BUREAU VERITAS MINERALS | SPECTRAL SERVICES (PERTH) | 11-2015

PROJECTOR ASPECT RATIO = 16:9

SPECTRAL DEVICES

Hylogger (FLSmidth, developed by CSIRO)

CORE

CHIPS

PULPS

► TerraSpec ASD Spectrometer integrated with rapid X-Y table and high resolution photography

► VNIR (380 – 1000nm)

► SWIR1 and 2 (1001 - (1800) - 2500nm)

HYLOGGER

Wavelength (nm)

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ecta

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SPECTRAL DEVICES

FTIR (Fourier Transform Infra-Red)

► Thermo Nicolet FTIR with

Diffuse Reflectance

Accessory

► SWIR (1665 – 3000nm)

► M-LWIR (3-12µm)

► TIR (12-26.5µm)

PULPS

FTIR

Carbonates

Quartz

Kaolinite

Hematite

► Collected spectra is representative of the molecular bonding in the sample due to the absorption of incident light at specific characteristic wavelengths

► Interpretation of spectral features can therefore be correlated primarily with mineralogy

► Technique compliments existing logging, assays and mineralogical analysis.

► Part of a routine geochemical and geomet workflow

► Alternate sample presentations available for Hylogger

► Non destructive

► Future interpretation possible without re-collection of spectra

► Improve your asset – create lasting digital records

► Analysis of archive samples to build knowledge library

SPECTRAL ANALYSIS PRINCIPLES

Spectral Interpretation Chemometric Approach

Spectral features are matched to spectral library of known

minerals

• Complete Spectra, or,

• Specific features may be used

• Hylogger interfaces with TSG Software

1. Train - Calibration samples, with known data, are

measured and a model is created

2. Prediction - Unknown samples are measured and the

spectra passed through the model to obtain a result.

Specific features in the spectra are ignored.

SPECTRAL ANALYSIS APPROACHES

Both techniques can be used for Hylogger and FTIR

CHEMOMETRIC APPROACH

1. Train Calibration samples, with known data, are measured and a model is created. Multiple techniques are used to obtain the best outcome for your sample types. (PLS, SVM, ANN)

2. Prediction Unknown samples are measured and the spectra passed through the model to obtain a result

How do we use this data for routine analysis?

Spectral Chemometric analysis is a two step process:

CHEMOMETRIC APPROACH

Bauxite matrix, PLS Calibration - 1006 samples from XRD. Validation 668 samples.

Matrix/dominant mineral

CHEMOMETRIC APPROACH

Bauxite matrix, PLS Calibration - 1006 samples from XRD. Validation – 668 samples.

Trace mineral

CHEMOMETRIC APPROACH

Iron ore matrix, ANN Calibration - 149 samples from XRD, Validation – 33 samples

Substitution Analyte

FTIR CHEMOMETRIC APPROACH

Element speciation

Iron Ore magnetite matrix, PLS Calibration - 250 samples from classical method. Validation 106 samples.

FTIR CHEMOMETRIC APPROACH

Physical property

Iron Ore magnetite matrix, PLS Calibration - 140 samples from pycnometer method. Validation 138 samples.

► Analytes can be:

• Elements (e.g. Fe, Fe2+, Al, Si)

• Minerals (e.g. Gibbsite, Hematite, Goethite, Kaolinite, Talc, Quartz)

• Physical properties (e.g. LOI, SG/Density)

► The success of calibrating an element, mineral or property relies on it having a spectral fingerprint that is distinguishable in the IR range.

► Typically, hydroxides, carbonates, sulfates, silicates, some oxides

► Quantification detection limit, typically 1%, Accuracy typically 10% (relative).

► Typically 200-500 samples for calibration, can be historical data with classical analysis, or geo logging (logging data, XRD, physical data, production data)

CHEMOMETRIC APPROACH

Summary

► Rapid, low cost analysis (compared to classical techniques)

► Non destructive, simple, robust equipment

► No special sample preparation

► Hylogger measured directly on core, chips or pulp samples.

► FTIR measured on pulp samples

SPECTRAL ANALYSIS

► Multiple minerals and analytes from the same spectra

► Calibration tailored to local mineral context and/or key mineral

processing parameters

► Calibration can be refined and improved over time with new data

► Re-run historical spectra against new model

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