Page 185 - Geochemical Anomaly and Mineral Prospectivity Mapping in GIS

186 Chapter 6

to local-scale intersections of strike-slip fault/fractures represent the results of the fractal
analysis. The hydrothermal fluids were further dispersed, however, outwards from the
center of a dilational jog, but they were trapped by the major NNW-trending strike-slip
faults/fractures bordering a dilational jog. Thus, it can be hypothesised that less
productive or barren epithermal veins formed at the central parts of a dilational jog (or
intersection of NNW- and NW-trending faults/fractures) whereas more productive
epithermal veins formed close to major NNW-trending strike-slip faults/fractures
bordering a dilational jog. These interpretations represent the quantified spatial
associations between epithermal Au deposit occurrences and the NNW-trending
faults/fractures, NW-trending faults/fractures and intersections of these two sets of
faults/fractures and the field observations that Au-bearing quartz veins in the study area
are associated mostly with NNW-trending faults/fractures (Mitchell and Leach, 1991) .
In addition to the above-mentioned prospectivity recognition criteria, which
constitute a conceptual model of geologic controls in the case study area, the following
non-geologic control is an important prospectivity recognition criterion to consider:
ƒ presence of multi-element stream sediment geochemical anomalies (representing
surficial expressions or evidence).
A conceptual model of geologic controls and surficial expressions of mineral deposits of
the type sought, which can be referred to as a deposit exploration model, provides the
theoretical framework for mineral prospectivity mapping.

CONCLUSIONS
Because the geological processes involved in mineralisation are too complex to be
modeled in a GIS in order to predict prospective areas for further exploration, a
conceptual model of geologic controls on mineralisation forms the basis of GIS-based
modeling of mineral prospectivity. A conceptual model of geologic controls on
mineralisation is usually a synthesis of exploration experience, qualitative analysis (i.e.,
review of existing knowledge about mineral deposit formation) and quantitative analyses
of spatial distributions of mineral deposit occurrences and their spatial associations with
certain geological features. The quantitative (GIS-based) analyses are based on the
general geological characteristics of mineral deposits of interest described in mineral
deposit models and on the specific geological characteristics of known occurrences of
mineral deposits of the type sought in a particular area. In the literature about mineral
deposit geology, several recent studies demonstrate applications of similar but different
GIS-based techniques to support conceptual modeling of geologic controls on
mineralisation (e.g., Groves et al., 2000; Coolbaugh et al., 2002; Porwal et al., 2006c;
Bierlein et al., 2008; Hronsky and Groves, 2008).
The GIS-based methods explained and demonstrated in this volume, as well as those
in the literature about mineral deposit geology, illustrate the utility of exploratory spatial
data analyses in studying patterns of mineral deposit occurrences and the plausible
factors or controls on such spatial patterns. These analyses constitute an inductive
process because they lead to conceptualisation of geologic controls on mineralisation