Ranking of Geochemical Samples by Characteristic Analysis and VIKOR Methods for Identifying Mineralization Areas

Document Type : Research Article

Author

Dept. of Mining, Birjand University of Technology, Birjand, Iran

10.29252/anm.2020.12376.1401

Abstract

Summary
The analysis of geochemical samples of several elements and the relevance of the location and extent of mineralization area in an exploration region with the mineralization, pathfinder, and indicator elements, make it a priority to determine the composite anomaly (multi-element anomaly) on a single-element anomaly. The purpose of this paper is to introduce ranking methods for the determination of the composite geochemical anomalies. For this purpose, three ranking methods namely that of characteristic analysis, VIKOR, and FDAHP-VIKOR methods are used. 365 geochemical samples have also been used which are taken in the epithermal Ag-Au Chah-Zard deposit. The ranking results in R mode indicating the criterion as the most important element related to mineralization area while Au, Ag and Sb elements take the following positions. Also, the ranking of geochemical samples shows that the area of 0.42 Km2 is considered to design a borehole drilling network in a detailed exploration phase.
 
Introduction
A multi-element anomaly is superior to a single element anomaly. Collective and multiplicative composite anomalies, integration, reduce dimension, clustering, and ranking methods are also used to determine the multi-element anomalies. The purpose of this paper is to introduce ranking methods for identifying mineral potential areas.
 
Methodology and Approaches
In this paper, the characteristic analysis method, which is a multivariate statistical method, and VIKOR algorithms, which is a multi-criteria decision-making method, are used to rank 365 geochemical samples of the Chah-Zard deposit area. The ranking of data is also done in two R and Q modes.
 
Results and Conclusions
Ranking results in R mode indicate that As criterion is the most important element related to mineralization and Au, Ag and Sb elements take the next positions. Also, the ranking of geochemical samples shows that the anomalies obtained from all three methods are similar to cumulative anomalies. The result obtained with the FDAHP-VIKOR algorithm is due to conformity of the location and extent of the anomaly area with the geochemical anomalies of the main mineralization elements, Ag and Au elements, and the median area of this range, as compared to the other two methods which are introduced as a potential mineralization area. An area of 0.42 Km2 is proposed for the design of a borehole drilling network in a detailed exploration phase and a smaller area of 0.10 Km2 within it is proposed for designing a density drilling network. Therefore, ranking methods can be introduced as a new method for determining composite anomalies.

Keywords

Main Subjects

Full Text

نمونه­برداری­های ژئوشیمیایی از محیط­های سنگی، خاکی و رسوبات آبراهه­ای یکی از مهم‌ترین ابزارهای شناسایی مواد معدنی در فازهای مختلف اکتشافی محسوب می‌شود. از آنجا که این نمونه­ها معمولاً برای تعداد زیادی عناصر به صورت هم‌زمان آنالیز می­شود؛ بنابراین تعیین آنومالی‌های ژئوشیمیایی مرکب (چند عنصره) بر تک عنصره برتری خواهد داشت. روش آنومالی‌های جمعی و یا ضربی، روش­های تلفیق، روش­های کاهش ابعاد، روش‌های خوشه‌بندی و روش‌های رتبه­بندی راه­حل­های تعیین آنومالی­های مرکب هستند [1-3]. در روش آنومالی‌های مرکب با جمع مقادیر استاندارد شده، می­توان آنومالی‌های جمعی و با ضرب مقادیر خام، می‌توان آنومالی‌های ضربی را به دست آورد. این روش‌ها بیشتر برای تعیین هاله‌های ژئوشیمیایی مرکب استفاده شده­اند [4]. در روش‌های تلفیق کلیه لایه‌های اطلاعاتی، بر اساس مبنای الگوریتم‌های داده-محور ( از قبیل شبکه‌های عصبی مصنوعی، اوزان شاهد، رگرسیون لجستیکی، ماشین بردار پشتیبان و طبقه‌بندی بیزین) و یا دانش-محور (از قبیل شاخص همپوشانی، منطق فازی، فرآیند تحلیل سلسله مراتبی و تکنیک اولویت‌بندی با شباهت به راه‌حل ایده‌آل) به یک لایه یا نقشه تبدیل می­شود [5-7]. الگوریتم‌های داده- محور برای مناطق دارای فعالیت­های اکتشافی بالا و الگوریتم‌های دانش- محور برای مناطقی با اطلاعات اکتشافی کم کاربرد دارند [6].

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Journal of Analytical and Numerical Methods in Mining Engineering
Volume 10, Issue 23
August 2020
Pages 145-158

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History

  • Receive Date: 09 June 2019
  • Revise Date: 18 April 2020
  • Accept Date: 04 July 2020

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