数据湖平台智能油田实时数据服务标准化研究

Standardized development and practical implementation of real-time data services for intelligent oilfields based on a data lake platform

智能油田应用开发涉及的数据种类繁多、来源多样,数据量大且标准不一。勘探开发数据湖平台的目标是在数据源与数据应用之间建立桥梁,对采集到的原始数据在数据湖内进行标准化治理、聚合加工并封装为标准化服务提供应用系统调用,实现数据资源的管用分离。根据某智能油田项目所开展的实时数据服务入湖迁移与标准化改造工作,提出了一套基于数据湖平台的智能油田实时数据服务标准化开发方法,并利用数据湖平台实时数据开发工具,将智能油田实时数据服务经标准化改造后迁移入湖。该项研究为油气生产企业数智化转型提供了新的方法与工具支撑,有助于提高智能油田大数据分析应用的开发效率与质量。

Intelligent oilfield application development involves a wide variety of data with large amount,from diverse sources and different standards.The Exploration and Production(E&P)data lake platform is positioned to build a bridge between data sources and data applications.The collected raw data is standardized,aggregated and processed in the data lake and encapsulated into standardized services for application systems to call,thereby realizing the separation from data resources to data applications.This paper summarizes the work related to the migration of real-time data services into data lake and the standardized transformation during one intelligent oilfield project.Then a standardized approach for real-time data services development in intelligent oilfield based on the data lake platform is proposed,which has been implemented and verified by using data lake real-time development tool to standardize the real-time data services and then migrate into data lake.This research provides new method and tool support for the digital and intelligent transformation of oil and gas enterprises to improve the efficiency and quality of industrial big data application development.