Evaluation of effective factors in window optimization of fry analysis to identify mineralization pattern: Case study of Bavanat region, Iran

سال انتشار: 1397
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 390

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شناسه ملی سند علمی:

JR_JMAE-9-1_015

تاریخ نمایه سازی: 18 تیر 1398

چکیده مقاله:

The known ore deposits and mineralization trends are important key exploration criteria in mineral exploration within a specific region. Fry analysis has conventionally been considered as a suitable method to determine the mineralization trends related to linear structures. Based upon literature sources, to date, no investigation has been carried out that includes the Sensitivity Analysis of Feature s Number (SAFN), Sensitivity Analysis of Window Size (SAWS), and Sensitivity Analysis of Spatial Distribution (SASD) of Fry analysis related to mineral locations. In this work, SAFN, SAWS, and SASD are performed by moving several different sub-windows among the main window in order to identify the main trends of mineralization by Fry analysis in the Bavanat region of Iran, which is qualified by its regional and local faults pattern. Based upon our investigation, the effectiveness of the window size and the number of features on Fry analysis are 15-30%. The determined main trends of sub-windows increase, whereas its distribution function of Fry outputs is more similar to the distribution function of Fry outputs of the main window. Moreover, the directions of rose diagrams could be changed due to the edge effects of marginal features around the selected window. However, by selecting an appropriate window, this problem can be solved. Additionally, by an appropriate window selection, the most suitable regional situation is an area that contains the largest number of deposits with a similar metallogenetic origin. Based upon our investigation, the distribution function of the Fry outputs is the main factor that directly controls the identified mineralization pattern of the selected windows.

کلیدواژه ها:

Mineral Exploration by Fry Analysis ، Sensitivity Analysis ، Mineralization Trend ، Window Size ، Features Number

نویسندگان

R. Ghasemi

Faculty of Mining, Petroleum & Geophysics Engineering, Shahrood University of Technology, Shahrood, Iran

B. Tokhmechi

Faculty of Mining, Petroleum & Geophysics Engineering, Shahrood University of Technology, Shahrood, Iran

G. Borg

Institute for Geosciences and Geography, Martin Luther University, Halle-Wittenberg, Germany