Mineral resources estimation based on block modeling

Bargawa, Waterman Sulistyana; Amri, Nur Ali

doi:10.1063/1.4940249

Cited by 7 publications

(4 citation statements)

References 5 publications

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“…: distance; k : power Ordinary kriging system solve OK weight (wi) using the equation system as follows [25]: The determination of the accuracy of the estimation technique is based on linear regression between the estimated grade and the composite grade, the comparison of the trend of the block model and grade on the drilling data, and the probability plot. The classification of mineral resources is carried out using the best estimation technique [26].…”

Section: Methodsmentioning

confidence: 99%

The Performance of Estimation Techniques for Nickel Laterite Resource Modeling

Bargawa

2022

Jurnal Teknologi

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The choice of estimation technique according to geological conditions and mineralization character is the main problem in estimating block grade of nickel laterite. CV (coefficient of variance) and variogram determine the choice of estimation technique for nickel laterite resource classification. This study aims to evaluate various techniques for estimating block grades and to select the appropriate method for the classification of nickel laterite resources. The basic statistical analysis is to find out the description of the data, while the variography is to find out the spatial correlation between the data. Nickel grade estimation results are based on Near Neighbor Polygon (NNP), Inverse Distance Weighting (IDW), and Ordinary Kriging (OK) techniques to determine the classification of nickel resources. Accuracy levels are based on cross-sectional visualization comparisons, plan views, probability plots and linear regression analysis. The OK technique were not superior in grade estimation, especially in nickel laterite deposits. The results showed that the IDW technique was suitable to be applied to the limonite zone, while the NNP technique was suitable to be applied to the saprolite zone. Based on the performance of the estimation technique, the weighted average method can be applied for the classification of inferred, indicated, and measurable resources. The grade-tonnage curve shows the nickel laterite resource potential in the study area.

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Section: Methodsmentioning

confidence: 99%

The Performance of Estimation Techniques for Nickel Laterite Resource Modeling

Bargawa

2022

Jurnal Teknologi

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“…Based on the DHSA graph and relative error values, the distance or area of influence for measured, indicated, and inferred resources can be evaluated. Geostatistical approach is generally used for estimation of ore mineral grade [16][17][18]. Another result of kriging is the use of kriging relative error of the ordinary kriging estimation method for classification of coal resources [19].…”

Section: Methodsmentioning

confidence: 99%

Classification of Coal Resources Using Drill Hole Spacing Analysis (DHSA)

Zulkarnain¹,

Bargawa²

2018

JGRE

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The classification of coal resources generally is based on geometric factors and the complexity of geological structures. The classification has not considered coal quality factors such as ash content, sulphur content, caloric value. The development of international classification standards has required a geostatistical analysis for the estimation and classification of coal resources. The purpose of this research is to apply geostatistics method to determine optimal drill hole distance, and to analyze classification of coal resource based on data of coal quality and quantity. Based on global estimation variance (GEV) approach from geostatistics, relative error value was obtained. Drill hole spacing analysis (DHSA) results in optimal drill hole spacing on each coal seam for the coal resources classification. Estimation using kriging block results in the value of kriging relative error. Coal resources classification was based on relative error of 0-10% for measured resources, 10-20% for indicated resources and > 20% for inferred resources. Based on a case study in a coal field consisting of three coal seams, the geostatistical approach produced the smallest distance on seam-3 as the optimal borehole range in the research area. This classification yields a greater area of influence than the SNI standard on simple geological complexity.

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“…Penentuan pola penyebaran serta ketebalan nikel laterit sangat penting pada saat perhitungan sumber daya dan cadangan mudah untuk diketahui secara detail (Yurnia et al, 2018). Selain itu, pola penyebaran dan ketebalan akan menjadi dasar yang kuat dalam menentukan modeling cadangan nikel laterit (Bargawa & Amri, 2016;Bargawa et al, 2020) dan proses perencanaan tambang yang akan dikerjakan (Coronas & Tabaika, 2019).…”

Section: Pendahuluanunclassified

Hubungan Pola Penyebaran dan Ketebalan Zona Bijih Endapan Nikel Laterit dengan Topografi Permukaan Pada PT Aneka Tambang Tbk

Fadli

2021

Idn. J. Earth Sci.

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Abstrak: Indonesia merupakan negara yang memiliki sumber daya nikel laterit yang berlimpah, mulai dari Sulawesi hingga ke Papua. Oleh karena itu, peneliti melakukan analisis pola sebaran dan ketebalan endapan nikel leterit untuk mendapatkan pola sebaran zona bijih dari endapan nikel laterit berdasarkan topografi permukaan. Adapun metode yang dilakukan adalah menganalisis sampel pemboran dengan X-ray spectometer, menganalisis topografi, morfologi dan membuat profil penampang antar sumbu bor untuk menganalisis pola sebaran zona bijih endapan nikel laterit. Data yang dihasilkan dari penelitian ini adalah bentuk topografi perbukitan dengan morfologi bergelombang, miring hingga melandai, dengan kemiringan lereng 20-160. Penampang endapan secara vertikal mengunakan parameter overburden dengan kadar Ni < 0.90% – > 4%. Penampang serta pola sebaran endapan nikel laterit terbagi 3 warna yaitu coklat untuk kadar Ni < 0.90%, kuning untuk kadar Ni 0,91% – 1,50%, dan hijau untuk kadar Ni > 1,51%. Berdasarkan penampang korelasi pada topografi landai, didapatkan kadar yang tinggi serta tebal dan topografi yang berbukit miring ditemukan kadar yang tinggi tetapi ketebalan yang tipis. Secara keseluruhan kadar nikel laterit berkisar 8 – 16 meter. Kata Kunci: Topografi, Nikel Laterit, Kadar, Ketebalan, Pola Penyebaran Abstract: Indonesia is a country that has abundant nickel laterite resources, from Sulawesi to Papua. Therefore, the researchers analyzed the distribution pattern and thickness of the nickel leterite deposits to obtain the distribution pattern of the ore zones of the laterite nickel deposits based on the surface topography. The method used is to analyze the drilling sample with an X-ray spectometer, analyze the topography, morphology and create a cross-sectional profile between the drill axes to analyze the distribution pattern of the laterite nickel ore deposit zone. The data generated from this study is a hilly topography with a wavy morphology, slanted, and sloping, with a slope of 20-160. The vertical cross section of the sediment uses overburden parameters with Ni content < 0.90% – > 4%. The cross-section and distribution pattern of laterite nickel deposits are divided into 3 colors, namely brown for Ni content < 0.90%, yellow for Ni content 0.91% – 1.50%, and green for Ni content > 1.51%. Based on the cross-sectional correlation on the sloping topography, it was found that high grades and thick and hilly topography found high grades but thin thicknesses. Overall, laterite nickel content ranges from 8 to 16 meters. Keywords: Topography, Nickel Laterite, Grade, Thickness, Distribution Pattern

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Mineral resources estimation based on block modeling

Cited by 7 publications

References 5 publications

The Performance of Estimation Techniques for Nickel Laterite Resource Modeling

The Performance of Estimation Techniques for Nickel Laterite Resource Modeling

Classification of Coal Resources Using Drill Hole Spacing Analysis (DHSA)

Hubungan Pola Penyebaran dan Ketebalan Zona Bijih Endapan Nikel Laterit dengan Topografi Permukaan Pada PT Aneka Tambang Tbk

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