Page 183 - Geochemical Anomaly and Mineral Prospectivity Mapping in GIS

184 Chapter 6

spatial association with nearest neighbour linear or point geological features. A
limitation of the distance correlation method is that it is not applicable to the analysis of
spatial association between mineral deposit occurrences and geochemical anomalies.
The observed differences in the results of the distance distribution method and the
distance correlation method illustrate, however, that spatial associations of mineral
deposit occurrences and certain geological features can only be quantitatively explored
but cannot be definitely confirmed. Nevertheless, the results of analyses of spatial
associations between mineral deposit occurrences and certain geological features can
provide ideas for new investigations that may lead to further understanding of geologic
controls on occurrences of mineral deposits of the type sought in a particular area. For
example, the similar results of the applications of the distance distribution method and
distance correlation method that there is positive albeit very weak spatial association
between the epithermal Au deposit occurrences and NE-trending faults/fractures in the
case study area (Table 6-IX) suggest that the set of all NE-trending faults/fractures (see
Fig. 5-13) probably represents various processes or structural regimes. However,
because the distance correlation method makes use of only linear (or point) geological
features that are closest to the known occurrences of mineral deposits of interest, it is
plausible that the epithermal Au deposits in the study area are associated with only one
of the possible various structural regimes represented by the NE-trending
faults/fractures. More importantly, the results of analyses of spatial associations between
mineral deposit occurrences and certain geological features in conjunction with the
results of analyses of spatial distribution of mineral deposit occurrences are useful in
defining a conceptual model of mineral prospectivity.
From the results of analyses of spatial associations between the epithermal Au
deposit occurrences and individual sets of geological features shown in Table 6-IX, it is
possible to rank the examined geological features according to their relative importance
to the occurrence of mineral deposits of the type sought. Note that, as stated earlier, the
smaller the distance of positive spatial association, the stronger the spatial dependence.
This proposition can be supported by estimation of likelihood of mineral deposit
occurrence as the ratio of the proportion (or percentage) of deposits in zones within the
distance of optimum positive spatial association with a set of certain geological features
to the proportion (or percentage) of zones in a study area within that distance from the
same set of geological features. This analysis is supported directly by the distance
distribution method [i.e., dividing Ô(X) by Ê(X)] but can also be derived based on the
results of the distance correlation method. Thus, the following recognition criteria of
prospectivity for epithermal Au deposits, arranged according to decreasing importance,
are postulated for the case study area:
ƒ proximity to NNW-trending faults/fractures (representing structural controls);
ƒ proximity to intersections of NNW- and NW-trending faults/fractures (representing
structural controls and proxy for heat source controls); and
ƒ proximity to NW-trending faults/fractures (representing structural controls).
By integrating these interpretations with those derived from the analyses of spatial
distribution of the epithermal Au deposit occurrence, a conceptual model of structural