基于Hadoop的油气水井生产大数据分析与应用

基于Hadoop框架的分布式存储、并行计算以及数据仓库建模等技术,构建Kylin多维分析平台,实现油气田注入井生产数据的统一存储、计算、分析功能,解决多表联合查询效率低、多数据库之间存在数据孤岛等问题。实现16个分散数据库的快速查询和管理优化,查询分析效率提升3倍。该平台可统一管理8×10~4余口注入井生产数据,业务分析时间由原来的1 d缩短到现在的5 s,查询时间为秒级响应。通过建立注入井生产数据多维分析模型,在中国石油天然气集团公司实现了注入井宏观管理分析、问题井管理分析、注入井生产运行分析等应用。实现了系统的快速响应,满足了高效分析需求。注入井生产数据分析粒度由原来的油田细化到单井,业务分析更为细致,能够实时掌握油气生产动态。

Big Data Analysis and Application Research of Oil and Gas Well Production based on Hadoop

Based on Hadoop framework"s distributed storage, parallel computing and data warehouse modeling techniques, this paper constructs Kylin multi-dimensional analysis system, which realizes the unified storage, calculation and analysis functions of oil and gas field injection well production data. It solves the problems of low efficiency of multi-table joint query and data islands between multiple databases. The fast query and management optimization of 16 distributed databases has been realized, and the efficiency of query analysis has been improved by 3 times. The platform can uniformly manage the production data of 8×10⁴ injection wells. The business analysis time is shortened from 1 d to 5 s, and the query time is second response. Through the establishment of multi-dimensional analysis model of injection well production data, the application of macroscopic management analysis, problem well management analysis and injection well production operation analysis of injection wells was realized in China National Petroleum Corporation. The system responds quickly and meets the needs of efficient analysis. The injection molding production data analysis granularity is refined from the original oilfield to a single well, and the business analysis is more detailed, and the oil and gas production dynamics can be grasped in real time.