Geochemical and Hydrothermal Alteration Patterns of the Abrisham-Rud Porphyry Copper District, Semnan Province, Iran

Autor: Timofey Timkin, Mahnaz Abedini, Mansour Ziaii, Mohammad Reza Ghasemi
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Minerals, Vol 12, Iss 1, p 103 (2022)
Druh dokumentu: article
ISSN: 12010103
2075-163X
DOI: 10.3390/min12010103
Popis: In this study, the zonality method has been used to separate geochemical anomalies and to calculate erosional levels in the regional scale for porphyry-Cu deposit, Abrisham-Rud (Semnan province, East of Iran). In geochemical maps of multiplicative haloes, the co-existence of both the supra-ore elements and sub-ore elements local maxima implied blind mineralization in the northwest of the study area. Moreover, considering the calculated zonality indices and two previously presented geochemical models, E and NW of the study have been introduced as ZDM and BM, respectively. For comparison, the geological layer has been created by combining rock units, faults, and alterations utilizing the K-nearest neighbor (KNN) algorithm. The rock units and faults have been identified from the geological map; moreover, alterations have been detected by using remote sensing and ASTER images. In the geological layer map related to E of the study area, many parts have been detected as high potential areas; in addition, both geochemical and geological layer maps only confirmed each other at the south of this area and suggested this part as high potential mineralization. Therefore, high potential areas in the geological layer map could be related to the mineralization or not. Due to the incapability of the geological layer in identifying erosional levels, mineralogy investigation could be used to recognize this level; however, because of the high cost, mineralogy is not recommended for application on a regional scale. The findings demonstrated that the zonality method has successfully distinguished geochemical anomalies including BM and ZDM without dependent on alteration and was able to predict erosional levels. Therefore, this method is more powerful than the geological layer.
Databáze: Directory of Open Access Journals
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