Paper No. 11
Presentation Time: 4:20 PM
SPATIAL MODELING OF ELEMENTAL MOBILIZATION IN A HYDROTHERMAL GOLD DEPOSIT
SAMAL, Abani Ranjan, GEOLOGY, Southern Illinois Univ at Carbondale, Mailcode 4324, Carbondale, IL 62901, FIFAREK, Richard H., Geology, Southern Illinois Univ at Carbondale, Mailcode 4324, Carbondale, IL 62901 and MOHANTY, Manoj K., Mining and Mineral Resources Engineering, Southern Illinois Univ at Carbondale, Carbondale, IL 62901-6603, arsamal@siu.edu
Hydrothermal mineral deposits form as a result of the enrichment and depletion of specific elements in host-rocks by geochemical processes. Late stage geochemical processes can redistribute previously introduced hydrothermal elements and cause their enrichment or depletion at different locations, possibly guided by geological features in the deposit. Using geostatistical analysis, the spatial variation of elemental concentrations can be modeled. In geostatistics, the cross-covariance analysis between pairs of elements [
Cxy(O), where
x and
y are a pair of elements sampled in a geochemically homogenous zone
O] allows modeling the spatial dependence between two elements. The cross-covariance can be positive or negative with a change in the direction of analysis. The maximum positive cross-covariance may deviate from the origin (original loci of elements) by a vector, known as the lag vector (
lxy(O)). This lag vector may indicate the direction of elemental mobility from an original position.
In this paper, the lag effect is defined as the maximum average cross-covariance between a pair of variables in each interval of distances of separation (lag). The average cross-covariance values are calculated in sixty-two different regularly spaced directions in three-dimensions. The modeling of cross-covariance between a pair of variables in three-dimensions is applied to assay data for a hydrothermal gold deposit. The results reveal major lag vectors of elemental remobilization that occurred during late stage oxidation. These directions correspond to recognized structural trends and therefore imply fluid control by specific faults or joint sets. A graphic presentation of the lag-vectors is created using GIS to infer these structural trends.
Further geostatistical research may prove useful for predicting suites of elemental enrichment in mineral exploration and perhaps the location of exotic deposits.