Uncertainty Analysis of Thermodynamic Variables of Fluid Inclusions: A Deposit-Scale Spatial Exploratory Data Modeling through Fuzzy Kriging

Abstract

Studies of data obtained from fluid inclusions have focused on two fields, namely: (1) improvement of analytical and experimental study methods; and (2) modeling of data from fluid inclusions to provide information that support mineral exploration. One thing that makes modeling of fluid inclusion data disadvantageous is the failure to record an accurate value per sample; in other words, uncertainty associated with a measured value is ignored. Because existing methods of estimating values in unvisited locations are unable to model data tainted with uncertainty, it was trialed here to use a fuzzy kriging approach to estimate thermodynamic variables derived from fluid inclusions in certain un-sampled parts of a porphyry-Cu deposit. Based on the estimated values and using a fuzzy decision table tool, a predictive fuzzy model of spatial distribution of Cu concentration was derived for the study area. This predictive model was validated in the samples taken from boreholes that are not used for collecting fluid inclusions data. This validation showed that the predictive model is reliable. Finally, the model was used to design an additional drilling pattern in areas with lower density of exploratory drilling.