Problems of Estimating the Resources of Accompanying Elements: A Case Study from the Cu-Ag Rudna Deposit (Legnica-Głogów Copper District, Poland)

• Published in: Minerals (Basel) Vol. 11; no. 12; p. 1431
• Main Authors: Auguścik-Górajek, Justyna, Mucha, Jacek, Wasilewska-Błaszczyk, Monika, Kaczmarek, Wojciech
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.12.2021
• Subjects: Abundance; Accuracy; Cobalt; Copper; Copper ores; Economics; Errors; Estimates; Estimation; Exploitation; Lead; Lithology; Mineral deposits; Mineralization; Minerals; Mining; Profitability; Recovery; Resources; Sampling; Sediments; Silver; Silver mines; Spatial variations; Statistical methods; Stratigraphy; Poland
• DOI: 10.3390/min11121431
• ISSN: 2075-163X

As a result of the exploitation of ore deposits, in addition to the main elements, the accompanying elements are also partially recovered. Some of them increase the profitability of exploitation, while others reduce it because they hinder the recovery of the main elements and thus increase the costs of the recovery process. A comprehensive economic calculation to assess the profitability of ore mining depends on an appropriately accurate estimation of the resources of both the main and associated elements. This issue was analyzed with the example of the Cu-Ag Rudna ore deposit (LGCD, Poland). The subject of the assessment was the resources prediction accuracy of the main element (Cu) and four (4) accompanying elements (Co, Ni, Pb, and V) using geostatistical estimation method, in particular the ordinary kriging after the estimation of the relative variograms for describing the spatial variability structures of elements abundance. It was found that the standard kriging errors (deviations) in accompanying elements resources that are scheduled for exploitation within a one-year period in some parts of deposits are drastically greater (2 to 5 times) than the estimation errors of the main element resources. This is due to the sparse sampling pattern for their determinations and/or the high variability (among others nugget effect) of their abundance. In this situation, without additional sampling and a denser sampling pattern, the possibilities of a reliable assessment of the influence of accompanying elements on the economic consequences of exploitation are very limited.