Perpustakaan Digital ITB

Accurate classification of nickel laterite mineral resources is a crucial element in supporting sustainable and efficient mining operations. This classification process is typically conducted by experts who consider various factors, including geological models, sampling density, and drill hole configurations. However, the uncertainties associated with classification decisions are often inadequately accounted for. This study aims to evaluate two geostatistical methods, namely conditional simulation and specific area. Both techniques are applied for classifying nickel laterite mineral resources in Central Halmahera, North Maluku, Indonesia, focusing on both plateau and coastal deposit types. The conditional simulation method is employed to capture spatial variability and uncertainty, while the specific areamethod serves to assess the efficiency of drill hole spacing in resource classification. The data utilized includes geological characteristics, nickel accumulation, and other related variables obtained from two deposit locations: plateau and coastal. Analysis is conducted using the geostatistical software Isatis.neo for variography, estimation, and simulation. This study compares various drilling configurations while considering uncertainties related to nominal production as support. A dataset comprising 953 drill holes in the plateau deposit and 612 drill holes in the coastal deposit, spaced at 50 meters, is used to investigate the performance of these methods. Infill drill holes (grade control data) is added as well with drill hole mesh of 25m and 12.5m for plateau and coastal deposit, respectively. The results indicate that the conditional simulation method provides more accurate estimates at closer drill hole spacings, as indicated by the increase in the probability of the simulation over the estimated, while the specific area method offers a more conservative view of resource classification. For plateau deposits, an optimal drill hole spacing of 25m × 25m is required for measured resource classifications in both limonite and saprolite layers. In contrast, for coastal deposits, a tighter spacing of 12.5m × 12.5m is recommended for measured classifications in the limonite and fine saprolite layers, while 25m × 25m is sufficient for the saprolite layer. Findings demonstrate that both methods can be synergistically employed to classify mineral resources within a two-dimensional context. The specific area method functions as a routine to obtain a good order of magnitude and to determine drill holes that delineate the boundaries between Mineral Resource classifications. Meanwhile, conditional simulation can be utilized to validate these boundaries. This research significantly contributes to the development of more accurate and effective mineral resource classification methods, which has implications for improved decision-making in the mining industry.