Spatial Analysis of Regional-scale Controls on VMS
Mineralization, Skellefte District, Sweden
Martiya Sadeghi
Geological Survey of Sweden, Uppsala, SE-751 28, Sweden
Emmanuel John M. Carranza
International Institute for Geo-Information Science and Earth Observation, Enschede, 7514AE, The Netherlands
Abstract. In the Skellefte district (Sweden), the
relationship of volcanogenic massive sulphide (VMS)
deposits with structures and lithostratigraphic units is still
not well understood. Fry analysis of the spatial pattern of
the VMS deposits and weights-of-evidence analysis of
the spatial associations of the VMS deposits with
deformation zones and lithostratigraphic units suggest
strong structural and lithostratigraphic regional-scale
controls on VMS mineralization in the Skellefte district.
Keywords. Point pattern, Fry plots, weights-of-evidence,
spatial association, shear zones, lithostratigraphy, GIS.
1 Geology of Skellefte district
The Skellefte district (SD), a loosely defined area of ca.
150 km by 50 km in northern Sweden, is situated in the
transition zone between the Bothnian Basin in the south
and terranes of mainly marine supracrustal rocks and
terrestrial island-arc assemblages in the north that are
divided into the Skellefte, Vargfors and Arvidsjaur
Groups (Fig. 1). In the SD, epiclastic and turbiditic
sedimentary rocks interfinger with the subaqueous
volcano-sedimentary rocks of the Skellefte Group (SG)
and the Vargfors Group (VG). The subaqueous volcanosedimentary rocks of the SG pass stratigraphically
upwards and topographically northwards into the
subaerial volcanic rocks of the Arvidsjaur Group (AG),
which are marine equivalents of the volcanosedimentary rocks of the VG. The VG consists mainly of
coarse clastic and turbiditic sedimentary rocks deposited
on the SG and BS and on the lower parts of the AG
(Kathol and Weihed, 2005). The southwestern and
eastern parts of the SD are underlain by intrusive rocks
of the Transscandinavian Igneous Belt.
The deformations and metamorphism in the SD are
mainly related to the Svecofennian Orogen (Bergman
Weihed 2001). The deformations include folds,
penetrative WNW-ESE to E-W cleavages and ductile
shear-zones. The shear zones cut the late post-orogenic
granitoids. The youngest shear zones trend N-S
(Bergman Weihed, 2001). The WNW-ESE striking
Skellefte Shear Zone (SSZ) in the central part of the SD
has mainly oblique-slip movements (Malehmir et al.,
2006) and its south side up is commonly up-thrown
(Bergman Weihed, 2001).
The SD has long been regarded as a volcanogenic
massive sulphide (VMS) district. There are 72 known
occurrences of VMS deposits in the district, more than
20 of which have been mined in the past and five of
which are being mined at present. The characteristics of
the VMS deposits in the SD are strongly similar to
Kuruko-type VMS deposits (Weihed et al., 2005). The
VMS deposits in the SD and in the whole of the
Fennoscandian Shield were formed between 1.97 and
1.88 Ga in extensional settings prior to basin inversion
and accretion (Weihed et al., 2005). That the VMS
deposits in the SD were formed in a strongly extensional
intra-arc that developed in a continental or mature arc
setting rather than in primitive volcanic arc setting is
evidenced by the stratigraphic architecture, range of
volcanic compositions and abundance of rhyolites
(Allen et al., 2002). Geophysical modeling suggests
that, in the western part of the SD, VMS deposits occur
on the northern limb of a regional E-W striking syncline
(Malehmir et al., 2006). The VMS deposits occur in
either the SG or VG, although they commonly occur
near the upper horizons of the SG.
In this paper, we present results of spatial analyses in
order to infer controls on VMS mineralization in the SD.
2 Spatial pattern analysis
Figure 1. Simplified geological map of the Skellefte district
(from Kathol and Weihed, 2005).
Proceedings of the Tenth Biennial SGA Meeting, Townsville, 2009
We performed Fry analysis in order to study the spatial
pattern of the VMS deposits in the SD. Fry analysis (Fry
1979) is a geometrical method of spatial autocorrelation
analysis of a type of point objects, like mineral deposits
845
Figure 2. (a) Fry plots (black dots) of 72 VMS deposits
(green dots). Rose diagrams of (b) of all pairs of Fry plots and
(c) only pairs of Fry plots within 75 km of each other. n = 72.
on regional-scale maps. For n number of points, n2-n
number of so-called Fry points created. Thus, if there are
subtle patterns in a set of point objects in terms of
spacing and orientation, a plot of Fry points enhances
such patterns. A rose diagram can be created for (a) all
pairs of Fry points and (b) pairs of Fry points within a
specified distance. The former case may reveal trends
due to processes that operated at, say, a regional scale,
whereas the latter case may reveal trends due to
processes that operated at, say, a prospect scale. Previous
works using Fry analysis to study mineralization controls
are described in Vearncombe and Vearncombe (1999)
and Carranza (2008, 2009).
The Fry points of the 72 occurrences of VMS deposits
in the SD show a primary 100-110º azimuth trend and
secondary trends of 90-100º and 110-120º (Fig. 2a,b),
suggesting regional-scale controls by WNW-ESE
trending geological features. Analyses using different
distance separations between Fry points were performed
in order to determine whether the 72 points represent a
homogenous population of VMS deposits or if they
constitute different groups of deposits. The highest
changes in frequencies of trends between Fry points
occurred when distances between 75 km and 150 km
were used. The latter is the distance within which, from
any of the VMS deposits, there is maximum probability
that all the other VMS deposits are present. The rose
diagram for Fry points within 75 km of each other show
two main directions of 100-110º and 130-140º, and one
secondary direction of 40-50º. The two main directions
suggest regional-scale controls by NW-SE to WNW-ESE
trending geological features, whereas the secondary
direction suggests prospect-scale controls by NE-SW
trending geological features.
3 Spatial association analysis
We applied weights-of-evidence (WofE) analysis in
order to quantify spatial association between a map of
points (i.e. mineral deposit locations) and a map of linear
features (e.g., faults of certain trends) or a map of
polygonal features (e.g., lithologic units of the same
type). For a map of linear features, a multi-class map
based on cumulative increasing distances (or buffer
zones) is created. For a map of polygonal features, each
846
polygon is considered a binary (presence-absence)
pattern. For each class or spatial pattern, P, in a binary or
a multi-class map, the type and magnitude of its spatial
association with a set of points, D, can be characterized
by calculation of a spatial statistic called contrast (C)
(for details of estimation see Bonham-Carter 1994). The
value of C is related to the area of P (denoted as N(P))
and to the number of points contained in P (denoted as
N(DP)). If C>0, then there is positive spatial
association between P and D; whereas if C<0, then there
is negative spatial association between P and D. A
positive spatial association is of interest because it
implies that the occurrence of D is ‘dependent’ on (i.e.
controlled by) P. The statistical significance of spatial
association can be determined by calculating Studentized
C, which is the ratio of C to its standard deviation. A
Studentized Ct2 indicates a statistically significant
positive spatial association.
There is a variety of regional-scale geoscience data
sets available and suitable for VMS prospectivity
mapping in the SD. Of these data sets, we quantified
spatial association of the VMS deposits with the
different lithostratigraphic units in the SD, the SG-VG
contact, and different sets of shear zones according to
their trends. For each of the linear geological features,
we sought the pattern representing the largest buffer
distance within which the Studentized C is at least 2. In
the WofE analyses, we used a raster-based GIS and a
pixel size of 200 m for the spatial representation of the
VMS deposits and the geological features.
3.1 VMS – shear zone association
Shear zones have been mapped in the field or interpreted
from aeromagnetic data. We compiled the mapped and
interpreted shear zones and then classified them into six
classes according to their trends: NNE (0-30º); NE (3060º); ENE (60-90º); WNW (270-300º); NW (300-330º);
NNW (330-360º). The results of the WofE analysis show
that the VMS deposits have statistically significant
positive spatial associations with WNW-, NW- and
ENE-trending shear zones (Table 1). At least 70% (t51)
of the VMS deposits are within 3.7 km of each of these
three sets of shear zones. The pattern formed by a 3.16
km buffer around WNW-trending shear zones has the
highest positive value of Studentized C, followed by the
pattern formed by a 3.23 km buffer around NW-trending
shear zones and then by the pattern form by a 3.7 km
buffer around ENE-trending shear zones.
3.2 VMS – SG-VG contact association
We reclassified the 1:250,000 scale lithostratigraphic
map of the SD and surrounding areas (Kathol and
Weihed, 2005) according to groups in order to extract
the contact between the SG and VG. We considered the
SG-VG contact for analysis because most of the VMS
deposits are known to occur in lithologic units in the
uppermost horizons of the SG, which is overlain by the
VG. The results of the WofE analysis show that 67 (or
about 93%) of the 72 VMS deposits occur within 12.02
km of the SG-VG contact (Table 1). This implies that
the VMS deposits have statistically significant positive
"Smart Science for Exploration and Mining" P. J. Williams et al. (editors)
Table 1. Skellefte district: spatial patterns (P) of geological
features having statistically significant positive spatial
associations with VMS deposits as quantified by weights-ofevidence analysis. Studentized C is calculated using (see
Bonham-Carter 1994): N (P), area of a pattern expressed in
number of pixels; and N (DP), number of pixels in a pattern
(P) that contain deposits (D).
Spatial pattern (P)
N(P)
N(DP) Studentized C
Shear zones:
WNW (0.00-3.16 km)
129736
63
3.188
NW (0.00-3.23 km)
171867
60
2.773
ENE (0.00-3.70 km)
179928
51
2.282
Stratigraphic contact:
SG-VG (0.00-12.02 km)
130369
67
2.404
Lithostratigraphic units:
SG felsic volcanics
SG sediments
SG mafic volcanics
31952
5006
8879
48
10
6
12.923
7.717
3.458
of the SG and the VG is approximately the same or that
the difference in the timing of their deposition is less
than 5 million years. That is because, although most of
the VMS deposits occur on the upper horizons (i.e.,
felsic volcanics) of the SG, there are few occurrences of
VMS deposits in the lower horizons of the VG.
The analysis of the spatial pattern of mineral deposits
and the analysis of their spatial associations with certain
types of geological features could provide insights into
mineralization controls, which could be useful in
mapping of prospectivity for the type of mineral deposits
sought. Therefore, regional-scale prospectivity for VMS
deposits in the SD can be modelled based on proximity
to WNW-, NW- and ENE-trending shear zones,
proximity to the contact between the SG and the VG, and
presence of felsic volcanics of the SG.
Acknowledgements
spatial association with the SG-VG contact.
The first author is thankful to the Geological Survey of
Sweden for funding of internal research project No35137.
3.3 VMS – lithology association
References
Based on lithostratigraphic map of the SD and
surrounding areas (Kathol and Weihed, 2005), about 64
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This observation and the results for the SG-VG contact
indicate that the VMS deposits occur in the upper
horizons of the SG below its contact with the VG. The
results further show that the VMS deposits have highest
statistically significant positive spatial association with
the felsic volcanics in the SG, followed by the sediments
and then the mafic volcanics in the SG.
4 Discussion and conclusions
The results of the WofE analysis of the spatial
associations of the VMS deposits with classes of shear
zones according to trends (Table 1) are relatively
consistent with the results of the Fry analysis (Fig. 2).
This means that Fry analysis and WofE analysis are
complementary tools for study structural controls on
certain types of mineralization, in this case VMS
deposits in the SD. Thus, the principal WNW trends in
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