Multivariate geostatistical simulation of compositional data using Principal Component Analysis
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Authors
Bolgkoranou, Maria
Date
Type
thesis
Language
eng
Keyword
Geostatistics , Multivariate Geostatistical Modeling , Principal Component Analysis
Alternative Title
Abstract
In the mining industry, there is interest in the use of spatial processes to model spatially collected data. For the multivariate observations, we should model associations at a specific location and between locations, but also among variables. Common methods for multivariate modeling rely on the Linear Model of Coregionalization (LCM), which is limited in higher dimensions and generates models that do not properly reproduce the features of the original multivariate samples.
In this thesis we present a simple methodology for multivariate geostatistical modeling of compositional data using Principal Component Analysis (PCA). According to the methodology, grades are, first, transformed to log-ratios. Then, these log-ratios are linearly transformed to Principal Components (PCs). PCA tends to spatially decorrelate the factors, allowing for the independent simulation of each PCs, instead of requiring a co-simulation. Sequential Gaussian Simulation is performed independently on each Principal Component and the simulated factors are then back-transformed to simulated log-ratios, and these are finally back-transformed to grades.
Using a 6-dimensional data set from a Nickel-Laterite deposit, we demonstrate the difference between the proposed methodology and classical co-simulation. The statistics and the further validation of the back-transformed grades after PCA and Sequential Gaussian Simulation showed that the proposed methodology tends to respect the relationships between the variables whereas co-simulation of the grades tends to respect the statistics but the reproduced relationships are not representative.
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CC0 1.0 Universal
Queen's University's Thesis/Dissertation Non-Exclusive License for Deposit to QSpace and Library and Archives Canada
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.
Queen's University's Thesis/Dissertation Non-Exclusive License for Deposit to QSpace and Library and Archives Canada
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.