Research On Three-Dimensional Geo-Modelling And Resource Reserve Calculation Of Timulike Iron Orebody In Fuyun County,Xinjiang Province

Iron is one of the main raw materials used in industries for the manufacture of a wide range of essential products.knowing the three-dimensional geological model of iron deposits,the distribution of iron grade within the deposits and the estimation of its resource reserves are some of the essential conditions for its extraction in order to supply industries which depend on it.One of the challenges for estimation of these deposits concern choosing the most suitable method for each particular deposit.By establishing a three-dimensional iron resource estimation model of the Timulike mine,this thesis explores the accurate resource estimation method and compares the estimation accuracy of several models to find the best resources estimation method of the Timulike iron deposit.To reach the objectives of this thesis,based on the processing and analysis of the iron orebody prospecting data by the methods of histograms and experimental variogram,the section-line method and the triangulation techniques of Surpac software are applied to establish the orebody model in three dimensions.Ordinary Kriging(abbreviated OKI)and Inverse Distance Weighting(abbreviated IDW)methods are applied to estimate iron resource reserves.The estimation accuracy of the models resulting from these methods is then determined by cross-validation with statistical comparison and linear regression methods.The results show that the spatial variability of the iron grade is high and this grade is very unevenly distributed although there is no bimodal distribution.The modelling method applied has been effective and suitable for the type of deposit.The 3D model of the ore body generated is thin and stretched along its length,and the continuity of mineralization is anisotropic with an anisotropy coefficient of 1.672 for the major/semimajor axis and 2.045 for the major/minor axis.For an industrial cut-off grade of 25%,the total reserve estimated by ordinary kriging amounts to 14.858 million tons with a mean iron grade of 34.225% iron ore,while 17.119 million tons with a mean iron grade of 34.919% were estimated by inverse distance weighting.At a cut-off of 20%,22.59 million tons of iron reserves with a mean iron grade of 30.246% are calculated by ordinary kriging while inverse distance weighting provides 23.936 million tons with a mean iron grade of 31.416 %.In each particular cut-off interval,the ordinary kriging estimation generally offered lower tonnage and iron mean grade than the inverse distance weighted estimate.At an iron grade of 60% or higher,the resource reserve calculated by the ordinary kriging method is zero,in contrast to the inverse distance weighting which calculated about 70604 tons of reserves that have iron grades of at least 60%.In addition,the estimation model by inverse distance weighting explains 91.7293%of iron grades variability with a correlation coefficient equal to 0.957754 which is more precise than the estimation model by ordinary kriging with 88.4632% of iron grades variability in samples and a correlation coefficient equal to 0.940549.Overall,even if the statistical results of the ordinary kriging model are sometimes closer to the iron grades of the composite,the inverse distance weighting model at the end of this study was more efficient and robust,although on the other hand it slightly overestimates the calculated resource reserves.