Research On Spark-based Reservoir Management System In Big Data Environment

With the development of reservoir operation and management informationization,reservoir operation and management data show explosive growth.It is extremely urgent and necessary to study how to use massive data to analyze and assist decision-making on reservoir operations.However,traditional reservoir operation and management systems It has been difficult to meet the corresponding needs.This paper uses the Hadoop ecosystem technology,combined with the non-relational database Hbase and the big data computing engine Spark.Through the study of the Spark-based reservoir management system in a big data environment,the rapid and parallel analysis of reservoir management big data is realized.Provide support for corporate production management.This paper first uses Kettle and Sqoop technologies to implement data extraction,conversion,and loading between traditional databases and HDFS,and solves the problem of inconsistent data formats,null values and other data information uncertainties.Second,a data warehouse tool based on Hive is designed The architecture of the operation management data warehouse,the theme is determined,the business partition table is established,and the data model is designed to facilitate the fast and parallel analysis of the data.Third,the calculation model of Spark is given,and Spark and HBase are combined.Completed the analysis result data storage and query optimization,and realized fast query and visual display of the analysis result data.Finally,based on the Hadoop cluster environment and the MyEcplice environment,a Spark-based reservoir operation management system under the big data environment was developed and implemented Based on big data technology,it has realized oilfield profitability analysis,operational capacity analysis,input-output efficiency analysis,and oil production plant development capacity analysis.This makes up for the deficiencies of traditional reservoir operation management systems in mass data storage and statistical analysis,and provides effective support for statistical analysis and auxiliary decision-making of reservoir operation data.