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Paper Number: 145
A
fractal measure of the spatial relationships between geological features
and mineral deposits
Renguang Zuo 1
1State
Key Laboratory of Geological Processes and Mineral Resources, China
University of Geosciences, Wuhan 430074, China (E-mail:
zrguang@cug.edu.cn)
__________________________________________________________________________
Quantifying the spatial relationships between geological features
(e.g. controlling factors for mineralization) and mineral deposits is
significant in mapping mineral prospectivity. A fractal relation was
proposed to measure the spatial relationships between geological
features and mineralization in this study. A power relation between the
density of mineral deposits (ρ) and the buffer width
(ε) of geological features (e.g. faults and intrusions) which
control the spatial distribution of mineral deposits was observed. This
relation gives ρ=Cεa–2, here,
a is the singularity index[1], and C is a
constant. a < 2 indicates a significant spatial correlation
between geological features and mineral deposits, meaning that the more
mineral deposits occurred near geological features. The lower a
value suggests a much more significant spatial correlation between a
specific geological feature and mineral deposits. Taking the Fujian
Province in China as an example, NNE–NE-trending faults, Yanshanian
intrusions, and Late Paleozoic marine sedimentary rocks and the
carbonate formations (C-P Formation) are three key factors controlling
the formation of skarn Fe mineralization. The relations between the
buffer width of geological features and the density (= the cumulative
number of Fe deposits /the buffer width) exhibited a perfect fractal
statistic. The obtained singularity index suggested that the
significance of Yanshanian intrusions and C–P Formation are greater than
that of NNE–NE-trending faults in controlling the formation of Fe
mineralization[2]. In addition, the fractal relation was also
observed between Jurassic to Cretaceous intermediate–felsic volcanic
rocks (Fig.1a), intrusions (Fig.1b), and Cu polymetallic mineralization
in southwest Fujian in China. The singularity index provided an
alternative approach to measure the spatial association between
geological features and mineral deposits.
a b
Fig.1. Log-log plots of buffer width of Jurassic to Cretaceous
intermediate–felsic volcanic rocks (a) and intrusions (b) versus the
density of mineral deposits.
References:
[1] Cheng Q (2007) Ore Geol. Rev. 32: 314–324.
[2] Wang Z (2015) Journal of Earth Science 26(6): 813-820.
