Fuzzy logic and goniometry as tools for improving the meaning of input data in modeling of mineral veins: a case study from the Kuh-e-Sefid mine, Eastern Iran

Identification of mineral veins that do not have much data available, due to the importance of vein mines in the economy of the country, is one of the main issues in the explorations. In the eastern region of Iran, the largest magnesite deposits discovered are vein structures located along the strike-slip shear zones. At present, mining of this mineral is confined to the outcrops of veins at the surface. If surface reserves are exhausted, the need for this mineral will only be met by subsurface estimates. This study aimed to evaluate the deep magnesium expansion in the Kuh-e-Sefid mine concerning the geometry of the mineral veins in the Neogene folded conglomerate based on a combination of proposed methods including statistical analysis of the angles related to the intersection of structural elements and fuzzy logic to create a meaningful database before entering data into mineral modeling software. In this method, first all the angles between the structural strikes are weighted two by two based on their intersection. Then, the correlation map of the angles is determined and matched with the shear fractures of the Riedel model. Fuzzy logic is used to create better correlation models, especially in the narrower statistical populations. Field evaluation in the easternmost areas of the mine with the least raw data available confirms the early promising points obtained by this method. Therefore, using these two computational tools, one can convert meaningful data before entering raw data into modeling environments.