Cluster and outlier analysis applications in minerals exploration

Transcription

1 Cluster and outlier analysis applications in minerals exploration OZRI 2015, Melbourne Australia

2 Cluster and outlier analysis applications in minerals exploration Laz Katona Principal Geoscientist Geological Survey of South Australia

3 Today s Presentation Where is the study area? Exploration approaches Vectorisation of gridded data Cluster and Outlier Analysis Conclusions 3

4 Where? Northern Gawler Craton Iron-Oxide Copper Gold (IOCG±U): Olympic Dam Prominent Hill Carrapateena Khamsin Iron ore: Cairn Hill Peculiar Knob Hawks Nest 4

5 What s out there? Nothing visible at surface Heavy reliance on geophysical (potential field) data Gravity Total Magnetic Intensity (TMI) Moonplain near Coober Pedy Photo Courtesy S Hill 5

6 What s out there? Nothing visible at surface Heavy reliance on geophysical (potential field) data Gravity Total Magnetic Intensity (TMI) Moonplain near Coober Pedy Photo Courtesy S Hill 5

7 What s out there? Nothing visible at surface Heavy reliance on geophysical (potential field) data Gravity Total Magnetic Intensity (TMI) 5

8 What s out there? Nothing visible at surface Heavy reliance on geophysical (potential field) data Gravity Total Magnetic Intensity (TMI) 5

9 Traditional approaches 6

10 Traditional approaches Targeting potential field anomalies: 6

11 Traditional approaches Targeting potential field anomalies: Gravity 6

12 Traditional approaches Targeting potential field anomalies: Gravity TMI (magnetic) 6

13 Traditional approaches Targeting potential field anomalies: Gravity TMI (magnetic) Spatially coincident Gravity and TMI (Olympic Dam Style hematite breccia hosted IOCG±U) 6

14 Advantages of vectorisation Display Overlay operations Classification (symbology) Ranking anomalies Quantitative analysis Geoprocessing GIS mineral potential studies. Clustering analysis 7

15 Vectorisation of geophysical grids 8

16 Vectorisation of geophysical grids 8

17 Vectorisation of geophysical grids Contouring Selection of anomalous regions Embedding raster statistics into polygons Classification and selection of sites 8

18 Vectorisation of geophysical grids Contouring Selection of anomalous regions Embedding raster statistics into polygons Classification and selection of sites 8

19 Vectorisation of geophysical grids Contouring Selection of anomalous regions Embedding raster statistics into polygons Classification and selection of sites 8

20 Vectorisation of geophysical grids Contouring Selection of anomalous regions Embedding raster statistics into polygons Classification and selection of sites 8

21 Vectorisation of geophysical grids Contouring Selection of anomalous regions Embedding raster statistics into polygons Classification and selection of sites 9

22 Vectorisation of geophysical grids Contouring Selection of anomalous regions Embedding raster statistics into polygons Classification and selection of sites 9

23 Vectorisation of geophysical grids Contouring Selection of anomalous regions Embedding raster statistics into polygons Classification and selection of sites 9

24 Vectorisation of geophysical grids Contouring Selection of anomalous regions Embedding raster statistics into polygons Classification and selection of sites 10

25 Vectorisation of geophysical grids Contouring Selection of anomalous regions Embedding raster statistics into polygons Classification and selection of sites 10

26 Vectorisation of geophysical grids Contouring Selection of anomalous regions Embedding raster statistics into polygons Classification and selection of sites 10

27 Vectorisation of geophysical grids Contouring Selection of anomalous regions Embedding raster statistics into polygons Classification and selection of sites 10

28 Vectorisation of geophysical grids Contouring Selection of anomalous regions Embedding raster statistics into polygons Classification and selection of sites 10

29 Vectorisation of geophysical grids Contouring Selection of anomalous regions Embedding raster statistics into polygons Classification and selection of sites 10

30 Vectorisation of geophysical grids Contouring Selection of anomalous regions Embedding raster statistics into polygons Classification and selection of sites 10

31 Vectorisation of geophysical grids Contouring Selection of anomalous regions Embedding raster statistics into polygons Classification and selection of sites 10

32 Vectorisation of geophysical grids Contouring Selection of anomalous regions Embedding raster statistics into polygons Classification and selection of sites 11

33 Vectorisation of geophysical grids Contouring Selection of anomalous regions Embedding raster statistics into polygons Classification and selection of sites 11

34 Vectorisation of geophysical grids Contouring Selection of anomalous regions Embedding raster statistics into polygons Classification and selection of sites Olympic Dam ore body outline, after Ehrig, et al.,

35 Vectorisation of geophysical grids Contouring Selection of anomalous regions Embedding raster statistics into polygons Classification and selection of sites 11

36 Vectorisation of geophysical grids Contouring Selection of anomalous regions Embedding raster statistics into polygons Classification 12

37 Vectorisation of geophysical grids Contouring Selection of anomalous regions Embedding raster statistics into polygons Classification 12

38 Vectorisation of geophysical grids Contouring Selection of anomalous regions Embedding raster statistics into polygons Classification 12

39 Vectorisation of geophysical grids Contouring Selection of anomalous regions Embedding raster statistics into polygons Classification 12

40 Vectorisation of geophysical grids Contouring Selection of anomalous regions Embedding raster statistics into polygons Classification 12

41 Vectorisation of geophysical grids Contouring Selection of anomalous regions Embedding raster statistics into polygons Classification 12

42 Clustering Is clustering evident? High/Low Clustering (Getis-Ord General G) Cluster and Outlier Analysis (Anselin Local Morans I) 13

43 Clustering Is clustering evident? High/Low Clustering (Getis-Ord General G) Cluster and Outlier Analysis (Anselin Local Morans I) 13

44 Clustering Is clustering evident? High/Low Clustering (Getis-Ord General G) Cluster and Outlier Analysis (Anselin Local Morans I) 13

45 Clustering Is clustering evident? High/Low Clustering (Getis-Ord General G) Cluster and Outlier Analysis (Anselin Local Morans I) 13

46 Clustering Is clustering evident? High/Low Clustering (Getis-Ord General G) Cluster and Outlier Analysis (Anselin Local Morans I) 13

47 Clustering Is clustering evident? High/Low Clustering (Getis-Ord General G) Cluster and Outlier Analysis (Anselin Local Morans I) Statistically significant hot spots, cold spots and spatial outliers (Cluster and outlier analysis tool documentation) Indicate whether the apparent similarity (a spatial clustering of either high or low values) or dissimilarity (a spatial outlier) is more pronounced than one would expect in a random distribution. (ESRI 10.1 Tool help) 14

48 Clustering Is clustering evident? High/Low Clustering (Getis-Ord General G) Cluster and Outlier Analysis (Anselin Local Morans I) Statistically significant hot spots, cold spots and spatial outliers (Cluster and outlier analysis tool documentation) Indicate whether the apparent similarity (a spatial clustering of either high or low values) or dissimilarity (a spatial outlier) is more pronounced than one would expect in a random distribution. (ESRI 10.1 Tool help) 14

49 Clustering Is clustering evident? High/Low Clustering (Getis-Ord General G) Cluster and Outlier Analysis (Anselin Local Morans I) Statistically significant hot spots, cold spots and spatial outliers (Cluster and outlier analysis tool documentation) Indicate whether the apparent similarity (a spatial clustering of either high or low values) or dissimilarity (a spatial outlier) is more pronounced than one would expect in a random distribution. (ESRI 10.1 Tool help) 14

50 Clustering gravity clusters What do the gravity clusters mean? 15

51 Clustering gravity clusters What do the gravity clusters mean? High Clusters relate to relatively shallow iron rich mineral accumulations and/or high grade metamorphic rocks. 15

52 Clustering gravity clusters What do the gravity clusters mean? High Clusters relate to relatively shallow iron rich mineral accumulations and/or high grade metamorphic rocks. Gravity outliers occur mostly in the southeastern portion of the study area and relate to high density intrusions and/or mineralisation within lower grade metamorphic rocks. 15

53 Clustering gravity clusters What do the gravity clusters mean? High Clusters relate to relatively shallow iron rich mineral accumulations and/or high grade metamorphic rocks. Gravity outliers occur mostly in the southeastern portion of the study area and relate to high density intrusions and/or mineralisation within lower grade metamorphic rocks. Helping redefine the Olympic copper/gold Province. 15

54 Clustering gravity clusters What do the gravity clusters mean? High Clusters relate to relatively shallow iron rich mineral accumulations and/or high grade metamorphic rocks. Gravity outliers occur mostly in the southeastern portion of the study area and relate to high density intrusions and/or mineralisation within lower grade metamorphic rocks. Helping redefine the Olympic copper/gold Province. Helping redefine the Olympic Subdomain 15

55 Clustering gravity clusters What do the gravity clusters mean? High Clusters relate to relatively shallow iron rich mineral accumulations and/or high grade metamorphic rocks. Gravity outliers occur mostly in the southeastern portion of the study area and relate to high density intrusions and/or mineralisation within lower grade metamorphic rocks. Helping redefine the Olympic copper/gold Province. Helping redefine the Olympic Subdomain 15

56 Clustering gravity clusters What do the gravity clusters mean? High Clusters relate to relatively shallow iron rich mineral accumulations and/or high grade metamorphic rocks. Gravity outliers occur mostly in the southeastern portion of the study area and relate to high density intrusions and/or mineralisation within lower grade metamorphic rocks. Helping redefine the Olympic copper/gold Province. Helping redefine the Olympic Subdomain Gravity outliers almost exclusively host known IOCG Occurrences. 15

57 Clustering gravity clusters What do the gravity clusters mean? High Clusters relate to relatively shallow iron rich mineral accumulations and/or high grade metamorphic rocks. Gravity outliers occur mostly in the southeastern portion of the study area and relate to high density intrusions and/or mineralisation within lower grade metamorphic rocks. Helping redefine the Olympic copper/gold Province. Helping redefine the Olympic Subdomain Gravity outliers almost exclusively host known IOCG Occurrences. 15

58 Conclusions Vectorisation has added to the utility of the data Identified known and potential IOCG occurrences May assist with the interpretation of geological or mineralogical domains 16

59 Current and Future plans Continued geological interpretation of clusters and outliers Release of Report Book Expand the vectorised regions Prospectivity modelling Australian Mineral Industry Research Association (AMIRA) Uncover Roadmap Vision: Delivering Australia's major new mines by locating and unlocking future mineral wealth, and positioning Australia as the global leader in exploration beneath post-mineral cover rocks. Moonplain near Coober Pedy Photo Courtesy S Hill 17

60 Thank You Laz Katona Geological Survey of South Australia Minerals and Energy Resources Level 4, 101 Grenfell Street Adelaide, South Australia 5000 GPO Box 320 Adelaide, South Australia 5001 T: E: Laz.Katona@sa.gov.au