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Correlating spatial model of coal quality with coal microstructures detected from X-ray CT image analysis
Heriawan M.N.a,b, Koike K.a
a School of Science and Technology, Kumamoto University, Japan
b Research Group of Earth Resources Exploration, Faculty of Mining and Petroleum Engineering, Institut Teknologi Bandung (ITB), Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]This study presents an application of the industrial X-ray CT scanner to correlation of coal quality with microstructures by scanning several bulk and core coal samples from a multilayer coal deposit in East Kalimantan, Indonesia. Most of samples were taken from three main seams termed Seams T, R, and Q from the upper to the lower sequence. Each seam is classified into three sub-units: Top, middle, and bottom because the quality of top and bottom sub-units is different from the middle sub-units. In general, the top and bottom sub-units have the ash content and total sulphur higher than the middle sub-units. Following this circumstance, coals were sampled from these sub-units for each seam and also oriented in the field. Coal microstructures were detected by image analysis of CT-values that are related to the bulk density of material. Coal microstructures were focused on the components in the coal samples with unusual CT-values. The normal coal components (macerals) had the CT-values ranging from 100 to 300. Based on this general trend, the components that had the CT-values extremely larger or smaller than that range were classified into impurity materials. Some natural microfractures detected on the CT-images were also infilled by impurity materials in some parts. In addition to the CT-image analysis, we produced a spatial model of coal quality using the borehole sample data and geostatistics. The impurity materials in coals detected from the CT-image were used to interpret this quality distribution. As the result, the low quality of coal is spatially correlated to the presence of artificial microfractures and larger amount of impurity materials infilled in the natural microfractures.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Borehole sample datum,Geo-statistics,Impurity material,Microfractures,Quality distribution,Spatial modeling,X ray CT images,X-ray CT scanner[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]