摘要
石油企业勘探开发业务链长、数据类型多且复杂,在数字化转型过程中,对建立跨专业、跨层级、跨部门数据关系的需求日益增加。数据谱系是一种方法论,旨在以业务为驱动,建立多层级横向、纵向业务数据谱系关系,真实反映业务运行情况和指标变化情况。对数据谱系方法论进行系统性研究,介绍了数据谱系的来源、理论基础、标准规范、软件支撑工具以及在天然气业务领域中的实践和应用场景等,对指导油田企业实现数据融合,形成完整的数据资源网、构建数据生态有重要参考意义。
The oil and gas industry has a long exploration and development business chain,with a variety of data types and complexities.In the process of digital transformation,the demand for establishing cross-disciplinary,crosslevel,and cross-departmental data relationships is increasing.Data ontology is a methodology that aims to establish multi-level horizontal and vertical business data ontology relationships to reflect the actual business operation situation and indicator changes.This paper conducts a systematic study of the data ontology methodology,introducing the sources,theoretical basis,standard specifications,software support tools,and practical applications and scenarios in the natural gas business field.It has important reference significance for guiding oilfield enterprises to achieve data integration,form a complete data resource network,and build a data ecosystem.
作者
石峰
于会松
宋秋明
王婉月
SHI Feng;YU Hui-song;SONG Qiu-ming;WANG Wan-yue(Xinjiang Oilfield Company,Karamay Xinjiang 834000,China)
出处
《计算机仿真》
2025年第11期272-275,280,共5页
Computer Simulation
关键词
数据谱系
指标
数据链
Data pedigree
Index
Data link
