Resource Estimation Method Comparison Using Inverse Distance Weighting Nearest Neighbour Point and Ordinary Kriging at Block X

  • Randy Galaxy Insitut Teknologi Nasional Yogyakarta
  • Hendro Purnomo
  • Rizqi Prastowo Institut Teknologi Nasional Yogyakarta
  • Hidayatullah Shidiq Institut Teknologi Nasional Yogyakarta

Abstract

Inverse Distance Weighting, Nearest Neighbor Point, and Ordinary Kriging resource estimation methods have different weighting characters which creates a differental in model and resource calculation. The NNP method is weighted only based on the closest point within certain radius, while the IDW method is weighted based on the estimated point distance to sample points within a certain radius, and the OK method is weighted based on the distance and data around the block. In limonite zone, NNP method obtain 520,750 tons of low Ni class with an average grade of 0.85%, medium grade class 696,750 tons with an average Ni grade of 1.21%, and high grade class 64,500 tons with an average Ni grade of 1.71% and in the saprolite zone, the NNP method obtain 551.016 tons of low Ni class with an average grade of 0.71%, medium class grade 718.359 tons with an average Ni grade of 1.3%, and high class grade 101.484 tons with an average Ni grade of 1.67%, and very high class grade 122.344 tons with an average Ni Grade level of 2.08%. From the results it is evaluated by Root Mean Square Error, in limonite zone the best method based with the smallest error value is the NNP method which gets an error value of 0.0089 and as the saprolite zone the best method is NNP method with an error value of 0.0127. From the modeling and resource calculation there are 3 area’s that require further exploration in the saprolite zone which is the northeast area, southwest and central area’s. As for the limonite zone, exploration continues following the saprolite zone because of the potential for high Ni Grade nickel deposits.

References

[1] Ernowo. Sunuhadi DN. Awaludin M. ESDM.Pusat Sumber Daya Mineral Batubara dan Panas Bumi. 2017.
[2] Golightly JP. Nickeliferous Laterite Deposits. Seventy-Fifth Anniv Vol 1981
[3] Arif I. Nikel Indonesia. PT. Gramedia Pustaka Utama. Jakarta. ISBN : 06-1935-4. 2018:280.
[4] Bardossy A. Introduction To Geostatistic. University of Stuttgart 1997.
[5] Bargawa WS. Geostatistik. Kilau Book. ISBN 978-623-7594-42-0. 2018.
[6] Almasi A, Jalalian A, Toomanian N. Using OK and IDW methods for prediction the spatial variability of a horizon depth and OM in soils of Shahrekord, Iran, Journal of Environment and Earth Science, Vol.4 No.15. 20144.
[7] Isaaks, E.H. and Srivastava RM. An Introduction to Applied Geostatistics. vol. 11. 1989. https://doi.org/10.1177/1748895811401979.
[8] Mousavifazl H. Alizadh A. Ghahraman B. Application of Geostatistical Methods for Determining Nitrate Concentrations in Groundwater (Case Study of Mashhad Plain, Iran). International Journal of Agriculture and Crop Sciences. IJACS/2013/5-4/318-328 2013.
[9] Hekmat A, Osanloo M, Moarefvand P. Block size selection with the objective of minimizing the discrepancy in real and estimated block grade, Saudi Society for Geosciences 2011. https://doi.org/10.1007/s12517-011-0321-8.
[10] Hustrulid W. Kuchta. M. Open pit mine planning & design: Fundamentals vol 1. Balkema 1995. ISBN 0415407370, 9780415407373.
[11] Purnomo H. Comparison the Performance of Ordinary Kriging and Inverse Distance Weighting Methods for Mapping Nickel Laterite Properties. Kurvatek 2019. https://doi.org/10.33579/krvtk.v4i1.1116.
Published
2022-11-11
How to Cite
Galaxy, R., Purnomo, H., Rizqi Prastowo and Hidayatullah Shidiq (2022) “Resource Estimation Method Comparison Using Inverse Distance Weighting Nearest Neighbour Point and Ordinary Kriging at Block X”, ReTII, pp. 70-76. Available at: //journal.itny.ac.id/index.php/ReTII/article/view/3373 (Accessed: 2May2024).