Uranium Deposit Model Using MPS by Soft Conditioning Probability Derived from Lithology Information of Drillhole

Summary This paper presents uranium deposit model using multiple point statistics simulation by soft data derived from prior knowledge based on drillhole. In this study, single normal equation simulation was applied to conduct uranium deposit modeling. The workflow of proposed methodology is divided into four stage; (1) simulation gird generation, (2) training image generation, (3) vertical proportion calculation and (4) uranium probability grid calculation. This probability was calculated from the lithology information of drillhole. The uranium probability was kriged into the simulation gird, and the kriged uranium probability were used as soft conditioning. Lastly, uncertainty analysis using Shannon entropy was conducted for the generated realizations. As a results, uranium deposit model using multiple point statistics was successfully applied, and the realizations by proposed methodology show that the uncertainty with the distance from the borehole is effectively reduced. The proposed methodology is expected to be used as a reference model for drilling plans by providing uncertainty information on the shape of uranium deposits.