3D Geological Modeling And Spatial Analysis Of Mineralization In I Mining Area Of Jinchuan Cu-Ni Sulfide Deposit

In recent years, with the development of mineral resource evaluation,3D modeling of geological body and spatial analysis technology, the theory and technology of concealed ore body3D visualization modeling are becoming increasingly sophisticated.3D geological modeling technology is used to build geologic models, to exhibit geologic features and spatial correlation, as well as to execute spatial analysis and reserve estimation. This study proceeds spatial analysis with ore body based on geo-statistical analysis principles, semivariable function and spatial variation ellipsoid are constructed to reveal distribution and variation of ore grade in different directions, reflect spatial correlation between ore bodies. Then ore grade and amount of metal is projected to three coordinate planes, to display the spatial distribution of ore body’s mineralization.This paper is supported by the project named "The stereoscopic quantitative prediction of concealed ore bodies in the deep and marginal parts of Jinchuan mine area", and has found the3D geological model of mine I, explored variation ellipsoid constructing methods and mineralization projection distribution. It contains several main parts as follows:(l)Raw data of Jinchuan Cu-Ni deposit is analyzed. According to drilling log and geological reports of different periods, Section-maps, Column-maps and geologic-topographic maps are digitized, and the geological database is constructed.(2)3D geological models of Mine I of Jinchuan Cu-Ni deposit are built.3D Entity models and block models are constructed basing on softwares of ArcGIS, GOCAD and Datamine.(3) Spatial variation ellipsoid is constructed. Supac was used to analysis the ore grades’ spatial variation of Cu and Ni basing on geo-statistics theory, revealing Cu, Ni ore grades’spatial distribution.(4) Grade of ore body and resource quantity are estimated. Basing on block model of ore body, using combination sample data as known data, utilizing spatial variation ellipsoid and experimental semi-variogram related parameters, grade of ore and resource quantity were estimated.(5) The spatial distribution of Ore body’s mineralization is drawn. Firstly, mineralization spatial distribution is analyzed by ore body’s spatial variation. Secondly, ore body’s block model and mineralization information’s contour map in projective plane, containing grade and the metal’s amount of Cu and Ni, were drawn. Finally, mineralization information’s spatial distribution is revealed to find out advantageous parts for deeper and blind ores prospecting.