Big data is massive, high growth rate and diversified information assets. It is an indispensable technology for the future prediction of ore prospecting targets. The research on the big data-3D metallogenic prediction is facing opportunities and challenges. The geo-spatial big data have some complex characteristics such as multitudinous data sources, different scales, large data volume, unstructured management, timeliness, co-management with spatial data and non-spatial data. Besides, data structure must be adapted to the 3D modeling and spatial analysis. This paper analyzes the characteristics of geo-spatial data and studies the requirements of multi-source geoscience information management. Based on the national and industry standards, a multi-source geoscience spatial database model is established which can meet the requirements of 3D mineralization prediction. There are several components such as control of drilling geology database, spatial attribute database and geophysical database. The multi-source geo-spatial index library is set up to support those databases work together. In this paper, a typical example of big data application is used as the research object. The data of the exploration results in the ore field are collected and the spatial database of the multi-source geology of Zhonggu ore field is established. On this basis, the effective extraction of ore-controlling elements, can further support the 3D mineralization prediction. The results show that the proposed multi-source geo-spatial database can effectively manage big data of geoscience,which is an important solution for big data-3D metallogenic prediction and it is an important support for 3D metallogenic prediction.
Zhang Mingming Li Xiaohui Tang Minhui Ma Liang Jia Cai Hu Xunyu Liao Baosheng Yuan Feng . Study on the construction of multi?source geological spatial database in 3D metallogenic prediction: A case study of Zhonggu orefield in Ningwu Basin[J]. Chinese Journal of Geology, 2017, 52(3): 743-754.