Version 1
: Received: 19 October 2019 / Approved: 20 October 2019 / Online: 20 October 2019 (16:53:36 CEST)
How to cite:
Yazdani, M.; Alinia, F. Geochemical Anomaly Separation by Statistical and Fractal Methods in the Sehezar Valley of Tonekabon – Northern Iran. Preprints2019, 2019100237. https://doi.org/10.20944/preprints201910.0237.v1
Yazdani, M.; Alinia, F. Geochemical Anomaly Separation by Statistical and Fractal Methods in the Sehezar Valley of Tonekabon – Northern Iran. Preprints 2019, 2019100237. https://doi.org/10.20944/preprints201910.0237.v1
Yazdani, M.; Alinia, F. Geochemical Anomaly Separation by Statistical and Fractal Methods in the Sehezar Valley of Tonekabon – Northern Iran. Preprints2019, 2019100237. https://doi.org/10.20944/preprints201910.0237.v1
APA Style
Yazdani, M., & Alinia, F. (2019). Geochemical Anomaly Separation by Statistical and Fractal Methods in the Sehezar Valley of Tonekabon – Northern Iran. Preprints. https://doi.org/10.20944/preprints201910.0237.v1
Chicago/Turabian Style
Yazdani, M. and Firouz Alinia. 2019 "Geochemical Anomaly Separation by Statistical and Fractal Methods in the Sehezar Valley of Tonekabon – Northern Iran" Preprints. https://doi.org/10.20944/preprints201910.0237.v1
Abstract
Sehezar area is located in southern Tonokabon in Mazandaran province, north of Iran, near the Tarom – Hashdtjin belt. The existence of granitoid masses in the region can be important in terms of the potential of mineralization. Geochemical anomaly separation from the background is one of the important steps in mineral exploration. In the past decades, geochemical anomalies have been identified by means of various methods. Some of these separation methods include: statistical analysis methods (like univariate, bivariate, multivariate statistics), spatial statistical methods and fractal and multi-fractal methods. To identify the anomalous area, 71 stream sediment samples were collected from the area and analyzed by the ICP-MS method, and then interpreted. Initially, data were normalized and afterwards, univariate analysis (threshold limit and screening (P.N) methods) was used, in which results of the probable and definite anomaly of the threshold method were confirmed by the P.N screening method. Finally, the maps of the anomal zones were drawn. Then, bivariate analysis (Pearson correlation coefficients) and multivariate analysis on normal data were performed on SPSS software, in which factor analysis and cluster analysis were used for multivariate analysis. As a result of using the factor analysis method, six factors were identified and factor maps were drawn by the Surfer software. Also, by using cluster analysis, the variables were divided into two groups. In order for a better separation of the geochemical anomaly from the background, in addition to the threshold method, the Concentration - Area fractal method was used. Here, the fractal geometry using full-logarithmic graphs of the Concentration - Area obtained is capable of separating the stairs of different sections (background, threshold, and anomaly) with respect to the angle coefficient of the Concentration - Area plot. Then, in conclusion, results of these methods were compared and investigated, and finally, the anomalies area maps of the Au, Ag, Cu, Fe, W elements were drawn by Concentration - Area fractal and threshold methods and anomalous zones were introduced.
Environmental and Earth Sciences, Geochemistry and Petrology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
