Geostatistical Analysis of Vein Geometry: A Comparative Study and Proposed Framework for Improved Resource Estimation
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Authors
Yildirim, Seyda
Date
2025-02-03
Type
thesis
Language
eng
Keyword
Geostatistics , Mining , Vein-type deposits , Geological Modeling
Alternative Title
Abstract
Vein-type gold deposits are pivotal within the mining industry, yet accurately defining the boundaries between mineralized veins and host rocks remains a persistent challenge. These delineations are crucial for precise resource estimation and directly impact the economic viability of mining projects. Existing methodologies, including conventional geostatistical techniques, often fail to adequately capture the complex geological nature of vein deposits, potentially leading to the under- or over-estimation of ore reserves. This study seeks to address these limitations by enhancing boundary definition methods through the application of advanced geostatistical techniques such as indicator kriging and cokriging. A comprehensive case study, utilizing over 14,000 drilling samples, was conducted to assess the accuracy and practical applicability of these methods in estimating vein boundaries. Each method presents distinct advantages and disadvantages: Indicator Kriging quantifies the probability of belonging to the vein, providing straightforward categorization, while cokriging utilizes spatial correlations between variables for improved accuracy. Although indicator kriging is simpler to implement, co-kriging is provided more precise boundary delineation due to its ability to incorporate multiple variables. By the conclusion of this study, it was determined that Cokriging, by leveraging spatial correlations between variables, proved more effective than Indicator Kriging for vein-type deposits. Given the unique characteristics of each vein-type gold deposit, automating the procedure for determining optimum parameters is essential. This automation not only improves the modeling process by providing the most suitable approach for each specific case but also ensures the generation of more accurate and reliable data, which significantly affects long-term mining decisions and economic outcomes. An automated framework, developed using Python and GSLIB, facilitated the efficient execution of these techniques. The findings are expected to significantly mitigate boundary estimation errors, ultimately leading to more reliable resource estimates and more informed decision-making, thus enhancing the overall economic feasibility of mining projects.
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ProQuest PhD and Master's Theses International Dissemination Agreement
Intellectual Property Guidelines at Queen's University
Copying and Preserving Your Thesis
This publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner.
Attribution-NonCommercial-NoDerivatives 4.0 International