Open AccessModeling and Resource Classification Lateritic Nickel Deposits on a Heterogeneous Block in The Haul-Sagu Area using Estimation and Simulation Geostatistical Method
Author(s) -
W A K Conoras,
A A Lamburu
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1569/4/042079
Subject(s) - tonnage , kriging , laterite , estimation , resource (disambiguation) , geostatistics , soil science , deposition (geology) , environmental science , statistics , geology , mathematics , nickel , structural basin , spatial variability , metallurgy , computer science , engineering , materials science , geomorphology , computer network , systems engineering , oceanography
Deposits modeling is a very important thing in the exploration field, especially in estimating reserves. This research was conducted to model the geometry of lateritic nickel ore deposition on heterogeneous blocks using the geostatistical estimation method Ordinary kriging (OK) and simulation methods namely, Sequential Gaussian Simulation (SGS) then the distribution of laterite zonation was carried out to calculate the resource and mineral resource classification based on estimation data and simulation. The estimation results using the OK method have an average value of Ni higher than the average Ni grade from the SGS simulation results. Analysis of the calculation of total tonnage of resources from the estimated OK data shows the total amount of measured tonnage of 5,875 tons is far lower than the amount of resource tonnage from the SGS simulation data which displays the total amount of tonnage measured 189,766 tons. However the average grade of Ni from measured OK Resources is 1.49% higher, compared to the average Ni grades from measured resources of SGS 1.33%. with a difference of 0.16% Ni grades. The opposite occurs when the average Fe grade of the measured OK resource is lower 24.15% compared to the average Fe grade of the Measured resource of SGS 32.81% with a very large difference in Fe grade of 8.66%.