THE APPLICATION OF PROJECTION PURSUIT MULTIVARIATE TRANSFORMATION (PPMT) TECHNIQUE IN COPPER MULTI-ELEMENT DEPOSITS
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Date
2024-04-12
Authors
Korniyenko, Artur
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Publisher
Nazarbayev University School of Mining and Geosciences
Abstract
The contemporary mining sector extensively incorporates digital technologies all over the mining
operations. These digital mine operations could be considered as more productive due to their
ability to be used as an additional data during strategic mine planning activities. Geostatistics and
mine planning are crucial processes for mining projects, including a range of valuable tools.
Traditional methods of mine planning sometimes include oversimplifications and fail to take into
account many sources of information that may aid in risk management and the development of
more optimum designs. In the field of mine planning, deterministic approaches that often rely on
a singular mineral resource model as an input, being replaced by a stochastic approaches that
involve the integration of many realizations that are equally probable, so that risk management
based on worst case scenario concept could be done. In addition, such bottleneck of typical
deterministic approaches (kriging) as the underestimation of low values and the overestimation of
high values for the underlying grade as well as smoothing effect are being avoided. In the context
of multi-element deposits, the use of multivariate geostatistics is recommended in order to more
accurately replicate the multivariate correlation between the variables. The latter aspect is
particularly critical since standard geostatistical approaches are unable to account for such specific
trait as spatial continuity of the deposit, resulting in a significant reduction in the accuracy of the
final resource model used for mine planning. This study proposes the comparison of stochastic
methodologies such as independent simulations, co-simulations and Projection Pursuit
Multivariate Transformation (PPMT), so that the most productive methodology could be suggested
as the most accurate one in terms of reproducing the intrinsic correlation coefficient between two
of the most correlated variables in this deposit that are copper and molybdenum. In addition, the
suggestion of the method was done based on the reproduction of the main statistical parameters
such as mean, variance, linear (Pearson’s correlation coefficient) and non-linear correlation
coefficient (Spearman's rank correlation coefficient) coefficients and the comparison of them with
the data measured by drillholes.
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Citation
Korniyenko, A. (2024). The application of projection pursuit multivariate transformation (PPMT) technique in copper multi-element deposits. Nazarbayev University School of Mining and Geosciences