Design and analysis of intelligent retrieval system for drilling data and completion data based on cloud platform. (August 2020)

• Record Type: Journal Article
• Authors: Zhao, Yifan; Wang, Kuisheng; Chen, Lianguo
• Is Part Of: Journal of physics. Volume 1607(2020)
• Publication Date: 2020-08
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1607/1/012026
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: In the context of the accelerating cloud platform construction in the oil industry, this paper solves the problem of difficulty in drilling and completion data retrieval by classifying and sorting drilling data and completion data to construct an intelligent retrieval model for drilling and completion data. Based on the cloud platform environment, this paper studies the method of constructing an retrieval system for drilling data and completion data through the microservice architecture. This system provides a unified retrieve page for structured data and unstructured data of drilling and completion operations. By using the ElasticSearch full-text search engine to build a retrieval model, it provides users with fast, efficient, and convenient comprehensive query and retrieval services, and lays a foundation for the intelligent construction of drilling and completion platforms.