Design and implementation of information management platform for big data of uranium

Authors

ZHOU Xiaoxi, Tianjin Center, China Geological Survey, Tianjin 300170, China
DENG Fan, Tianjin Center, China Geological Survey, Tianjin 300170, China
WAN Lin, Faculty of Information Engineering, China University of Geosciences, Wuhan 430074, China
YANG Jun, Tianjin Center, China Geological Survey, Tianjin 300170, China

Abstract

In order to integrate the borehole data and geological survey data of sandstone-type uranium deposits, the unified management of the borehole database was implemented, and the efficiency of integrated application of the geological data of borehole data was improved. A comprehensive information management platform for uranium was designed and implemented. For big data platform, the four-layer framework composed of the base installation, information resources, application service, user interaction was proposed. Techniques such as virtualization of cloud computing, distributive storage and parallel computing were adopted to set up the basic environment of the big data of uranium and improve the unified storage management and the computing power of the big data set of was enhanced. Based on the parallel computing technique, the functions of fast 3-D visualized expression and fast inquiry of multiple conditions was realized, providing technical support of data basis and information for uranium exploration and result integration. uranium boreholes. The goal for intelligent extraction, highly efficient conversion and fast loading of multi-source heterogeneous borehole data was realized. The working efficiency of data management and integrated application

Keywords

big data technology, information management platform, data mining, metallogenic prediction

DOI

10.3969/j.issn.1001-1986.2019.01.002

Recommended Citation

ZHOU Xiaoxi, DENG Fan, WAN Lin, et al. (2019) "Design and implementation of information management platform for big data of uranium," Coal Geology & Exploration: Vol. 47: Iss. 1, Article 3.
DOI: 10.3969/j.issn.1001-1986.2019.01.002
Available at: https://cge.researchcommons.org/journal/vol47/iss1/3

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