摘要
生成式人工智能DeepSeek凭借本地轻量化部署、注重算法优化、开源共享等优势,显著提升工业场景的技术渗透率,推动天然气场站从传统运维向数智化跃迁。围绕DeepSeek的技术属性与天然气场站业务的适配性展开分析,基于技术接受模型(TAM)解构DeepSeek的应用效能,系统构建数据治理、算法创新与应用重构的技术路线。通过“核心平台—功能模块—场景延伸”分层架构设计“1+3+N”体系,提出多模态资源建设、生产运维和安全服务的智能化应用框架。针对边缘算力瓶颈、跨领域复合型人才短缺及多源异构数据治理等挑战,提出加强算力共享、专属数据体系建设及人才培养等建议,为天然气智慧场站建设提供理论支持与实践指导。
With the advantages of local lightweight deployment,focus on algorithm optimization,and open-source sharing,generative AI DeepSeek significantly improves the technology penetration rate in industrial scenarios,and promotes the natural gas field stations leaping from traditional operation and maintenance to digital intelligence.The study analyzes the adaptability of DeepSeek technical attributes and natural gas station business,deconstructs DeepSeek application effectiveness based on the Technology Acceptance Model(TAM),and systematically constructs technical routes for data governance,algorithmic innovation,and application reconfiguration.The"1+3+N"system is designed through the layered architecture design of“core platform-functional module-scene extension”,the intelligent application framework of multimodal resource construction,production,operation and security services is proposed.For the challenges of edge arithmetic bottleneck,shortage of cross-domain composite talents and governance of multi-source heterogeneous data,it puts forward the su ggestions of strengthening arithmetic sharing,construction of exclusive data system and talent cultivation,which provide theoretical support and practical guidance for the construction of intelligent gas stations.
作者
蒋华明
唐鑫
谭威
胥一超
魏亚涛
Jiang Huaming;Tang Xin;Tan Wei;Xu Yichao;Wei Yatao(PipeChina West East Pipeline Company,Shanghai 210002,China)
出处
《当代石油石化》
2025年第5期33-39,52,共8页
Petroleum & Petrochemical Today
关键词
人工智能
DeepSeek
天然气场站
智慧管理
技术接受模型
artificial intelligence
DeepSeek
natural gas station
intelligent management
technology acceptance model
