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SAMPLE COMPOSITE MECHANISM TO REDUCE THE ERRATIC GRADE DISTRIBUTION IN RESOURCE ESTIMATION OF AU-AG EPITHERMAL, CIURUG VEIN, BLOCK 3 SOUTH, LEVEL 500 AND 600, PONGKOR MINE

Oleh   E. P. Zen [-]
Kontributor / Dosen Pembimbing : Syafrizal, K. Anggayana
Jenis Koleksi : Prosiding
Penerbit : FTTM - Teknik Pertambangan
Fakultas : Fakultas Teknik Pertambangan dan Perminyakan (FTTM)
Subjek :
Kata Kunci : resource estimation, composite, IDS, NNP, kriging, Pongkor
Sumber :
Staf Input/Edit : Resti Andriani  
File : 2 file
Tanggal Input : 2021-11-18 11:05:59

An outstanding characteristic exists in many Au - Ag deposit especially in vein system deposits is the erratic grade distribution. During bulk volume and grade estimation, the erratic effect has to be reduced as minimum in order to gain the higher spatial continuity especially for grade parameter. It is assumed that the erratic effect could be reduced by applying more robust geometry suppori. In the study, the geometry support is represemed by interval of sample composite. The data set used is channel sampling obtained in the deyelopmem stage in Ciurug vein, block 3 south, level 506 and 600. In the evaluation of Au — Ag grade spatial distribution, composite interval of Lim. 2.5 m, and S m would be applied as block uni: dimension of cube shape in deposit modeling and reserve estimation. Reserve estimation with different block size would be conducted with inverse distance sguare (IDS), nearest neighbor point (NNP), and kriging method. The results show the sample composite mechanism has limit of size to reduce the erratic effect. The size limit could be analyzed by several parameters of descriptive statistics: standard deviation. standard error, and confidence level. The combinations in Au — Ag reserve estimation between block size and the third methods reveal thc. different trends. Based on cross validation results, IDS and NNP yield underestimated and overestimated calculation respectively, while kriging method generates moderate calculation. Furthermore, the estimation with block size of 2.5 —m and kriging method is considered as the best estimation based .on descriptive statistic, correlation and regression, and covarians analysis on cross validation.