油田大数据分析模式研究

Research on Big Data Analysis of Digital Oilfield

随着数字化油田的建设,围绕石油勘探、开采、储运、销售等业务,产生了大量的数据,且数据结构复杂,数据产生的速度极快,数据价值密度较低。传统的文本分析已经无法完全胜任,如果能将大数据分析引入数字化油田的开发过程,不仅可以有效管理数据,还能对海量数据进行深层次的挖掘和分析。基于此,本文针对生产中遇到的数据安全问题、数据存储问题、数据分析问题、分级工具匮乏等问题,进行有针对性分析,并提出相应的解决方案。

With the construction of digital oilfield,a large number of data have been generated around the business of oil exploration,exploitation,storage and transportation,sales and so on.The data structure is complex,the speed of data generation is extremely fast,and the data value density is low.Traditional text analysis is not fully competent.If big data analysis can be introduced into the development process of digital oilfield,it can not only effectively manage data,but also carry out deep-seated mining and analysis of massive data.Based on this,this paper analyzes the data security problems,data storage problems,data analysis problems,lack of classification tools,and puts forward the corresponding solutions.