| With the massive increasing of drilling and completion data of oil companies and the deepening of oilfield digitization technology,oil companies have formed an operating mode of multi-data center collaborative work,and gradually deploy database systems and application software on cloud platforms.Under the massive data foundation and the operation mode of multi-data center,comprehensive statistical analysis methods can provide oil companies with data support in production,management,scientific research,and decision-making,so that oil companies with multiple branches can improve management and work efficiency.Now,microservices have become the mainstream architecture method.This paper studies the method of constructing a multi-data center drilling and completion data statistical analysis system through a micro-service architecture.Through the research on the status quo of the drilling and completion data statistical analysis system,and the analysis of the requirements in a certain oil company,the microservice-based drilling and completion system has been designed and implemented.First,a distributed micro-service environment is constructed;then,the data set is divided based on the data correlation matrix using the BEA(Bond Energy Algorithm)algorithm;next,the random forest algorithm is used to preprocess the drilling and completion data;finally,the data of drilling and completion are statistically analyzed and a variety of display methods are realized.The use of this system in a certain oil company shows that the BEA algorithm based on the correlation matrix improves the data response speed of multiple data centers,and the random forest algorithm improves the analyzability of the data.The intuitive display of drilling and completion data has also improved the work efficiency of employees.This system provides an innovative method for the collaborative work mode of multiple data centers in petroleum enterprises,and has a great application value. |
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