Metallogenic Prediction of the Zaozigou Gold Deposit Using 3D Geological and Geochemical Modeling

Deep-seated mineralization prediction is an important scientific problem in the area of mineral resources exploration. The 3D metallogenic information extraction geology and geochemistry can be great help. This study uses modeling technology to intuitively depict spatial distribution orebodies, fractures, intrusive rocks. In particular, geochemical models 12 elements are established for extraction. Subsequently, front halo element association As-Sb-Hg, near-ore Au-Ag-Cu-Pb-Zn, tail W-Mo-Bi identified. Upon this foundation, convolutional neural network model built used deep-seated prediction, which expresses a high performance (AUC = 0.99). Associated with regularity, two exploration targets delineated, might able serve as beneficial achievements deep Zaozigou gold deposit.