Fosterville Gold Mine, Victoria
approximately 20km north-east of Bendigo in Central Victoria,
Fosterville is an established gold mine operated by Perseverance
Exploration. The deposit is hosted in a sequence of interbedded
Ordovician sandstones and shales (turbidites) and consists of a series
of approximately north-south striking structurally controlled ore
bodies. Extraction of gold from oxide material is currently being
carried out using heap leach. Mineralisation continues into the sulphide
initial PIMA survey was carried out on 50 grab samples from grade
control drill spoil in the pit. Assay data from this grade control
drilling was compared with the spectral data. Although the assay data
was taken from 5 metre composite samples and there was only poor control
on the PIMA samples, there appeared to be a relationship between gold
and the position, and shape of the AlOH absorption feature between
around 2196 and 2218nm. Further work indicated that illite composition
could be correlated with the distribution of mineralisation.
understand the spatial
relationships between illite compositions and gold, the analysis of over
700 located grade control assay pulps was carried out. The spectra in
the Fosterville dataset come from these grade control sample pulps.
the Fosterville zip file to your PC and then unzip it. There are three
files in the zip file, Fosterville.tsg, Fosterville.bip and
Fosterville.ini, all three files are required to be in the same
directory for you to successfully open the TSG file and view the
Fosterville file is a deceptively simple data set because there are only
2 principal mineral groups recognised in the spectral data
(illite/muscovite and kaolinite). However, the
dataset is particularly challenging because of the apparent lack of
significant variation in mineralogy throughout these samples. In fact it
is very easy to discard a dataset like this if only traditional analysis
techniques such as visual interpretation are used. Unfortunately, this
is almost certainly true of many datasets analysed prior to the
availability of software like TSG. It is not until these data are
analysed as an integrated and spatially related dataset
that the significance of the spectral data becomes apparent.
set is useful because it demonstrates how many of TSG's analysis
functions and display graphics can be used to resolve a wealth of
invaluable mineral information directly related to alteration and the
distribution of the target mineralisation.
a series of steps that you might like to follow which demonstrate a
variety of TSG analysis features using the Fosterville dataset.
Start up TSG
Open up the
Fosterville tsg file. The file has been set up already and should
open up with the TSG screens already prepared for the following
steps. The set up information is saved in the .ini file
associated with the data set. If you are using a copy which has been
changed since its creation you may need to set up some of the
selection of the spectra in the Spectrum screen. You will notice
that the data are fairly monotonous consisting primarily of spectra
dominated by illite group minerals with generally weaker proportions
of kaolinite. All kaolinite here is weathering related.
Go to the
Scatter plot screen, if not already set up you can build each graph
as they are described.
plot screen should be set up to show 8 plot windows in 4 columns and
2 rows . We will refer to these Plot Windows as PW1 to
8 from top left to bottom right. When using the Scatter plot screen
it's best to have TSG maximised on your screen desktop. If your
screen resolution is still too low to see the data clearly try
working with fewer (eg 2) plot windows and scroll through them using
the small up and down arrows next to the Subs onscreen
Remember at any
stage you can pop up the floater window to examine the spectrum of
any of the data points displayed.
PW1 to 5 are all spatial plots
and use X = Eastings, Y = Northings, with the data points coloured
by different scalars.
- this plot shows the spatial distribution of Au (ppm) across the
dataset. X = Eastings, Y = Northings and Aux = Au. The colour of the Au
scalar is scaled between 0 and 2 ppm. To change the colour scale click
the RH mouse button and select Scale from the pop up menu, which will
pop up the Scale dialogue. This lets you set the scale for the x
and y axes as well as the scalar used for the data point colours.
- this plot shows the spatial distribution of variations in the
wavelength of the main AlOH absorption feature (Aux = Wave_AlOH). This
scalar is calculated from a spectral profile, in PW2 it is colour scaled
from 2206 to 2210nm. To see how this scalar was calculated select the
scalar column and then select Edit/add/delete > modify scalar
from the RH mouse pop up menu in the Log screen.
- this plot shows the spatial distribution of a feature parameter scalar
(feature 2196) which reads the wavelength of absorption features in the
vicinity of 2196nm (paragonites).
Calculating values from feature parameters often works well when the
target absorption is not the dominant local feature. This is frequently
the case for AlOH absorptions associated with paragonitic micas at
Fosterville, as the AlOH absorption is dominated by the kaolinite and
the 2196nm paragonite feature is usually only evident as an inflection.
Simply calculating the wavelength of the dominant AlOH feature (see PW2)
tends to give intermediate values influenced by any AlOH minerals
present (kaolinite, phengitic and paragonitic illites at Fosterville).
Although the feature parameter may not identify the paragonite with a
100% success rate, because of the large number of samples in this
dataset and because they are all located we can still get a strong
indication of the distribution of these illites with respect to the Au
mineralisation in PW3. Therefore, the spatial distribution of the
short wavelength (paragonitic) illites in PW3 clearly shows the spatial
relationship between Au mineralisation (PW1) and the distribution of
this illite phase.
working in environments containing a number of minerals possessing
coincident or nearly coincident diagnostic absorption features it is
important to develop analysis or processing strategies that can be used
to separate and identify these minerals. Here at Fosterville we have a
number of AlOH phyllosilicates, some alteration related (paragonitic
illites), some related to unaltered country rock (phengitic illites),
some widely spread (muscovites) and some weathering related
and 5 are both parameters designed to map kaolinite. Its often
useful to try out a couple of different processing strategies targeted
at a particular mineral and then to compare the results. The similar
spatial distribution of data in PW4 and 5 tends to indicate that these
parameters are both mapping kaolinite distribution quite effectively.
These results can be checked further by using the Floater window to
check some of the sample spectra.
parameter used in PW4 (feature 2160) is a feature parameter measuring
the depth of the secondary kaolinite AlOH absorption near to 2160
nm. The parameter used in PW5 is a parameter that measures the slope
of the 2160nm feature, this is less than 1 for kaolinitic samples and
greater than 1.02 for those samples with negligible kaolinite. This
second plot visually maps the kaolinite distribution very well, and
makes a good comparison with the Au plot (PW1), basically the elevated
Au zones are where there is negligible kaolinite (shown in dark blue).
PW6, and 7 are all scatter plots where the X axis is a
spectral profile scalar representing the wavelength of the dominant AlOH
feature (Wave_AlOH). The Y axis in these plots is a spectral profile
scalar representing the depth of the dominant AlOH feature (DepthAlOH).
In these samples kaolinite has the effect of increasing the brightness
or albedo of the sample and the relative depth of the AlOH absorption
feature, as a result kaolinite rich samples tend to have higher Y values
in these plots. Because the wavelength of the kaolinite AlOH absorption
does not vary to any great extent samples with higher kaolinite
proportions tend to cluster around 2206 to 2208nm (X axis). Conversely
the mass of samples spread across the X axis with lower Y values tend to
be dominated by illites of varying composition (paragonitic, muscovitic
uses TSA illite weight to colour the data points, here cooler colours
indicate less illite (more kaolinite in these data), as expected the
higher illite weights are found towards the base of the plot.
show a similar trend however this time the auxiliary scalar is the
"feature 2160" scalar used in PW4 to map kaolinite. Here the hotter
colours indicate stronger kaolinite responses towards the top of the
is a histogram of AlOH wavelengths for all samples, illustrating broadly
the three influences on the AlOH wavelengths on these samples: the large
middle peak is dominated by kaolinite, the small peak near 2205nm
represents those kaolinitic samples mixed with the paragonitic illite,
and the weak peak near 2211nm is associated with the phengitic illites
mixed with kaolinite. These can be checked using the Floater
you may like to look at how the data points in the scatter plots relate
spatially to their position in the E-N plots. To do this click the
RH mouse button to get the pop up context menu, select Class
browse/edit and then turn on the lasso option. You can then
select clusters of data points with the lasso and see where those
samples occur in the other plots.
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