Risk reduction in Sechahun iron ore deposit by geological boundary modification using multiple indicator Kriging

作     者：S.Kasmaee F.M.Torab 

作者机构：Department of Mining and Metallurgical EngineeringIranian Iron Ore Research Center(IORC)Yazd University Department of Mining and Metallurgical EngineeringYazd University 

出 版 物：《Journal of Central South University》 (中南大学学报（英文版）)

年 卷 期：2014年第21卷第5期

页      面：2011-2017页

核心收录：

学科分类：0810[工学-信息与通信工程] 081801[工学-矿产普查与勘探] 081803[工学-地质工程] 0806[工学-冶金工程] 08[工学] 0818[工学-地质资源与地质工程] 0805[工学-材料科学与工程（可授工学、理学学位）] 0703[理学-化学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by Iron Ore Research Center of Yazd University 

主　　题：geological boundaries multiple indicator kriging risk assessment block model uncertainty Sechahun deposit 

摘      要：Uncertainty on the geological contacts and the block volumes of the models along boundaries is often a major part of the global uncertainty of reserve *** work introduces a geostatistical technique that has been developed and tested in an iron ore deposit at Bafq mining district,in central Iran,and that,based on a probability criterion,helps to objectively model the geometry of this iron ore *** main problem in reserve estimation of this ore body is its geometrical modeling and uncertainty in geological *** work deals with the geostatistical method of multiple indicator kriging,which is used to determine the real boundaries of ore body in different *** approach has potential to improve project performance and decrease operational *** this purpose,the ore body is separated into two categories including rich iron zone(w(Fe)45%)and poor iron zone(20%w(Fe)45%).It significantly benefits to decrease the risk of reserve evaluation in the *** case study also highlights the value of multiple indicator kriging as a tool for estimates the position of grade boundaries within the *** of the resultant probability maps with the real ore/waste contacts on the extracted levels shows that the first indicator model could separate the whole ore body(poor plus rich)from the waste zone by probability of more than 0.35,which concludes the total reserve of 53 million *** second indicator model applied to separate the rich and poor domains and the results show that the blocks with the estimated probability of equal to or more than 0.4 lay within the rich ore zone consisting of 15.8 million tons reserve.