142
11 CONCLUSIONS
When the deposit being studied has a lognormal distribution, a high nugget effect and a
short-range variogram combined with a high-selectivity operation and limited number of
drillholes that lead to a substantial support difference between the panel (limited by the drilling mesh) and the SMU size, in-situ resources estimation with linear methods such as Ordinary Kriging are not effective for a reliable estimation of the contained metal in such deposit.
For an accurate estimation of the contained metal, the concept of Recoverable Resources
need to be applied with the use of non-linear techniques such as Uniform Conditioning and
Conditional Simulations (SMU scale) that provide practical and reliable alternative for the
assessment of the recoverable resources.
Univariate Turning Bands does not explicitly use the correlations between the main and
auxiliary variables as the Localized Multivariate Uniform Conditioning, besides this, Multivariate Localized Uniform Conditioning grade tonnage distribution lies within the range of
100 grade tonnage curves obtained by using conditional simulation. The results achieved by
two different approaches, Localize Multivariate Uniform Conditioning and Turning Band
Simulation, provides a more accurate global estimate of grade and tonnage over the in-situ
linear estimation performed with Ordinary Kriging.
Although the Turning Bands Simulation is known for its accuracy and computational efficiency, the Localize Multivariate Uniform Conditioning is less time consuming and has an
easier workflow implementation. Nevertheless, only the simulation approaches can quantify
Figure 9. Grade tonnage curve of LUC and 100 realizations, above the level 750.
Figure 10. Nb 2 O 5 grade variation obtained from 100 realizations and the LUC throughout the
life of mine.
Cutoff
Cutoff
100
100
90
90
80
80
70
70
1!,
~
j
60
60
50
5 0
l
.
I!
4 0
40
~
30
30
10
10
Krige_SMU
LUC lOxlOx S
Cut o ff
Cutoff
HlOO S i mulatio n
-
Simulation Range
- NB_MEAN
-P-OS
- P-95
e NB_LUC
2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036
11 CONCLUSIONS
When the deposit being studied has a lognormal distribution, a high nugget effect and a
short-range variogram combined with a high-selectivity operation and limited number of
drillholes that lead to a substantial support difference between the panel (limited by the drilling mesh) and the SMU size, in-situ resources estimation with linear methods such as Ordinary Kriging are not effective for a reliable estimation of the contained metal in such deposit.
For an accurate estimation of the contained metal, the concept of Recoverable Resources
need to be applied with the use of non-linear techniques such as Uniform Conditioning and
Conditional Simulations (SMU scale) that provide practical and reliable alternative for the
assessment of the recoverable resources.
Univariate Turning Bands does not explicitly use the correlations between the main and
auxiliary variables as the Localized Multivariate Uniform Conditioning, besides this, Multivariate Localized Uniform Conditioning grade tonnage distribution lies within the range of
100 grade tonnage curves obtained by using conditional simulation. The results achieved by
two different approaches, Localize Multivariate Uniform Conditioning and Turning Band
Simulation, provides a more accurate global estimate of grade and tonnage over the in-situ
linear estimation performed with Ordinary Kriging.
Although the Turning Bands Simulation is known for its accuracy and computational efficiency, the Localize Multivariate Uniform Conditioning is less time consuming and has an
easier workflow implementation. Nevertheless, only the simulation approaches can quantify
Figure 9. Grade tonnage curve of LUC and 100 realizations, above the level 750.
Figure 10. Nb 2 O 5 grade variation obtained from 100 realizations and the LUC throughout the
life of mine.
Cutoff
Cutoff
100
100
90
90
80
80
70
70
1!,
~
j
60
60
50
5 0
l
.
I!
4 0
40
~
30
30
10
10
Krige_SMU
LUC lOxlOx S
Cut o ff
Cutoff
HlOO S i mulatio n
-
Simulation Range
- NB_MEAN
-P-OS
- P-95
e NB_LUC
2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036