摘要
The West Mine of the Bayan Obo deposit, located in the northern-central part of Inner Mongolia, China, is enriched in Nb, rare earth elements and iron （Nb-REE-Fe） mineral resources. This paper presents a combined method to explore metallogenic correlation of the Nb-REE-Fe mineralization at the Bayan Obo West Mine. The method integrates factor analysis and Back Propagation （BP） neural network technology into processing and modeling of geological data. In this study, the Nb and REE contents of samples were transformed into discrete values to analyze the correlations among the metallogenic elements. The results show weak mineralization correlations between Nb and REEs. Nb and U are closely related in the geochemical patterns, while Fe is closely related to both Th and Mn. LREEs are an important factor for the mineralization of the Bayan Obo deposit, while Fe and Nb can be considered as the results of passive mineralization. On the basis of a metallogenic correlation analysis, the factors affecting the Fe-REE-Nb mineralization were extracted, and the Nb mineralization model was established by the BP neural network. Based on the BP neural network data computing, the variability of the Nb concentration displays a coupled multi-factor nonlinear relationship, which can be used to reveal the inherent metallogenic elemental regularities and predict the degree of element mineralization enrichment in the mining area.
The West Mine of the Bayan Obo deposit, located in the northern-central part of Inner Mongolia, China, is enriched in Nb, rare earth elements and iron （Nb-REE-Fe） mineral resources. This paper presents a combined method to explore metallogenic correlation of the Nb-REE-Fe mineralization at the Bayan Obo West Mine. The method integrates factor analysis and Back Propagation （BP） neural network technology into processing and modeling of geological data. In this study, the Nb and REE contents of samples were transformed into discrete values to analyze the correlations among the metallogenic elements. The results show weak mineralization correlations between Nb and REEs. Nb and U are closely related in the geochemical patterns, while Fe is closely related to both Th and Mn. LREEs are an important factor for the mineralization of the Bayan Obo deposit, while Fe and Nb can be considered as the results of passive mineralization. On the basis of a metallogenic correlation analysis, the factors affecting the Fe-REE-Nb mineralization were extracted, and the Nb mineralization model was established by the BP neural network. Based on the BP neural network data computing, the variability of the Nb concentration displays a coupled multi-factor nonlinear relationship, which can be used to reveal the inherent metallogenic elemental regularities and predict the degree of element mineralization enrichment in the mining area.
基金
supported by National Key Research and Development Program(Grant No.2016YFC0501102)
National Science and Technology Major Project(Grant No.2016ZX05066-001)
