Abstract

In the theory of sampling, variograms have proven to be a powerful tool to characterise the heterogeneity of 1-dimensional lots. Yet its definition and application in sampling for mineral processing have always been limited to one variable, typically ore grade. However this definition is not adapted to sampling for mineral processing where samples contain multiple properties of interest, i.e. variables, such as multiple element grades, grain size, etc. For such cases, the multivariable variogram, originally developed for spatial data analysis, can be used to summarise time variation of multiple variables (e.g. ore characteristics which are important for the process) and highlights the multivariate time auto-correlation of these variables. A case study of low-grade kaolin residue sampling for gravity processing shows that the multivariogram summarises the overall variability and highlights a periodic phenomenon when all variables are taken into account. This example illustrates the potential of the multivariable variogram compared to the classical approach.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.