Geostatistical Ore Body Modeling on Uranium Mineralization in Remaja Sector, Kalan Area, West Kalimantan

Roni Cahya Ciputra (Faculty of Mining and Petroleum Engineering, Bandung Institute of Technology (ITB) Ganesha St., No. 10, Bandung 40132, Indonesia Research Center for Nuclear Fuel Cycle and Radioactive Waste Technology, Research Organization for Nuclear Energy (ORTN),)
Mohamad Nur Heriawan (Faculty of Mining and Petroleum Engineering, Bandung Institute of Technology (ITB) Ganesha St., No. 10, Bandung 40132, Indonesia)
Heri Syaeful (Research Center for Nuclear Fuel Cycle and Radioactive Waste Technology, Research Organization for Nuclear Energy (ORTN), National Research and Innovation Agency (BRIN) PUSPIPTEK Area, Building 20, South Tangerang 15314, Indonesia)
Dhatu Kamajati (Bureau for Public Communication, General Affairs, and Secretariat, National Research and Innovation Agency (BRIN) B.J. Habibie Building, M.H. Thamrin St., No. 8, Central Jakarta 10340, Indonesia)
Putri Rahmawati (Bureau for Public Communication, General Affairs, and Secretariat, National Research and Innovation Agency (BRIN) B.J. Habibie Building, M.H. Thamrin St., No. 8, Central Jakarta 10340, Indonesia)

Eksplorium : Buletin Pusat Pengembangan Bahan Galian Nuklir
Vol 43, No 1 (2022): Mei 2022

Manual ore body modeling on Remaja Sector, Kalan, West Kalimantan generally takes a long time and is subjective. On the other hand, automatic modeling (implicit modeling) is faster, objective, and equipped with uncertainty factors. This study aimed to analyze the comparison between the geostatistical Sequential Indicator Simulation (SIS) ore body model to the manual ore body model. The lithology database was used as input for variogram analysis and SIS simulation. The directional variogram was used to construct an experimental variogram for the lithology with orientation data. The orientation of the lithologies corresponds to the anisotropy of their variogram map. The SIS was carried out in  Block A and Block B with block sizes of 6×6×6 m3 and 5×5×5 m3 respectively. The simulation results were processed to produce a lithology probability model. By using maximum probability as block lithology, simulation results were well validated by the composite database histogram, the lithologies along the tunnel on the geological map of level 450 masl of Eko Remaja Tunnel., and the lithologies along boreholes. The weakness of the geostatistical ore body model was the results depending on the input parameters. Meanwhile, several advantages of the geostatistical ore body model were a faster processing process, equipped with an uncertainty factor, and the block size of the model has taken into account the distance between grade data so that it can be used directly for grade estimation. Quantitatively, the geostatistical ore body model had a higher average percentage of conformity to the lithology of the mineralized zone along the borehole than the manual ore body model.