4
based on the metal equivalent relationship, which takes
into account the different metal ratios. (Karpekov, 2016).
Exploratory Data Analysis
The data were reviewed to determine appropriate inter-
polation domains, and appropriate estimation as well as
grade interpolation parameters. Statistical procedures were
applied to the data to establish different domains based on
the availability of geological information. The Ninajassa
fault in the central part of the project, the Uchuro fault
to the north and the Azuca fault to the south, establish
domains.
The statistics for the variables Ag, Au and thickness of
veins were completed. The results obtained were used to
validate the construction of the block model and the devel-
opment of estimation plans. Analyzes were performed on
composite assay data.
RESULTS
Composites
Statistical tables for composites of the elements Au, Ag
and thickness were prepared. The statistics of the Au and
Ag variables were carried out on composites with a fixed
length of 2 meters, while the thickness statistics were car-
ried out with the measured data of the real thickness of the
structure.
To establish the boundaries, the threshold and even-
tually, for the veins with more data, the probability plot
graphs were taken as elements of judgment.
Table 3 shows the results of the composites of each
vein, for the Silver (Ag) element, as well as the statistical
analysis of the vein grades.
The probability plot was made for the Ag element com-
posites every two meters in length.
Table 4 shows the results of the composites of each
vein, for the Gold (Au) element, as well as the statistical
analysis of the vein grades.
The probability plot was made for the Au element
composites every two meters in length.
Table 5 shows the results of the composites of each
vein, for the thickness of veins.
The probability plot was made for the thickness of all
structures.
Variogram
The variography of the project was reviewed first evalu-
ating the veins with more composite data, then making
groupings by systems and finally grouping all the veins. The
elements Ag and Au were evaluated.
Table 3. Statistics of the composites for Ag of the 33 veins
Code of Vein Min Max Avg Var SD CV
01_AÑA 10.7 109.3 60.0 4860.0 69.7 1.2
02_BRI 2.4 296.0 100.3 13684.0 117.0 1.2
03_CHA 5.3 194.8 52.6 4189.0 64.7 1.2
04_CHO 1.7 685.4 101.0 20294.0 142.5 1.4
05_COL 2.8 740.5 166.7 47750.0 218.5 1.3
06_ESC 0.3 859.7 108.1 36187.0 190.2 1.8
07_ESP B 0.8 839.8 118.0 23100.0 152.0 1.3
08_ESP B N 1.1 583.6 270.9 49481.0 222.4 0.8
09_ESP C 1.9 947.0 156.1 91036.0 301.7 1.9
10_ESP C1 3.2 402.1 56.9 6631.0 81.4 1.4
11_ESP S 1 1.6 486.4 69.6 7883.0 88.8 1.3
12_ESP S 2 12.3 131.7 41.5 1541.0 39.3 1.0
13_ESP S 3 51.2 1522.1 401.4 397851.0 630.8 1.6
14_ESP S 4 32.3 64.2 48.3 508.0 22.5 0.5
15_ESP S 5 82.5 82.5 82.5 0.0 0.0 0.0
16_ESP_A 2.8 714.7 130.2 27327.0 165.3 1.3
17_GLA 34.9 290.9 140.2 17924.0 133.9 1.0
18_MEZT 1.5 976.0 215.1 53.0 229.4 1.1
19_ORS 1.3 499.0 146.4 30634.0 175.0 1.2
20_SORP 53.2 1239.1 529.3 269658.0 519.3 1.0
21_PER 8.7 585.4 124.8 16719.0 129.3 1.0
22 173.0 202.9 188.0 448.0 21.2 0.1
23 38.4 125.2 94.2 2345.0 48.4 0.5
24 8.3 567.2 207.9 68761.0 262.2 1.3
25 168.0 669.0 440.2 64162.0 253.3 0.6
26 120.8 311.0 206.3 9321.0 96.5 0.5
27 254.6 254.6 254.6 0.0 0.0 0.0
28 51.2 344.0 180.1 10420.0 102.1 0.6
29 32.7 236.1 130.6 7737.0 88.0 0.7
30 16.2 290.1 101.5 12932.0 113.7 1.1
31 15.9 445.0 117.1 22846.0 151.1 1.3
32 10.4 355.5 183.8 13167.0 114.7 0.6
33 239.0 1772.9 1005.9 1176409.0 1084.6 1.1
Figure 5. Probability plot for Ag element
based on the metal equivalent relationship, which takes
into account the different metal ratios. (Karpekov, 2016).
Exploratory Data Analysis
The data were reviewed to determine appropriate inter-
polation domains, and appropriate estimation as well as
grade interpolation parameters. Statistical procedures were
applied to the data to establish different domains based on
the availability of geological information. The Ninajassa
fault in the central part of the project, the Uchuro fault
to the north and the Azuca fault to the south, establish
domains.
The statistics for the variables Ag, Au and thickness of
veins were completed. The results obtained were used to
validate the construction of the block model and the devel-
opment of estimation plans. Analyzes were performed on
composite assay data.
RESULTS
Composites
Statistical tables for composites of the elements Au, Ag
and thickness were prepared. The statistics of the Au and
Ag variables were carried out on composites with a fixed
length of 2 meters, while the thickness statistics were car-
ried out with the measured data of the real thickness of the
structure.
To establish the boundaries, the threshold and even-
tually, for the veins with more data, the probability plot
graphs were taken as elements of judgment.
Table 3 shows the results of the composites of each
vein, for the Silver (Ag) element, as well as the statistical
analysis of the vein grades.
The probability plot was made for the Ag element com-
posites every two meters in length.
Table 4 shows the results of the composites of each
vein, for the Gold (Au) element, as well as the statistical
analysis of the vein grades.
The probability plot was made for the Au element
composites every two meters in length.
Table 5 shows the results of the composites of each
vein, for the thickness of veins.
The probability plot was made for the thickness of all
structures.
Variogram
The variography of the project was reviewed first evalu-
ating the veins with more composite data, then making
groupings by systems and finally grouping all the veins. The
elements Ag and Au were evaluated.
Table 3. Statistics of the composites for Ag of the 33 veins
Code of Vein Min Max Avg Var SD CV
01_AÑA 10.7 109.3 60.0 4860.0 69.7 1.2
02_BRI 2.4 296.0 100.3 13684.0 117.0 1.2
03_CHA 5.3 194.8 52.6 4189.0 64.7 1.2
04_CHO 1.7 685.4 101.0 20294.0 142.5 1.4
05_COL 2.8 740.5 166.7 47750.0 218.5 1.3
06_ESC 0.3 859.7 108.1 36187.0 190.2 1.8
07_ESP B 0.8 839.8 118.0 23100.0 152.0 1.3
08_ESP B N 1.1 583.6 270.9 49481.0 222.4 0.8
09_ESP C 1.9 947.0 156.1 91036.0 301.7 1.9
10_ESP C1 3.2 402.1 56.9 6631.0 81.4 1.4
11_ESP S 1 1.6 486.4 69.6 7883.0 88.8 1.3
12_ESP S 2 12.3 131.7 41.5 1541.0 39.3 1.0
13_ESP S 3 51.2 1522.1 401.4 397851.0 630.8 1.6
14_ESP S 4 32.3 64.2 48.3 508.0 22.5 0.5
15_ESP S 5 82.5 82.5 82.5 0.0 0.0 0.0
16_ESP_A 2.8 714.7 130.2 27327.0 165.3 1.3
17_GLA 34.9 290.9 140.2 17924.0 133.9 1.0
18_MEZT 1.5 976.0 215.1 53.0 229.4 1.1
19_ORS 1.3 499.0 146.4 30634.0 175.0 1.2
20_SORP 53.2 1239.1 529.3 269658.0 519.3 1.0
21_PER 8.7 585.4 124.8 16719.0 129.3 1.0
22 173.0 202.9 188.0 448.0 21.2 0.1
23 38.4 125.2 94.2 2345.0 48.4 0.5
24 8.3 567.2 207.9 68761.0 262.2 1.3
25 168.0 669.0 440.2 64162.0 253.3 0.6
26 120.8 311.0 206.3 9321.0 96.5 0.5
27 254.6 254.6 254.6 0.0 0.0 0.0
28 51.2 344.0 180.1 10420.0 102.1 0.6
29 32.7 236.1 130.6 7737.0 88.0 0.7
30 16.2 290.1 101.5 12932.0 113.7 1.1
31 15.9 445.0 117.1 22846.0 151.1 1.3
32 10.4 355.5 183.8 13167.0 114.7 0.6
33 239.0 1772.9 1005.9 1176409.0 1084.6 1.1
Figure 5. Probability plot for Ag element