Geological Domaining with Unsupervised Clustering and Ensemble Support Vector Classification

Article Geochemistry & Geophysics

A combined multivariate approach analyzing geochemical data for knowledge discovery: The Vazante - Paracatu Zinc District, Minas Gerais, Brazil

Ilkay S. Cevik et al.

Summary: The Vazante Group in Minas Gerais, Brazil, hosts world-class zinc silicate deposits and Pb-Zn sulfide deposits. A recent study revealed base metal sulfide mineralization in siliciclastic rocks prior to orogenic events. Multivariate analysis showed that the siliciclastic rocks exhibit preorogenic mineralization geochemical signature traits.

JOURNAL OF GEOCHEMICAL EXPLORATION (2021)

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Article Metallurgy & Metallurgical Engineering

A Simple Unsupervised Classification Workflow for Defining Geological Domains Using Multivariate Data

Fouad Faraj et al.

Summary: In natural resource industries, the increasing amount of data recorded during sampling sites has made geostatistical analysis more challenging. Traditional methods of establishing domains are time-consuming, but a newly proposed unsupervised classification workflow allows practitioners to input domain knowledge easily and can be applied for various purposes.

MINING METALLURGY & EXPLORATION (2021)

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Review Energy & Fuels

Machine Learning-A Review of Applications in Mineral Resource Estimation

Nelson K. Dumakor-Dupey et al.

Summary: Mineral resource estimation involves determining the grade and tonnage of a deposit, with conventional methods and emerging machine learning techniques showing superior performance in approximating complex relationships among geological parameters.

ENERGIES (2021)

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Article Geosciences, Multidisciplinary