Article ID: MTJPAM-D-21-00023

Title: Multivariate and Spatial Statistical Analysis of Geochemical Data of Dolomite: The Case of Industrial Raw Materials’ Differentiation

Montes Taurus J. Pure Appl. Math. / ISSN: 2687-4814

Article ID: MTJPAM-D-21-00023; Volume 3 / Issue 2 / Year 2021, Pages 8-28

Document Type: Research Paper

Author(s): Zeki Ince a , Ozge Ozer Atakoglu b , Mustafa Gurhan Yalcin c

aDepartment of Geological Engineering, Akdeniz University, 07058 Antalya, Turkey

bDepartment of Geological Engineering, Akdeniz University, 07058 Antalya, Turkey

cDepartment of Geological Engineering, Akdeniz University, 07058 Antalya, Turkey

Received: 12 March 2021, Accepted: 16 March 2021, Published: 31 March 2021.

Corresponding Author: Mustafa Gurhan Yalcin (Email address:

Full Text: PDF


Dolomite, which is a carbonate rock formed with a sufficient source of magnesium, may have different genesis and types. Various geochemical and statistical methods are used to determine these differences. In this study, dolomite samples were collected from the Obaalacami site in the Alanya district of the Antalya province (Turkey). The study aims to reveal the differences in the geochemical properties of dolomite samples in terms of their genesis and existence using multivariate and spatial statistical analyses. Therefore, multivariate statistics and spatial analysis methods were used. The mineralogical properties of the samples collected from the field were determined by conducting XRD analysis. It was found that 90% of the mineralogical content of the samples consisted of dolomite mineral and the remaining 10% consisted of calcite. Thin cross-sectional images revealed that calcite mineral was found in the recrystallized form. The dolomite samples, which were geochemically classified under three groups, were found to have similar elemental contents by using statistical methods (distribution maps, heat maps, and cluster analysis). The samples classified as Type-1 dolomite (medium-crystalline dolomite) were found to have high concentrations of MgO in their composition while the samples classified as Type-2 dolomite (micritic fine-crystalline dolomite) had high concentrations of CaO and Zr content. On the other hand, the samples classified as Type-3 dolomite (dolarenite dolomite) were found to have high concentrations of Al2O3, SiO2, Fe2O3, and Sr compounds. The mathematical model of the regression analysis for the formation of dolomites in the region was found to be (%) SiO2 = -0.1 + 31.92 * (%) Sr + ϵ (R2 = 0.97, P-value =0). Multivariate and spatial statistical methods conducted to interpret geochemical data revealed that dolomitic formations in the region had different genesis and types. The interpretations regarding the genesis and types of the dolomites provide parameters that can be effectively used in determining the industrial use of dolomites. The multivariate statistical and spatial analysis methods conducted in the study can be easily used to obtain the geochemical properties of various metallic mines and various industrial raw materials, their spatial distributions, and the differences in terms of their genesis.

Keywords: Multivariate statistics, Spatial statistics, Applied mathematics, Dolomite

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