2024 : 11 : 21
Mohammad Parsa

Mohammad Parsa

Academic rank: Assistant Professor
ORCID:
Education: PhD.
ScopusId: 21
HIndex:
Faculty: Faculty of Engineering
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Research

Title
Multifractal analysis of stream sediment geochemical data: Implications for hydrothermal nickel prospection in an arid terrain, eastern Iran
Type
JournalPaper
Keywords
Nickel mineralization Concentration – area (C-A) fractal model Multifractal spectrum Local singularity mapping Iran
Year
2017
Journal JOURNAL OF GEOCHEMICAL EXPLORATION
DOI
Researchers Mohammad Parsa ، Abbas Maghsoudi ، Mahyar Yousefi ، Martiya Sadeghi

Abstract

In this study, fractal/multifractal modeling methods have been applied for preliminary hydrothermal Ni prospection using a set of stream sediment geochemical data of Ahangaran district, which is an arid terrain in eastern Iran. The study area has a complex geological and morphological setting, which is dominated by the presence of aeolian sands. Cretaceous ophiolitic rocks hosting nickel endowment are influenced by extensive listwanitic alteration. Hydrothermal nickel mineralization occurs as veinlets and disseminated forms within the listwanite units. Among the analyzed elements, Ni, Cr and, Co have been recognized as being associated with listwanitic alteration and Ni mineralization, through robust factor analysis of compositional data. The regional background patterns of these mineralization-related elements were delineated via the concentration – area (C-A) fractal modeling method. Different multifractal characteristics of the selected elements were recognized using the multifractal spectrum f(α) curves and different multifractal indices. The enrichment and depletion patterns of the related elements in different parts of the study area were also identified using the local singularity mapping technique. The application of local singularity mapping manifested different geochemical patterns that were not recognized via the C-A fractal modeling method. The superiority of the local singularity mapping technique in delineating geochemical populations over the C-A fractal modeling method, was revealed by quantification of the correlation between geochemical anomalies and geological evidence of the mineralization.