Estimate and Verification of Mineral Resources of a Deposit with Positive Skewness

doi:10.12972/ksmer.2016.53.3.211

All Issue

2016 Vol.53, Issue 3 Preview Page Next Page

Research Paper

Estimate and Verification of Mineral Resources of a Deposit with Positive Skewness 양의 왜도를 갖는 광상의 광량 평가기법과 검증: 이동길
Dong-Kil Lee

30 June 2016. pp. 211-218

PDF

Abstract

In this study, gold deposit with positively skewed grade distribution was selected and a geostatisticaltechnique to estimate the mineral resources is proposed. To that end, normalization of the positively skewed gradedistribution, selection and process of top-cut, use of a logarithmic variogram and conversion of nugget and sillwere carried out so as to estimate the mineral resources with the ordinary Kriging method and inverse distancemethod. Verification using drillhole data with 4 different verification methods reveals that the methods appearalmost to coincide.

Keywords

Estimation of mineral resources

Positive skewness

Variogram

Gold deposit

본 연구에서는 품위분포가 양의 왜도를 보이는 금광상을 선정하여 광량평가를 위한 지구통계적 기법을제시하였다. 이를 위해 양의 왜도를 보이는 품위정보의 정규화 변환, 이상치의 선정과 처리방법, 로그 베리오그램 활용, nugget과 sill의 변환을 수행하여 정규 크리깅법과 역거리가중법에 대한 광량 평가결과를 도출하였다.본 연구에서 제시된 광량 평가결과에 4가지의 검증방법을 적용하여 시추데이터와 검증을 수행한 결과, 거의일치하는 양호한 결과를 확인하였다.

키워드

광량평가

양의 왜도

베리오그램

금광상

References

Alan C.N., 1992, Ore Reserve/Resource Estimation, SME Mining Engineering Handbook 2nd Edition, p. 351.
Coombes, J., 2008, The Art and Science of Resource Estimation, Coombes Capacity.
GEMCOM, 2009, Geostatistics Manual, Gemcom Software International Inc.
Gruijters, S.H., Maljers, D. and Veldkamp, J.G., 2005, “3D interpolation of grain size distributions in the upper 5 m of the channel bed of three lower Rhine distribution,” Physics and chemistry of the earth, Vol. 30, No. 4, pp. 303-316.
Journel A.G., Huijbregts C.J., 1981, Mining Geostatistics, Academic Press, London.
Ki, S.I., Choe, J.G., Kim, S.J. and Jang, M.C., 2003, “Development of a User-Oriented Program for Reserve Estimation and Reservior Characterization,” Journal of the Korean Society of Mineral and Energy Resources Engineers, Vol. 40, No. 3, pp. 198-208.
Kim, S.J. and Park, H.D., 2009, “Development of Software for Mineral Resources Estimation and 3D Modeling using Varigram,” Journal of the Korean Society of Mineral and Energy Resources Engineers, Vol. 46, No. 2, pp. 151-159.
Kim, T.H., 2014, Ore Reserves Estimation Using 3D Modeling Software, MS Thesis, Sangji University, South Korea.
Kupfersberger, H. and Deutsch, C.V., 1999, “Methodology for Integrating analog geologic data in 3D variogram modeling,” AAPG Bulletin, Vol. 83, No. 8, pp. 1262-1278.
Lee, D.G., Seo K.W. and Lim, J.S., 2011, “3D Geostatistical Modeling Using Well Data of Oil Sand Reservoir in the Leismer Field, Canada,” Journal of the Korean Society of Mineral and Energy Resources Engineers, Vol. 48, No. 6, pp. 687-700.
Lee, W.S., Huh, D.G., Kim, I.K., Kim, H.T., Kim S.J. and Park, H.W., 2001, “Inverse Modeling to Generate the Geostatistically Based Heterogeneous Permeability Fields Honoring the Production Data,” Journal of the Korean Society of Mineral and Energy Resources Engineers, Vol. 38, No. 6, pp. 432-442.
Mario, E.R. and Clayton, V.D., 2014, Mineral Resource Estimation, Springer, London.
Meirvenne, M.V., Maes, K. and Hofman, G., 2003, “Threedimensional variability of soil nitrate-nitrogen in an agricultural field,” Biology and fertility of soils, Vol. 37, No. 3, pp. 147-153.
Noh, M.G., 2015, Geostatistical Integrated Analysis of Geophysical Data for Accuracy Enhancement of Reserve Estimation of Metal Mine, Ph.D. Thesis, Kangwon National University, South Korea.
Oh, S.H., 2008, “Geostatistical Inversion of RMR Using Geophysical Data,” Journal of the Korean Society of Mineral and Energy Resources Engineers, Vol. 45, No. 6, pp. 620-626.
Park, N.W. and Oh, S.H., 2006, “Application of Geostatistical Simulation to Assessment of the Effects of Uncertainty of Spatial Data in Mineral Potential Prediction,” Journal of the Korean Society of Mineral and Energy Resources Engineers, Vol. 43, No. 3, pp. 213-223.
Snowden, DV, 1996, Practical interpretation of resource classification guidelines, Mineral Resource and Ore Reserve Estimation, The AusIMM Guide to Good Practice (Monograph 23).

Information

Publisher :The Korean Society of Mineral and Energy Resources Engineers
Publisher(Ko) :한국자원공학회
Journal Title :Journal of the Korean Society of Mineral and Energy Resources Engineers
Journal Title(Ko) :한국자원공학회지
Volume : 53
No :3
Pages :211-218
DOI :https://doi.org/10.12972/ksmer.2016.53.3.211

[1] Alan C.N., 1992, Ore Reserve/Resource Estimation, SME Mining Engineering Handbook 2nd Edition, p. 351.

[2] Coombes, J., 2008, The Art and Science of Resource Estimation, Coombes Capacity.

[3] GEMCOM, 2009, Geostatistics Manual, Gemcom Software International Inc.

[4] Gruijters, S.H., Maljers, D. and Veldkamp, J.G., 2005, “3D interpolation of grain size distributions in the upper 5 m of the channel bed of three lower Rhine distribution,” Physics and chemistry of the earth, Vol. 30, No. 4, pp. 303-316.

[5] Journel A.G., Huijbregts C.J., 1981, Mining Geostatistics, Academic Press, London.

[6] Ki, S.I., Choe, J.G., Kim, S.J. and Jang, M.C., 2003, “Development of a User-Oriented Program for Reserve Estimation and Reservior Characterization,” Journal of the Korean Society of Mineral and Energy Resources Engineers, Vol. 40, No. 3, pp. 198-208.

[7] Kim, S.J. and Park, H.D., 2009, “Development of Software for Mineral Resources Estimation and 3D Modeling using Varigram,” Journal of the Korean Society of Mineral and Energy Resources Engineers, Vol. 46, No. 2, pp. 151-159.

[8] Kim, T.H., 2014, Ore Reserves Estimation Using 3D Modeling Software, MS Thesis, Sangji University, South Korea.

[9] Kupfersberger, H. and Deutsch, C.V., 1999, “Methodology for Integrating analog geologic data in 3D variogram modeling,” AAPG Bulletin, Vol. 83, No. 8, pp. 1262-1278.

[10] Lee, D.G., Seo K.W. and Lim, J.S., 2011, “3D Geostatistical Modeling Using Well Data of Oil Sand Reservoir in the Leismer Field, Canada,” Journal of the Korean Society of Mineral and Energy Resources Engineers, Vol. 48, No. 6, pp. 687-700.

[11] Lee, W.S., Huh, D.G., Kim, I.K., Kim, H.T., Kim S.J. and Park, H.W., 2001, “Inverse Modeling to Generate the Geostatistically Based Heterogeneous Permeability Fields Honoring the Production Data,” Journal of the Korean Society of Mineral and Energy Resources Engineers, Vol. 38, No. 6, pp. 432-442.

[12] Mario, E.R. and Clayton, V.D., 2014, Mineral Resource Estimation, Springer, London.

[13] Meirvenne, M.V., Maes, K. and Hofman, G., 2003, “Threedimensional variability of soil nitrate-nitrogen in an agricultural field,” Biology and fertility of soils, Vol. 37, No. 3, pp. 147-153.

[14] Noh, M.G., 2015, Geostatistical Integrated Analysis of Geophysical Data for Accuracy Enhancement of Reserve Estimation of Metal Mine, Ph.D. Thesis, Kangwon National University, South Korea.

[15] Oh, S.H., 2008, “Geostatistical Inversion of RMR Using Geophysical Data,” Journal of the Korean Society of Mineral and Energy Resources Engineers, Vol. 45, No. 6, pp. 620-626.

[16] Park, N.W. and Oh, S.H., 2006, “Application of Geostatistical Simulation to Assessment of the Effects of Uncertainty of Spatial Data in Mineral Potential Prediction,” Journal of the Korean Society of Mineral and Energy Resources Engineers, Vol. 43, No. 3, pp. 213-223.

[17] Snowden, DV, 1996, Practical interpretation of resource classification guidelines, Mineral Resource and Ore Reserve Estimation, The AusIMM Guide to Good Practice (Monograph 23).

Journal of the Korean Society of Mineral and Energy Resources Engineers ISSN:2288-0291(Print) 2288-2790(Online) 한국자원공학회지

All Issue