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Total sulfur variability analysis of coal deposits using ordinary kriging estimation
Coal's price collapse has become a challenge in exploring and exploiting coal deposits in the mining industry. Total sulfur is one of the coal qualities sufficiently considered in the use of coal. The Geostatistics method using ordinary kriging estimation is done to determine the total sulfur v...
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creator | Novianti, Yuniar Siska Hakim, Romla Noor Nurhakim Fikri, Hafidz Noor |
description | Coal's price collapse has become a challenge in exploring and exploiting coal deposits in the mining industry. Total sulfur is one of the coal qualities sufficiently considered in the use of coal. The Geostatistics method using ordinary kriging estimation is done to determine the total sulfur variation in the coal seam. Modelling was performed on every three meters of coal thickness using 193 samples on a seam of coal with a thickness of up to 30 meters. Geostatistical modelling is implemented on the coal seam, and it produces ten sulfur distribution models. The modelling results show clearly that in the model in the first layer, the distribution of sulfur is higher in value than other layers. These results expected can help select mining stages and exploration drilling activities in the context of increasing coal reserves. |
doi_str_mv | 10.1063/5.0061118 |
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Total sulfur is one of the coal qualities sufficiently considered in the use of coal. The Geostatistics method using ordinary kriging estimation is done to determine the total sulfur variation in the coal seam. Modelling was performed on every three meters of coal thickness using 193 samples on a seam of coal with a thickness of up to 30 meters. Geostatistical modelling is implemented on the coal seam, and it produces ten sulfur distribution models. The modelling results show clearly that in the model in the first layer, the distribution of sulfur is higher in value than other layers. These results expected can help select mining stages and exploration drilling activities in the context of increasing coal reserves.</description><identifier>ISSN: 0094-243X</identifier><identifier>EISSN: 1551-7616</identifier><identifier>DOI: 10.1063/5.0061118</identifier><identifier>CODEN: APCPCS</identifier><language>eng</language><publisher>Melville: American Institute of Physics</publisher><subject>Coal ; Coal mining ; Exploratory drilling ; Geostatistics ; Mining industry ; Modelling ; Sulfur ; Thickness</subject><ispartof>AIP Conference Proceedings, 2021, Vol.2363 (1)</ispartof><rights>Author(s)</rights><rights>2021 Author(s). 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Total sulfur is one of the coal qualities sufficiently considered in the use of coal. The Geostatistics method using ordinary kriging estimation is done to determine the total sulfur variation in the coal seam. Modelling was performed on every three meters of coal thickness using 193 samples on a seam of coal with a thickness of up to 30 meters. Geostatistical modelling is implemented on the coal seam, and it produces ten sulfur distribution models. The modelling results show clearly that in the model in the first layer, the distribution of sulfur is higher in value than other layers. These results expected can help select mining stages and exploration drilling activities in the context of increasing coal reserves.</description><subject>Coal</subject><subject>Coal mining</subject><subject>Exploratory drilling</subject><subject>Geostatistics</subject><subject>Mining industry</subject><subject>Modelling</subject><subject>Sulfur</subject><subject>Thickness</subject><issn>0094-243X</issn><issn>1551-7616</issn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2021</creationdate><recordtype>conference_proceeding</recordtype><recordid>eNotkEtLxDAUhYMoOI4u_AcBd0LH3KZ5LWXwBQNuKrgLmTQZMtamJq3Qf2_HmdWBw8e9HwehWyArIJw-sBUhHADkGVoAY1AIDvwcLQhRVVFW9PMSXeW8J6RUQsgFqus4mBbnsfVjwr8mBbMNbRgmbDrTTjlkHD22cWYa18cchozHHLodjqkJnUkT_kphdyhcHsK3GULsrtGFN212N6dcoo_np3r9WmzeX97Wj5uiBy5l4ThjglHPwYmGCwlg7VZxVbLK0qZSjSHOMGOZ9MozUYGTW1t6WllVCi8UXaK7490-xZ9x_q_3cUyzd9YlJwBEEAEzdX-ksg3Dv5_u02yaJg1EH1bTTJ9Wo3_Ud19l</recordid><startdate>20211123</startdate><enddate>20211123</enddate><creator>Novianti, Yuniar Siska</creator><creator>Hakim, Romla Noor</creator><creator>Nurhakim</creator><creator>Fikri, Hafidz Noor</creator><general>American Institute of Physics</general><scope>8FD</scope><scope>H8D</scope><scope>L7M</scope></search><sort><creationdate>20211123</creationdate><title>Total sulfur variability analysis of coal deposits using ordinary kriging estimation</title><author>Novianti, Yuniar Siska ; Hakim, Romla Noor ; Nurhakim ; Fikri, Hafidz Noor</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p1688-e655753f61e7d67811ccb969254c3d49da0ea5ac58f9f5741e8bc2f34c927f793</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Coal</topic><topic>Coal mining</topic><topic>Exploratory drilling</topic><topic>Geostatistics</topic><topic>Mining industry</topic><topic>Modelling</topic><topic>Sulfur</topic><topic>Thickness</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Novianti, Yuniar Siska</creatorcontrib><creatorcontrib>Hakim, Romla Noor</creatorcontrib><creatorcontrib>Nurhakim</creatorcontrib><creatorcontrib>Fikri, Hafidz Noor</creatorcontrib><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Novianti, Yuniar Siska</au><au>Hakim, Romla Noor</au><au>Nurhakim</au><au>Fikri, Hafidz Noor</au><au>Cahyadi, Tedy Agung</au><au>Abdullah N, Madi</au><au>Saaid, Ismail Mohd</au><au>Chang, Chih Hua</au><au>Multazam, Mochammad Tanzil</au><au>Rahim, Robbi</au><au>Liqiang, Ma</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Total sulfur variability analysis of coal deposits using ordinary kriging estimation</atitle><btitle>AIP Conference Proceedings</btitle><date>2021-11-23</date><risdate>2021</risdate><volume>2363</volume><issue>1</issue><issn>0094-243X</issn><eissn>1551-7616</eissn><coden>APCPCS</coden><abstract>Coal's price collapse has become a challenge in exploring and exploiting coal deposits in the mining industry. Total sulfur is one of the coal qualities sufficiently considered in the use of coal. The Geostatistics method using ordinary kriging estimation is done to determine the total sulfur variation in the coal seam. Modelling was performed on every three meters of coal thickness using 193 samples on a seam of coal with a thickness of up to 30 meters. Geostatistical modelling is implemented on the coal seam, and it produces ten sulfur distribution models. The modelling results show clearly that in the model in the first layer, the distribution of sulfur is higher in value than other layers. These results expected can help select mining stages and exploration drilling activities in the context of increasing coal reserves.</abstract><cop>Melville</cop><pub>American Institute of Physics</pub><doi>10.1063/5.0061118</doi><tpages>7</tpages><oa>free_for_read</oa></addata></record> |
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source | American Institute of Physics:Jisc Collections:Transitional Journals Agreement 2021-23 (Reading list) |
subjects | Coal Coal mining Exploratory drilling Geostatistics Mining industry Modelling Sulfur Thickness |
title | Total sulfur variability analysis of coal deposits using ordinary kriging estimation |
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