1. Surficial uranium targeting model and prospectivity mapping of the Yeelirrie Area, Western Australia Abstract: An exploration targeting model for calcrete-hosted surficial uranium deposits in the palaeochannels of Western Australia is presented. The model is used to develop a knowledge-driven Mamdani-type fuzzy inference system for prospectivity modelling of calcrete-hosted surificial uranium deposits the Yeelirrie area. The inputs to the model are. spatial proxies that serve as expressions of mineralization processes in the publicly available exploration datasets. In the output prospectivity map, the SE-NW trending Yeelirrie and E-W trending Hinkler's Well palaeochannels show high prospectivity. The known surifical deposits fall in high prospectivity areas, although the minor showings and anomalies in the southern part of the study area fall in low prospectivity areas. A comparison with the available radiometric images shows that several channels showing high surface U concentrations in the NW and NE quadrants may not be prospective. Objectives Develop exploration targeting model of calcrete-hosted surficial uranium deposits in palaeochannels of Western Australia;, Generate prospectivity model of calcrete-hosted surficial uranium deposits in the palaeochannels around Yeelirrie, Western Australia, Methodology U-Sources Genetic and Targeting Model Targetting CriteriaPossible Predictor maps or spatial proxiesPredictor Maps Generated- Used-Not Used Rationale 1.U-Content - Considerably high in continental crustal rocks. - As catchment area of a palaeochannel increases, fluids collect more U from larger areas. Proximity to continental crustal rocks Radiometric data indicating U enrichment Geochemical data on U enrichment in ground waters Size of catchment area of palaeochannel Give Map of Underlined 2. Source rock Geochemistry - Type of rock affecting its suitability as a leachable source of U Proximity to -peraluminous granites, -peralkaline felsic volcanic rocks, -pre-existing U mineralization, Mineralogy: minerals with high U contents and also susceptible to weathering: biotite, monazite, zircon, apatite, allanite; biotite favourable as a leachable source for U Data not available 3. Source rock structure - To determine the degree of weathering that facilitates extraction of U from sources by the circulating fluids. Structural data: density of fractures, faults, joints Calculation of weathering indices from geochemical data Calculation of Fluid-rock ratio Mapping geomorphology: granitic topographic highs more susceptible to weathering Meteorological data for temperature fluctuation (weathering due to temperature fluctuation ) 4. U enrichment in ground water - Near-surface oxidizing environment for leaching U Hydrological data to calculate the Eh-pH of fluids for leaching U; Oxidation state of fluids and pH of waters (acidic or alkaline waters) Data not available Constituent Processes Targeting CriteraPossible Predictor Maps/Spatial Proxies V Sources 1. Presence of mafic-ultramafic rocks 2. Redox environment: Extraction of V from source rocks by acidic fluids occurs in reducing fluid Eh. If the same fluid contains uranyl complexes, then strong reducing Eh can cause destabilization of uranyl complexes. Hence such fluids should be mildly reducing. Proximity to greenstone belts, mafic-ultramafic rocks, BIFs Eh-pH of fluids Mapping the depth of water table K SourcesContinental crustal rocks Proximity to Continental crustal rocks; Ground water geochemistry gives dissolved K + ion content Energy for driving fluids Hydraulic gradient for subsurface fluid circulation from source to trap Mapping topography and slopes of palaeovalley floors (using DEM or thermal infrared data); Palaeochannel mapping- Flow directions from slope calculations and palaeochannel intersections; Caution: Topographic gradients may not be exact proxies for hydraulic gradients 1 Conceptual Model & Knowledge Filtering & Analysis Mineral systems Models Mineral systems Models Data Compilation & Preparation Literature Review Literature Review Spatial Analysis Predictor Maps Neural Networks (NN) Neural Networks (NN) Fuzzy Inference Systems (FIS) Weights of Evidence (WofE) Prospectivity Modelling