This chapter delves into the methods for estimating mineral resources and ore reserves. It begins with sampling and sample analyses, emphasizing the importance of sample studies, including geological, hydrogeological, physical, geotechnical, chemical, and metallurgical assessments. The concepts of ore grade, compositing of grades, and cut-off grade are discussed, highlighting the significance of the length-weighted average method for calculating average ore grade. Various estimation methods are introduced, including polygonal methods and geostatistical approaches such as inverse distance weighting (IDW) and ordinary Kriging methods. These methods are explained in the context of their applications, strengths, and limitations in mineral resources estimation. The chapter details the mathematical processes of the Ordinary Kriging method, which optimizes ore reserves estimation by considering the spatial correlation and variation of ore grade. The chapter also highlights the creation and utilization of block models together with geostatistical methods as an essential foundation for visualizing and calculating mineral resources. Additionally, the importance of regulatory compliance in the reporting of mineral resources and ore reserves according to the JORC code is emphasized.

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Mineral Resources and Ore Reserves Estimation

  • Greg Guanlin You

摘要

This chapter delves into the methods for estimating mineral resources and ore reserves. It begins with sampling and sample analyses, emphasizing the importance of sample studies, including geological, hydrogeological, physical, geotechnical, chemical, and metallurgical assessments. The concepts of ore grade, compositing of grades, and cut-off grade are discussed, highlighting the significance of the length-weighted average method for calculating average ore grade. Various estimation methods are introduced, including polygonal methods and geostatistical approaches such as inverse distance weighting (IDW) and ordinary Kriging methods. These methods are explained in the context of their applications, strengths, and limitations in mineral resources estimation. The chapter details the mathematical processes of the Ordinary Kriging method, which optimizes ore reserves estimation by considering the spatial correlation and variation of ore grade. The chapter also highlights the creation and utilization of block models together with geostatistical methods as an essential foundation for visualizing and calculating mineral resources. Additionally, the importance of regulatory compliance in the reporting of mineral resources and ore reserves according to the JORC code is emphasized.