Abstract
This study aims to identify proper parts of B2coking coal seam in the North block of East-Parvadeh coal deposit (Central Iran) using the C-N fractal models based on sulfur and ash values. Based on the C-N log-log plots, there are five different geochemical populations for both sulfur and ash data. First for sulfur has ranged from 0-1.58%namely very sulfur population which has best quality for coking coal and this has situated in the northern and western parts of the area. However, first and second populations for ash with ash values between 0 and 30% namely very ash population and low ash population have suitable quality for coking coal in B2 seam which have situated mostly in the western part of the North Block. Moreover, proper parts of the B2coking coal seam are situated in the northern and western parts of the North Block.
Highlights
Recognition of coking coal parts in the bituminous coal seams is necessary for mine planning and equipment selection of these zones
The Tabas coalfield provides a high percent of Irans coking coal for metallurgical applications, because its reserve is estimated to be 3-4 Gt [2,3].Spatial distribution of geochemical data is significant for separation of geochemical populations but it is not taken into consideration for conventional statistical methods
Other fractal models were developed and applied in geochemical exploration such as power spectrum-area (S-A) by Cheng et al[18], concentration-distance (C–D) by Li et al[12], concentration-volume (C-V) by Afzal et al[15]and concentration-number (C–N) by Hassanpour and Afzal[19].In this paper, C-N fractal model was applied for separation of ash and sulfur populations based on drillcore data from the B2 seam of the North block of East-Parvadeh coal deposit, Central Iran,for identification of proper parts of coking coal
Summary
Recognition of coking coal parts in the bituminous coal seams is necessary for mine planning and equipment selection of these zones. The Tabas coalfield provides a high percent of Irans coking coal for metallurgical applications, because its reserve is estimated to be 3-4 Gt [2,3].Spatial distribution of geochemical data is significant for separation of geochemical populations but it is not taken into consideration for conventional statistical methods. These methods are based on quantities such as mean, median and standard deviation cannot identify difference between geochemical populations, e.g. ore zones or anomalies,in many cases. Other fractal models were developed and applied in geochemical exploration such as power spectrum-area (S-A) by Cheng et al[18], concentration-distance (C–D) by Li et al[12], concentration-volume (C-V) by Afzal et al[15]and concentration-number (C–N) by Hassanpour and Afzal[19].In this paper, C-N fractal model was applied for separation of ash and sulfur populations based on drillcore data from the B2 seam of the North block of East-Parvadeh coal deposit, Central Iran,for identification of proper parts of coking coal
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