DRILL HOLE SPACING ANALYSIS USING GEOSTATISTIC METHODS FOR EVALUATION OF SEAM C COAL RESOURCES IN PIT X BLOCK Y ON KUTAI BASIN, KAUBUN DISTRICT, KUTAI TIMUR REGENCY, EAST KALIMANTAN PROVINCE - 'Arsy Tritura Ebsyar, Hafidz
In Indonesia, Standar Nasional Indonesia (SNI) become the main reference for coal resource classification which is classified based on geological complexity and drilling geometry in the form of the drill hole spacing. However, along with mining exploration developments, it is required to establish further studies related to geological complexity that are linked to the parameters of coal quantity data such as seam thickness and coal quality data such as fixed carbon, inherent moisture, total sulfur, and volatile matter. The distribution of drill hole data was treated with spatial clustering based on the average spacing of existing drill holes, and the condition of land cover that divided into Block 1 which is dominantly covered by vegetation (exploration area) and Block 2 which is an active pit area. To determine the resources distribution of Seam C, Seam C is modeled by two dimensions and three dimensions, the impact of geological complexity is classified into moderate and resource classification based on existing drill hole spacing is classified into measured classification. The Global Estimation Variance (GEV) approach is used to produce the optimum drill hole spacing of Seam C. Estimation using the Global Estimation Variance would produce error values for each space, specifically 100x100 m, 250x250 m, 500x500 m, 750x750 m, 1000x1000 m, 1500x1500 m, 2000x2000 m, 2500x2500 m, and 3000x3000 m. Then the results of the drill hole spacing analysis will be linked to a relative error classification to match every error with classification of 0-10% for measured resources, 10-20% for indicated resources, and 20-50% for inferred resources. The results of this study for Seam C in the Menumbar Formation for optimum drill hole spacing for the block 1 classification of measured resources is 200 m, the indicated is 400 m, and the inferred is 950 m. Then for block 2 the classification of measured resources is 250 m, the indicated is 450 m, and the inferred is 1150 m.