

  • Yingchao Chen & Yang Zhang, 2025. "Shale Gas Transition in China: Evidence Based on System Dynamics Model for Production Prediction," Energies, MDPI, vol. 18(4), pages 1-20, February.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:4:p:878-:d:1589719
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    References listed on IDEAS

    as
    1. Liu, Jianye & Li, Zuxin & Duan, Xuqiang & Luo, Dongkun & Zhao, Xu & Liu, Ruolei, 2021. "Subsidy analysis and development trend forecast of China's unconventional natural gas under the new unconventional gas subsidy policy," Energy Policy, Elsevier, vol. 153(C).
    2. Lin, Boqiang & Wang, Ting, 2012. "Forecasting natural gas supply in China: Production peak and import trends," Energy Policy, Elsevier, vol. 49(C), pages 225-233.
    3. Mohr, S.H. & Evans, G.M., 2011. "Long term forecasting of natural gas production," Energy Policy, Elsevier, vol. 39(9), pages 5550-5560, September.
    4. Wang, Jianliang & Feng, Lianyong & Zhao, Lin & Snowden, Simon, 2013. "China's natural gas: Resources, production and its impacts," Energy Policy, Elsevier, vol. 55(C), pages 690-698.
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