TY - JOUR
T1 - Cross-technology convergence in shale gas development
T2 - Insights from international patent network and machine learning
AU - Wei, Yigang
AU - Gao, Entong
AU - Xi, Jingxin
AU - Wu, Qiying
AU - Guo, Meiyu
N1 - The research is supported by the National Natural Science Foundation of China (Nos. 72474017, 72174020, and 71904009), the Beijing Natural Science Foundation (No. 9232014), the Research Grants Council of the University Grants Committee of Hong Kong (Nos. 12616222 and 22611624), the Natural Science Foundation of Guangdong Province (No. 2025A1515010017), and the National Natural Science Foundation of China (No. 723B2001).
Publisher Copyright:
© 2025 The Authors.
PY - 2026/1/6
Y1 - 2026/1/6
N2 - Understanding technological convergence patterns in transitional energy sources is critical for strategic innovation governance during the global sustainability transition. This study examines cross-technology convergence in shale gas innovation through analysis of 17,929 patents filed across major jurisdictions between 2000 and 2023. Based on semantic topic modeling (Top2Vec), IPC co-occurrence networks with machine learning methods, we map the structure technological integration and compare innovation strategies across countries. Three core findings emerge: (1) shale gas innovation forms a highly interconnected global network with established cores in hydraulic fracturing, environmental mitigation, and processing, alongside emerging clusters in microseismic monitoring and purification technologies; (2) systematic cross-country differences reveal distinct innovation strategies: the United States operates as a broad integrator, China and Japan as focused specialists, and Europe as collaboration-centric; (3) integration breadth correlates most strongly with patent recency, documentation scope, and moderate family size, though modest predictive performance (R² = 0.36) reflects the complex, non-linear dynamics of technological convergence. These findings inform targeted policies for transitional energy governance, including monitoring critical network bridges, strategically funding emergent clusters, and tailoring collaboration mechanisms to national innovation postures.
AB - Understanding technological convergence patterns in transitional energy sources is critical for strategic innovation governance during the global sustainability transition. This study examines cross-technology convergence in shale gas innovation through analysis of 17,929 patents filed across major jurisdictions between 2000 and 2023. Based on semantic topic modeling (Top2Vec), IPC co-occurrence networks with machine learning methods, we map the structure technological integration and compare innovation strategies across countries. Three core findings emerge: (1) shale gas innovation forms a highly interconnected global network with established cores in hydraulic fracturing, environmental mitigation, and processing, alongside emerging clusters in microseismic monitoring and purification technologies; (2) systematic cross-country differences reveal distinct innovation strategies: the United States operates as a broad integrator, China and Japan as focused specialists, and Europe as collaboration-centric; (3) integration breadth correlates most strongly with patent recency, documentation scope, and moderate family size, though modest predictive performance (R² = 0.36) reflects the complex, non-linear dynamics of technological convergence. These findings inform targeted policies for transitional energy governance, including monitoring critical network bridges, strategically funding emergent clusters, and tailoring collaboration mechanisms to national innovation postures.
KW - Complex Network Analysis
KW - Cross-Technology
KW - Green Patent
KW - Machine Learning
KW - Patent Mining
KW - Shale Gas
UR - https://www.scopus.com/pages/publications/105025520996
UR - https://www.sciencedirect.com/science/article/pii/S2352484725008017?via%3Dihub
U2 - 10.1016/j.egyr.2025.108925
DO - 10.1016/j.egyr.2025.108925
M3 - Journal article
AN - SCOPUS:105025520996
SN - 2352-4847
VL - 15
JO - Energy Reports
JF - Energy Reports
M1 - 108925
ER -