Indirect modeling of spatial distribution of gold grade using the integration of IP-RS data and associated sulfide paragenes in the range of Yangani and Qinrjeh (zarshuran)

Document Type : research - paper

Authors

1 Master's degree in Tehran University-Tehran

2 Faculty Member of University of Tehran

3 faculty of member of university of Tehran

4 North Amir-Abad University College of Engineering

Abstract

The study area is the Yeganlly and Qinranjeh area, southwest of Zarshuran gold mine, 35 km away from Takab city, West Azarbaijan province. The study area is located on the southwest edge of the mine. Only 17 borehole data were available for this study and were evaluated. Geophysical data includes 17 parallel profiles with a length of about 735 meters with a 30 meter distance electrode and a polar-bipolar mapping array according to the topography of the area. The objective of introducing and presenting a method for simulation and single-multivariate estimation using the most widely used methods, such as usual cracking, ordinary cokriging, sequential simulation, sequential coexistence simulation, in order to reproduce more precisely the initial region variables and Secondary will be. Geophysical data was constructed of a so-called sulfide factor. After normalizing, for each variable, the variography chart was drawn and estimated using the Kriging method according to the variogram in the borehole coordinates. Then, by normalizing the data in the specimen, analysis of the main components on the variables was performed using SPSS software. The output of this part was two factors that the fact that the amount of gold mineralization was high was introduced as a mineralization factor. Now, with two existing factors, namely, the sulfide factor (geophysical factor) and the gold mineralization factor in the studied area, the combined interactions between the built-in block models were combined with the estimation and simulation; ultimately, validation was also performed by evaluating and estimating two boreholes Isolated randomly using other specimens at the end. It was found that according to the evaluated results, when estimating the gold grade when using sulfide factors and mineralization in coking, the gold monorangle estimation by conventional Kriging estimation is closer to the real values of gold.

Keywords


منابع [1] Journel, A.G., 1974, “Geostatistics for conditional simulation of ore bodies”. Economic Geology 69(5), 673-687.## [2] Lantuéjoul, C., 2013, “Geostatistical simulation: models and algorithms”. Springer Science & Business Media.## [3] Rahimi, H., Asghari, O., Hajizadeh, F., 2018, “Selection of optimal thresholds for estimation and simulation based on indicator values of highly skewed distributions of ore data”. Natural Resources Research, 27(4), 437-453.## [4] Chiles, J. P., Delfiner, P., 2012, “Geostatistics: Modeling spatial uncertainty”. New Jersey: Wiley.## [5] Armstrong, M., 1998, “Basic linear geostatistics”. Berlin: Springer.## [6] Safikhani, M., Asghari, O., Emery, X., 2017, “Assessing the accuracy of sequential gaussian simulation through statistical testing”. Stochastic environmental research and risk assessment 31(2), 523-533.## [7] Talesh Hosseini, S., Asghari, O., Ghavami Riabi, S. R., 2018, “Spatial modelling of zonality elements based on compositional nature of geochemical data using geostatistical approach: a case study of Baghqloom area, Iran”. Journal of Mining and Environment 9(1), 153-167.## [8] طالش حسینی، سجاد؛ مرادزاده، علی؛ اصغری، امید؛ 1398؛ " کاربرد شبکه برنامه‌ریزی GERT در ساختار مدیریت پروژه-های شبیه‌سازی زمین آماری در کانسار مس – طلا دالی شمالی استان مرکزی"، نشریه علمی پژوهشی مهندسی معدن، دوره 14، شماره 42، صفحه 32 تا 46. ## [9] Mehrabi, B., Yardley, B.W.D., Komninue, A., 2003, “Modelling the As-Au association in hydrothermal gold mineralization: Example of Zarshuran deposit, NW Iran”.## [10] Ghane, B., Asghari, O., 2017, “Modeling of mineralization using minimum/maximum autocorrelation factor: case study Sury Gunay gold deposit NW of Iran”. Geochemistry: Exploration, Environment, Analysis, 17(3), 186-193.## [11] Wackernagel, H., 2013, “Multivariate geostatistics: an introduction with applications”. Springer Science & Business Media.## [12] Rezaee, H., Marcotte, D., 2017, “Integration of multiple soft data sets in MPS thru multinomial logistic regression: a case study of gas hydrates”. Stochastic Environmental Research and Risk Assessment, 31(7), 1727-1745. ## [13] Lee, S. J., 2005. “Models of soft data in geostatistics and their application in environmental and health mapping”. PhD thesis, University of North Carolina at Chapel Hill.## [14] Xu, W., Tran, T.T., Srivastava R.M., 1992, “Integrating seismic data in reservoir modeling; the collocated cokriging alternative”. SPE Annual technical conference and exhibition, Society of Petroleum Engineers, Washington, DC, 833–842. 4–7 October.## [15] Sinclair, A.J. and Blackwell, G.H., 2006. Applied mineral inventory estimation. Cambridge University Press.## [16] Rossi, M.E. and Deutsch, C.V., 2013. Mineral resource estimation. Springer Science & Business Media.## [17] Soltani, F., Afzal, P., Asghari, O., 2014, “Delineation of alteration zones based on Sequential Gaussian Simulation and concentration–volume fractal modeling in the hypogene zone of Sungun copper deposit, NW Iran”. Journal of Geochemical Exploration 140, 64-76.## [18] Zelterman, D., 2015, “Applied multivariate statistics with R”. Cham: Springer.## [19] Davis, J.C., Sampson, R.J., 1986, “Statistics and data analysis in geology”. Vol. 646. New York et al.: Wiley.## [20] Rondon, O., 2012, “Teaching aid: minimum/maximum autocorrelation factors for joint simulation of attributes”. Mathematical Geosciences, 44(4), 469-504.## [21] Desbarats, A.J., Dimitrakopoulos, R., 2000, “Geostatistical simulation of regionalized pore-size distributions using min/max autocorrelation factors”. Mathematical Geology, 32(8), 919-942.## [22] نوروزی باغکمه، غلامحسین؛ 1392؛ "روش‌های الکتریکی در ژئوفیزیک اکتشافی"، انتشارات دانشگاه تهران، تهران، جلد اول.## [23] Abedi, M., Asghari, O., Norouzi, G.H., 2015, “Collocated cokriging of iron deposit based on a model of magnetic susceptibility: a case study in Morvarid mine, Iran”. Arabian Journal of Geosciences, 8(4), 2179-2189.## [24] نوروزی باغکمه، غلامحسین؛ 1392؛ "ژئوفیزیک اکتشافی"، انتشارات دانشگاه تهران، تهران، جلد اول.## [25] Loke, M.H., 2003, “Rapid 2D Resistivity & IP Inversion using the least-squares method”. Geotomo Software. Manual.## [26] Dey, A., Morrison, H.F., 1979, “Resistivity modeling for arbitrarily shaped three-dimensional structures”. Geophysics, 44(4), 753-780.## [27] Silvester, P. P., Ferrari, R. L., 1996, “Finite elements for electrical engineers”. Cambridge university press.## [28] Asghari, O., Sheikhmohammadi, S., Abedi, M., Norouzi, G.H., 2016, “Multivariate geostatistics based on a model of geo-electrical properties for copper grade estimation: a case study in Seridune, Iran”. Bollettino di Geofisica Teorica ed Applicata, 57(1).## [29] شیخ محمدی، سمیه؛ اصغری، امید؛ نوروزی باغکمه، غلامحسین؛ 1393؛ "استفاده از متغیر کمکی ضریب سولفیدی بهمنظور بهبود نتایج برآورد مس با کوکریجینگ هممختصات و کریجینگ با روند بیرونی"، نشریه ژئوفیزیک ایران، دوره 8، شماره 1، صفحه 45 تا 58.##