GOLD POTENTIAL OF A HIDDEN ARCHEAN FAULT ZONE: THE CASE OF THE CADILLAC-LARDER LAKE FAULT

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Distribution of orogenic gold deposits along the CLLF

Spatial distribution of mineral deposits has been of great interest for the exploration and the research community even considering that mine or deposit distribution can only give an evaluation of the true metallic distribution of an area considering undiscovered deposits and economic factors. A systematic geographical distribution of mineralizations can be exploited as a valuable regional exploration tool and analogues to evaluate natural resource potentiality in under explored regions presenting similar geological context (McCammon, 1993). The mathematical function that determines the spatial distribution of orogenic gold mineralization can be used to determine fault segment which are the most favorable for undiscovered deposits along important Archean structures. Furthermore, the distribution of mineral deposits can provide insights on the formation of gold deposits.
A fractal approach was considered to explain the spatial distribution of precious metals within the Sierra Nevada (Carlson, 1991) and gold deposits in the Zimbabwe craton (Blenkinsop and Sanderson, 1999). The distribution of Archean orogenic gold deposits in the vicinity of crustal scale fault zone has also been tested along the Boulder-Lefroy Fault zone in Australia by Weinberg et al (2004) which noted a link with the presence of a gold mine and geological complexity. The approach proposed in this study is focussed on the distance separating each deposit from its neighbors and the possible relation with the distribution of mineralizing fluids pathways in structural dilation sites.

Available Data and Methodology

The spatial analysis of the distribution orogenic gold deposits along the CLLF was undertaken using information contained in the public database of the Ministry of Natural Ressources and Fauna of Quebec. The study focuses on the segment where the CLLF marks the boundary between the Abitibi and Pontiac. The length of this segment of the CLLF represents about 160 km and almost 80% of its total length.
The CLLF is often represented as a line on the 2D map even though the associated damage zone of this major structure represents a much larger area, corresponding to many hundred meters. To account for the thickness of the deformation zone and the multiple splays directly associated to the CLLF, a one kilometer buffer zone was established around the map trace of the CLLF in the sector of interest. All deposits located within this zone were used to conduct the spatial analysis. Mineralized occurrences defined by a single sample or a drill hole interception were not taken into account. The final deposit database is presented in table 1.
The deposit database was filtered to conduct the analysis only on deposits belonging to the orogenic gold type, and avoid incorporating other mineralization types with distinct characteristics, source, timing, and formation mechanism. Other types of gold mineralizations encountered in the study area are mainly volcanic massive sulfides or porphyry type deposits. Individual studies of deposits were used to determine the type of mineralization (Couture, 1996, Legault & Rabeau, 2006; Pilote et al., 2000; Lafrance et al., 2003; , Poulsen et al., 2000; Robert et al. 2005; Dubé and Gosselin, 2007). Certain known characteristics of orogenic gold deposits were also used to discriminate orogenic gold deposits from other types of gold mineralization. The metal content was the main discriminating factor on the basis that f the mineralizing fluids involved in the formation of orogenic gold have very low salinity deposits implying low base metal content (Groves et al., 2003).

Regional potential mapping using structural failure location

The location of known deposit should correspond to the localization of a structural failure du to near lithostatic fluid pressure. The cumulative frequency distribution FD [d] of the curvilinear distances D between two neighbor deposits is the
proportion of occurrences which were found within a distance d of a known deposit. By considering the number of deposits in the study, this relation can be interpreted as the conditional probability of finding a mineralized occurrence at a distance less than d from a known mineralized occurrence along a fault zone. The theoretical fitted distribution FD [d] was used to evaluate the probability of potentially unrecognized mineralized occurrences within the close vicinity of the CLLF. Deposits presenting inter-distance greater than predicted by the theoretical model (Fig. 1-4) were interpreted as indicating potential zones with possible unrecognized mineralized occurrences. To determine the probability distribution, the trace of the CLLF was regularly sampled every 10m in order to calculate the curvilinear distance to the nearest known projected deposit. This curvilinear distance was interpolated laterally on a regular grid band of 2km in extension and centered on the CLLF, giving the distance d to the nearest known deposit of any locations situated in this zone (Fig. 1-6A). The log(d) uniform distribution model was then used to derive a probability map along the full length of the Eastern segment of the CLLF. Figure 1-6b presents those results for various levels of confidence.
The results presented in Figure 1-6 have to be interpreted with caution. Since the methodology used inter distance calculation between deposits, the distance measured for deposits located on the extremities of the faults are biased. Consequently, the part of the CLLF located near the Grenville front presents a higher occurrences inter distance compared to the rest of the fault, and therefore a highest derived probability, because no deposits are present passed the Grenville Front. The Eastern part of the studied portion of the CLLF presents the same bias but it is important to note that the Kerr Addison deposits is located only a few kilometers from the Ontarian border and that there is truly a lack of deposits in this area since the CLLF is covered by the Proterozoic sediments of the Gowganda Formation (Rabeau et al., 2009) which renders classical exploration techniques difficult.

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Modeling the Archean-Proterozoic Unconformity and the Hidden Archean Units

One of the main challenges in the modeling process was the evaluation of the geometry of the unconformity between the Proterozoic cover and the Archean units underneath using structural data and very sparse data derived from drill-holes performed in the sedimentary cover (Fig. 2-5). A total of 418 surface bedding measurements were used to estimate the shape of the unconformity at depth. The structural data show that the Proterozoic sedimentary formation has a basin-like shape with very shallow dipping borders (Fig. 2-5a). The geometry of the unconformity was refined using 81 compiled diamond drill holes from which 42 intercept the base of the Proterozoic cover (Fig. 2-5b). The surface representing the unconformity was built to accommodate both sets of data giving priority to drill hole control points. The final estimation shows that, in the study area, the Cobalt Group has a thickness of up to 790 m in its western portion and becomes shallower towards the east where two inliers are present (Fig. 2-5c).

Geophysical Inversion

The gravity and magnetic data were inverted to recover the density and the magnetic susceptibility distribution in three dimensions in order to assist in interpreting the 3D geometry of certain geological entities. The airborne magnetic data of the northern half of the study area were acquired via MEGATEM technology with 125 m line spacing (Xstrata, unpublished data, 2002), whereas the data from the southern part are from a wider-spaced (200 m) public database of the Ministry of Natural Resources and Fauna of Quebec (Dion and Lefebvre, 1997). The ground gravity data represent the compilation of two databases from the Ministry of Natural Resources and Fauna of Quebec and the Geological Survey of Canada, where the distribution of the stations are heterogeneous and mostly located along roads and lake shores (Dion, 1993).
The inversion of gravity data defines a density distribution model that provides the best fit to the observed data on surface. The inversion algorithm used (GRAV3D) was developed at the University of British Columbia (Li and Oldenburg, 1998). The elevated density contrast between the units of the Pontiac and the Abitibi Subprovinces allows proper estimation of the dip of the CLLF along the total length of the model. The 3D inversion results confirm that the CLLF is steeply dipping (~ 75° N) underneath the Proterozoic cover (Fig. 2-7b). This result is consistent with the magnetic data inversion.

Spatial Analysis of Mineralized Occurrences

Computer-based methodologies such as 3D modeling can be used as predictive tools by uncovering repetitive controls on mineralization. A common method used to delineate prospective areas is to carry out a spatial analysis on a training set of data to identify factors controlling the distribution of known deposits and to use this knowledge on lesser known regions.
The 3D geological model was used to test the spatial association of specific geological features with gold occurrences. These occurrences were determined using almost 210,000 compiled gold assays. Samples analyzed for precious metals are generally well distributed within the study area even if certain sectors associated with closed mines or studied deposits over-represented (Fig. 2-9a). In order to properly evaluate the controls on orogenic gold mineralization, the database had to be filtered to remove assays derived from other mineralization types with distinct characteristics, source, timing and formation mechanism. These gold occurrences can belong to volcanogenic massive sulfide deposits, porphyry-type deposits associated with syenites, or epithermal-type deposits.

Table of contents :

CHAPITRE 1: SPATIAL DISTRIBUTION OF OROGENIC GOLD DEPOSITS ALONG MAJOR ARCHEAN FAULTS
1.1 Introduction générale
1.2 Abstract
1.3 Introduction
1.4 Geological setting
1.5 Distribution of orogenic gold deposits along the CLLF
1.6 Available Data and Methodology
1.6.1 Validation of the spatial distribution
1.7 Discussion
1.7.1 Regional potential mapping using structural failure location
1.8 Conclusions
1.9 Acknowledgements
1.10 References
1.11 Annexe 1
CHAPITRE 2: GOLD POTENTIAL OF A HIDDEN ARCHEAN FAULT ZONE: THE CASE OF THE CADILLAC-LARDER LAKE FAULT
2.1 Introduction générale
2.2 Abstract
2.3 Introduction
2.4 Geological Setting
2.5 Geological Modeling
2.5.1 Modeling the Archean-Proterozoic Unconformity and the Hidden Archean Units
2.5.2 Geophysical Inversion
2.6 Spatial Analysis of Mineralized Occurrences
2.6.1 Lithologies
2.6.2 Faults and Fault Intersections
2.6.3 Distance to Intrusive Rocks
2.7 3D Mineral Potential Mapping under the Proterozoic Cover
2.7.1 Cross-Validation of the 3D potential map
2.8 Conclusion
2.9 Acknowledgements
2.10 References
CHAPITRE 3: 3D STRAIN MODELING DRIVEN BY FIELD DATA IN THE VICINITY OF THE CADILLAC LARDER LAKE FAULT ZONE: INSIGHTS ON ARCHEAN OROGENIC GOLD
3.1 Introduction générale
3.2 Abstract
3.3 Introduction
3.4 Geological Setting
3.5 Tectonic evolution and timing of gold mineralizations
3.6 Geomechanical modeling
3.7 3D Geological Model and Strain Modeling applied to the CLLF
3.7.1 Modeling parameters
3.7.2 Boundary conditions
3.8 Results
3.8.1 Spatial association between mineralized sites and dilatant zones
3.9 Discussion
3.9.1 Limitations:
3.10 Conclusion
3.11 Acknowledgements
3.12 References
CONCLUSIONS
Références

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