Comparison between ordinary kriging (OK) and inverse distance weighted (IDW) based on estimation error. Case study: Dardevey iron ore deposit, NE Iran

2013 ◽  
Vol 7 (9) ◽  
pp. 3693-3704 ◽  
Author(s):  
Shahab Shahbeik ◽  
Peyman Afzal ◽  
Parviz Moarefvand ◽  
Mania Qumarsy
Keyword(s):  
Ordinary Kriging ◽  
Iron Ore ◽  
Estimation Error ◽  
Ore Deposit ◽  
Inverse Distance Weighted ◽  
Distance Weighted ◽  
Iron Ore Deposit ◽  
Inverse Distance ◽  
Ne Iran

Assessing grade domain of iron ore deposit using geostatistical modelling: A case study

2014 ◽  
Vol 83 (5) ◽  
pp. 549-554 ◽  
Author(s):  
V. Kameshwara Rao ◽  
C. R. Rao ◽  
A. C. Narayana
Keyword(s):  
Iron Ore ◽  
Ore Deposit ◽  
Geostatistical Modelling ◽  
Iron Ore Deposit

scholarly journals Ore resource modelling of Ajabanoko iron ore deposit, Ajabanoko, Nigeria

2020 ◽  
Vol 9 (1) ◽  
pp. 128
Author(s):  
Adebimpe Rasheed Adeshina ◽  
Akande Jide Muili
Keyword(s):  
Iron Ore ◽  
Mining Operation ◽  
Drill Hole ◽  
Mineral Deposits ◽  
Distance Method ◽  
Ore Deposit ◽  
Ore Body ◽  
Iron Ore Deposit ◽  
Resource Modelling ◽  
Inverse Distance

Ore resource modelling is an essential aspect of mining operation. It is also a crucial pre-mining step required for a successful exploitation of mineral deposits. Ajabanoko iron ore resource model was developed and the ore reserve estimate carried out using inverse distance method as contained in Surpac 6.4.1 mine software. The total number of blocks used for the model is 54,475. Ore estimation result obtained from thirteen drill hole data indicates 38,313,595 tonnes of iron ore and density of 3.65 tonnes/m3. The average grade and total volume of the ore body is 36.36 % and 10,496,595 m3 respectively.  

Geometallurgical Domaining by Cluster Analysis: Iron Ore Deposit Case Study

2018 ◽  
Vol 28 (3) ◽  
pp. 665-684 ◽  
Author(s):  
Babak Rajabinasab ◽  
Omid Asghari
Keyword(s):  
Cluster Analysis ◽  
Iron Ore ◽  
Ore Deposit ◽  
Iron Ore Deposit

scholarly journals The use of ordinary kriging and inverse distance weighted interpolation to assess the odour impact of a poultry farming

2020 ◽  
Vol 29 (1) ◽  
pp. 17-26
Author(s):  
Izabela Sówka ◽  
Agnieszka Grzelka ◽  
Marcin Pawnuk ◽  
Anna Pielichowska
Keyword(s):  
Spatial Data ◽  
Ordinary Kriging ◽  
Animal Husbandry ◽  
Weighted Interpolation ◽  
Inverse Distance Weighted ◽  
Interpolation Methods ◽  
Distance Weighted ◽  
Inverse Distance Weighted Interpolation ◽  
Inverse Distance

The aim of the study was to determine the usefulness of spatial data interpolation methods in analyses of the odour impact of animal husbandry facilities. The interpolation methods of data obtained from measurements using the field olfactometry technique were the ordinary kriging method (OK) and the inverse distance weighted method (IDW). The quality of the analyses that have been obtained indicates the potentially better use of the OK method in the presentation of spatial odour concentration distributions.

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