Downhole Molybdenum Grade Distribution of the Red Hills Mo- Cu deposit, Trans-Pecos Texas

2013 Downhole Molybdenum Grade Distribution of the Red Hills Mo- Cu deposit, Trans-Pecos Texas Stefanie Frelinger University of Texas at Austin, Jackson School of Geosciences GEO386G: GIS and GPS Applications in Earth Sciences 12/5/2013 1

Contents Objectives... 4 Methods... 5 Data Collection and Cleanup... 5 ArcGIS Processing... 5 Personal Geodatabase Creation and Data Import... 5 DEM Import and Clipping... 8 Database Parsing by Elevation... 10 Kriging... 10 Results, Conclusions, and Future Work... 15 References... 27 Figures Figure 1. The Red Hills intrusive complex is... 4 Figure 2. Display x,y, and z drill hole information from.csv file.... 5 Figure 3. Red Hills drill hole locations.... 6 Figure 4. Export drill hole locations to personal database.... 6 Figure 5. Exporting drill hole locations to a shapefile.... 7 Figure 6. Cerro Orono south-east quadrangle orthophoto underlain by Red Hills drill hole locations.... 7 Figure 7. Zoomed in view of the Red Hills oredeposit with drill hole locations overlaying orthophoto.... 8 Figure 8. DEM file of the Cerro Orona quadrangle of 10m resolution.... 9 Figure 9. Conversion of ASCII 10m DEM file as a float type raster.... 9 Figure 10. DEM clip of the Red Hills area.... 10 Figure 11. Selecting Kriging analysis and output surface type.... 11 Figure 12. Inserting data source and field for kriging analysis.... 11 Figure 13. Selecting all coincident samples as a mean to reproduce a representative kriging surface.... 12 Figure 14. The variogram/semivarigram parameters such as the major range, lag size and number of lags can be adjusted in this kriging step.... 12 Figure 15. Preview of kriging surface before surface generation.... 13 Figure 16. Cross validation of kriging surface data such as number of samples, mean, root-mean-square, mean standardized, etc... 13 Figure 17. Method report generation summarizing pertinent information of krigged surface once analysis is complete.... 14 Figure 18. Ordinary Kriging results for 4000ft-3900ft elevation for Mo%.... 16 Figure 19. Ordinary Kriging results for 3900ft-3800ft elevation for Mo%.... 16 Figure 20. Ordinary Kriging results for 3800ft-3700ft elevation for Mo%.... 17 Figure 21. Ordinary Kriging results for 3600ft-3500ft elevation for Mo%.... 17 Page 2

Figure 22. Ordinary Kriging results for 3500ft-3400ft elevation for Mo%.... 18 Figure 23. Ordinary Kriging results for 3400ft-3300ft elevation for Mo%.... 18 Figure 24. Ordinary Kriging results for 3300ft-3200ft elevation for Mo%.... 19 Figure 25. Ordinary Kriging results for 3200ft-3100ft elevation for Mo%.... 19 Figure 26. 3-D image of the Red Hills ortho photo with drill hole collars on the surface.... 20 Figure 27. 3-D view of the demclip_2ft DEM and drill hole collars of the Red Hills area.... 20 Figure 28. 3-D view of depth and orientation of drill hole collars in the subsurface.... 21 Figure 29. Side of view of Red Hills topography and drill holes.... 21 Figure 30. Side view of stacked vector files converted from elevation kriging surfaces.... 22 Figure 31. Oblique view of 4000ft-3900ft vector file.... 22 Figure 32. Oblique view of 3900ft-3800ft vector file.... 23 Figure 33. Oblique view of 3800ft-3700ft vector file.... 23 Figure 34. Oblique view of 3700ft-3600ft vector file.... 24 Figure 35. Oblique view of 3700ft-3600ft vector file.... 24 Figure 36. Oblique view of 3500ft-3400ft vector file.... 25 Figure 37. Oblique view of 3400ft-3300ft vector file.... 25 Figure 38. Oblique view of 3300ft-3200ft vector file.... 26 Page 3

Objectives The Laramide age Red Hills porphyry Molybdenum-Copper deposit is located in Trans-Pecos Texas, 18 miles NE from the city of Presidio (Figure 1). The intrusive complex was emplaced into a Permian sedimentary sequence resulting in an extensive hornfels zone with local garnet skarn. The molybdenum (Mo) host mineral molybdenite exists within pervasive quartz stockwork veins cross-cutting quartzmonzonite, quartz-latite, and biotite porphyry wall rocks. Tosca Mining Corporation drilled over 24,000ft of new Red Hills core during a drilling and evaluation program in 2012 which provided new Mo and Cu assay information. This new suite of data has been incorporated into a dataset with historic drill hole information for the purpose of determining the downhole distribution of Mo grades throughout the extent of the orebody to identify any trends that suggests locations of fluid flow pathways of the mineralized hydrothermal solutions. Ordinary kriging was performed on Mo assay grades every 100ft downhole. This statistical analysis was chosen because it is used to provide the best linear, unbiased estimate for grade based on a least squares minimization of the error of estimation, or kriging error. Kriging analysis is able to interpolate Mo grades where sample locations are not present by using a weighted average based on sample distance. These weights are calculated by the minimum variance defined in a variogram. Figure 1. The Red Hills intrusive complex is located 3mi south-east of the Chinati Mountains Caldera, west of the Shafter mining district (Evans, 1975). Page 4

Methods Data Collection and Cleanup Exploration at the Red Hills area began in the early 1960 s where several stages of prospecting from different companies has made Mo assay drill hole data available for this study. This data was stored in excel spreadsheets and required significant formatting in order to be used effectively in ArcGIS. To- From intervals were substracted by the appropriate elevation starting from the collar elevations in order to obtain the true depth elevation for vertical holes. Angled holes required more robust trigonometric methods utilizing azimuth, sample depth, and drill hole angle information to calculate the correct x, y, and z locations at every assay interval. This excel file was then converted into a comma delimited.csv file. The 10 meter resolution ASTER Digital Elevation Model (DEM) of the South-East Quarter-Quad of the Cerro Orona quadrangle and ortho imagery were obtained from Texas Natural Resources Information System at www.tnris.org. ArcGIS Processing Personal Geodatabase Creation and Data Import A personal geodatabase named DEM was created in the :S-drive which contained the drill hole.csv file named project. In ArcMap10, the coordinate system and datum was defined in the data frame as NAD83 State Plane Texas South Central FIPS 4203 Feet as well as the geographic coordinate system GSC North America 1983. The.csv file was loaded and displayed into a blank map as a layer by File>Add Data>Add XY Data(Figure 2 and 3). The x, y, and z field were matched with the appropriate fields which created a project.txt Events layer. This layer was converted to a feature class within the personal geodatabase and also as a shapefile by right clicking>data> Export Data renaming the file RH_Drillholes(Figure 4 and 5). Figure 2. Display x,y, and z drill hole information from.csv file. Page 5

Figure 3. Red Hills drill hole locations. Figure 4. Export drill hole locations to personal database. Page 6

Figure 5. Exporting drill hole locations to a shapefile. The Cerro Orona ortho image was added to the Table of Contents (TOC) by Add Data > naip12_nccir_1m 2904_13_4_20120901 with no requirement of projection transformations (Figure 6 and 7). Figure 6. Cerro Orono south-east quadrangle orthophoto underlain by Red Hills drill hole locations. Page 7

Figure 7. Zoomed in view of the Red Hills oredeposit with drill hole locations overlaying orthophoto. DEM Import and Clipping The dem 10m_2904.ascii file was loaded into the TOC (Figure 8) and transformed to a float output type raster(figure 9). The DEM was clipped to a map area from a drafted polygon using by utilizing the Arc Toolbox Datamanagement Clip tool within the System Toolboxes. The dem was chosen as the input raster and the map area was chosen as the output extent. The resulting clip, clip2, was saved to the personal geodatabase(figure 10). The clip2 dem, however, was in meter units rather than imperial so the clip2 dem was inputted Raster Calculator located in Spatial Analyst within ArcToolbox and multiplied by 3.28084. The output file was named demclip_2ft. 20ft elevation contours were constructed from the demclip_2ft dem by the Spatial Analyst Tools extension in ArcToolbox: Spatial Analyst Tools>Surface>Contour>and the output type defined as clip2_ft. Page 8

Figure 8. DEM file of the Cerro Orona quadrangle of 10m resolution. Figure 9. Conversion of ASCII 10m DEM file as a float type raster. Page 9

Figure 10. DEM clip of the Red Hills area. Database Parsing by Elevation Shapefiles needed to be created for datapoints that lied within specified elevations intervals within a 100ft range from the RH_Drillholes shapefile. This was done by opening the attribute table by right clicking RH_Drillholes.shp>Open Attribute Table and performing a query to select all samples that existed above and below a specific elevations. The selected records were exported as shapefile and added to the TOC as a layer. These data samples were divided in 100ft vertical increments from 4300ft- 2100ft. Kriging Preliminary kriging analyses were run on elevation ranges from 4300ft-2800ft in order to determine the most appropriate kriging parameters to use consistently at each elevation range. This was done by activating the Geostatistical Analyst Extension>Geostatistical Analyst>Geostatistical Wizard>Ordinary Kriging Type and Prediction Output Surface Type>Select Source Dataset and Mo Data Field>Use Mean>Finish. The range, lag size, number of neighbors, partial sill size, number of samples, and number of drill holes were recorded for each kriging pass with every elevation range. Due to limiting drill hole numbers and sample size issues only elevations from 4000ft-2900ft were retained as the study moved forward. When choosing the appropriate range (which directly affects your search ellipse size of the semi-major/semi-minor axes), it is best practice to choose a range value that does not exceed the Page 10

smallest range from the list in Table 1. Therefore, the search parameters from elevation 4000ft-3200ft were chosen: Range: 642ft Lags: 85 Lag Size: 12 Max Sample Size: 5 Min Sample Size: 2 Each Kriging Prediction Map was exported as vector files by right clicking the layer>data>export to Vector>correct input file>new output file name. Figure 11. Selecting Kriging analysis and output surface type. Figure 12. Inserting data source and field for kriging analysis. Page 11

Figure 13. Selecting all coincident samples as a mean to reproduce a representative kriging surface. Figure 14. The variogram/semivarigram parameters such as the major range, lag size and number of lags can be adjusted in this kriging step. Page 12

Figure 15. Preview of kriging surface before surface generation. Figure 16. Cross validation of kriging surface data such as number of samples, mean, root-mean-square, mean standardized, etc. Page 13

Figure 17. Method report generation summarizing pertinent information of krigged surface once analysis is complete. Table 1. Preliminary Ordinary Kriging runs by elevation. Crossed out intervals were excluded for the remainder of the study. From (ft) To (ft) Range Lag Lag # Partial Sill Weights Sample # Drill Hole # 4200 4100 690 107 0.000128 8 19 13 4100 4000 690 107 12 376.8937 8 19 13 4000 3900 1376 175 0.00106 16 252 >49 3900 3800 1823 222 12 0.00153 20 199 >49 3800 3700 934 114 12 0.00118 17 171 >49 3700 3600 3435 393 12 0.0011 20 134 >49 3600 3500 703 79 12 0.00053 15 118 49 3500 3400 681 69 12 0.0016 8 102 36 3400 3300 642 85 12 0.00088 8 98 30 3300 3200 1940 221 12 0.0059 15 104 25 3200 3100 36 4 12 0.0021 8 86 20 3100 3000 65 8 12 0.00057 7 65 15 3000 2900 296 34 12 0.0002 7 61 14 2900 2800 29 3.5 12 0.0019 7 46 13 Page 14

Results, Conclusions, and Future Work In conjunction with generating x,y surfaces of the kriging prediction maps (Figures 18-21), the kriging surfaces for each elevation range were converted to vector files by right clicking the kriging surface layer>export Data> To a Vector. These vector files were loaded into ArcScene along with drill hole data (Figures 27-30), demclip2_ft DEM surface(27-30), clip2_ft contour file, and 2m_05 orthophoto (Figures 26-38). The elevation values were defined for each vector file by right clicking the layer in the TOC>Properties> Base Heights tab>use a constant value or expression> and inputting the correct base elevation for each file. The demclip2_ft DEM 3-D surface was generated by right clicking the layer in the TOC>Properties> Base Heights tab>floating on a custom surface>demclip2_ft input option (Figure 27). This same procedure was applied to the 2m_05 orthophoto and clip2_ft contour file (Figure 26). Higher elevations ranging from 4000ft-3500ft, kriging surfaces have produced a crescent shaped Mo oredbody where high grade concentrations exist on the eastern and western limbs of the crescent structure (Figures 18-21). A weakly mineralized zone to the northwest has been highlighted, however there is little confidence that this is a product of reality because the contours were generated based on values from one drill hole. Mo grades continue to increase and become more laterally extensive spreading higher grades to the north and north-east from the main orebody. At the 3500ft-3400ft elevation range, three high grade bull s-eyes appear which is most likely a product of declining sample numbers and increasing distances between samples (Figure 22). The continuity of these high grades zones is quite disjunctive. Perhaps fluid flow was focused along specific high angle structures and favorable conditions for mineral precipitation occurred at this depth. This may also be a false product from the kriging data due to high variation in the samples at this particular depth. Kriging surfaces start to become rough and irregular at the 3300ft-3200ft elevation range which points out a highly concentrated Mo zone on the western flank of the orebody. Poor correlation of Mo grade distribution occurs at 3200ft-3100ft by which the results have been largely ignored. In conclusion, Mo grades analyzed by ordinary kriging give satisfying results from the 4000ft elevation level to the 3400ft elevation level. Producing kriging maps below the 3400ft yields fruitless results due to the reduction of samples and larger distances between those samples. Future work will include the incorporation of Cu assay data split by hypogene or supergene mineralization by similar kriging methods applied in this study to identify and possible correlations with Mo mineralization. Alteration data will also be incorporated into the database to correlate sulfide mineralization with specific alteration types. Structure data from past field season will also be imported into the data base to verify whether the bullseyes in elevation 3500ft are actually related to subsurface structures or not. Page 15

Figure 18. Ordinary Kriging results for 4000ft-3900ft elevation for Mo%. Figure 19. Ordinary Kriging results for 3900ft-3800ft elevation for Mo%. Page 16

Figure 20. Ordinary Kriging results for 3800ft-3700ft elevation for Mo%. Figure 21. Ordinary Kriging results for 3600ft-3500ft elevation for Mo%. Page 17

Figure 22. Ordinary Kriging results for 3500ft-3400ft elevation for Mo%. Figure 23. Ordinary Kriging results for 3400ft-3300ft elevation for Mo%. Page 18

Figure 24. Ordinary Kriging results for 3300ft-3200ft elevation for Mo%. Figure 25. Ordinary Kriging results for 3200ft-3100ft elevation for Mo%. Page 19

Figure 26. 3-D image of the Red Hills ortho photo with drill hole collars on the surface. Figure 27. 3-D view of the demclip_2ft DEM and drill hole collars of the Red Hills area. Page 20

Figure 28. 3-D view of depth and orientation of drill hole collars in the subsurface. Figure 29. Side of view of Red Hills topography and drill holes. Page 21

Figure 30. Side view of stacked vector files converted from elevation kriging surfaces. Figure 31. Oblique view of 4000ft-3900ft vector file. Page 22

Figure 32. Oblique view of 3900ft-3800ft vector file. Figure 33. Oblique view of 3800ft-3700ft vector file. Page 23

Figure 34. Oblique view of 3700ft-3600ft vector file. Figure 35. Oblique view of 3700ft-3600ft vector file. Page 24

Figure 36. Oblique view of 3500ft-3400ft vector file. Figure 37. Oblique view of 3400ft-3300ft vector file. Page 25

Figure 38. Oblique view of 3300ft-3200ft vector file. Page 26

References Evans, T.J., 1975, Gold and silver in Texas: University of Texas at Austin, Bureau of Economic Geology, Mineral Resource Circular No. 56, 36p. Gilmer, A.K., 2001, Age and characterization of the red hills porphyry copper-molybdenum deposit and its relationship to the Chinati Mountains Caldera, Presidio county, Texas. Master of Science thesis. The University of Texas at Austin. Page 27

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