1. Kevin D. Box Advisor: Dr. Jay Parish GEOG 596A Second Spring Semester
Multispectral and Surface Sampling approach to Gold Exploration in Marble Bar, Australia
Kevin D. Box
Advisor: Dr. Jay Parish
GEOG 596A
Second Spring Semester

2. General Outline Project Objective Background Methodology
Criteria for economic success
Deposit Type
Deposit Deposition
Area of interest
Methodology
Data
Work flow
Ratios
Potential Exploration Targets
Moving Forward

3. Project Objective
Utilize remote sensing techniques to identify potential gold bearing conglomerates within the Marble Bar Basin.
Actively explore targets, identified from remote sensing, using field work and surface sampling to validate success and failures of remote sensing in exploration.

4. Background Economic Gold Deposits Grade Tons Geometry Depth
Must be high enough to warrant mining
Tons
Must have enough gold to warrant mining
Geometry
Deposit must be large enough to warrant cost of mill and extraction methods
Depth
With excessive depth comes excessive waste and cost
The four combined factors create a formula that is the primary criteria for whether a deposit can economically be mined at a profit. Many deposits do not meet these criteria to be economically profitable.

5. Gold Deposits Disseminated Vein (Lode)
Very fine grained gold dispersed through the rocks. Large deposits and usually low grade but still economically feasible.
Carlin, Nevada
Cripple Creek, Colorado
Homestake, South Dakota
Vein (Lode)
High grade concentration as a result of hydrothermal solutions being forced through faults or fractures. Very high concentrations within a tight space.
Sleeper, Nevada
Mother Lode, California

6. Gold Deposits Placer Paleoplacer
Gold deposition as a result of weathering and being moved by water. These are usually formed with alluvial and beach systems.
California Gold Rush
Klondike, Canada
Nome, Alaska
Paleoplacer
“Old” placers. Old placers that have been fossilized into rock. Deposited in a sheet and can be kilometers long. Gold can be disseminated and crystalline.
Witwatersrand, South Africa
1.5 billion ounces
Over 4km deep

7. Paleoplacer Gold Origin
Multiple Theories –
Placer Model
Occurred during orogenic formation
Hydrothermal Model
Sediments were deposited and fluids were hydrothermally pumped into the sediment seams then compressed to reform as rock
Microbial Model
BUGS!
Gold concentrations in seawater during the time of deposition could have ranged from 4 – 40 ppb (compared to today of 4ppt)
Microbes play a role in exhaling gold from seawater and creating pyrite in the process. Also could explain the formation of the high grade carbon leaders in the Witwatersrand deposit

8. Basin Sediment Deposition
The three theories agree that paleoplacers are sediment deposited.
Trapped Sediments
Sediments Reworked in Streams
Shoreline Sediment Deposition

9. Sediment deposition Gold Bearing Conglomerate(s)
Basement Rocks
Sediment Package
Volcanic
Cover
Gold Bearing Conglomerate(s)
Examples of Gold Bearing Quartz Pebble Conglomerate from diamond drilling
at Nullagine, WA

10. Why Australia? Pilbara Exploration Marble Bar Basin Nullagine Basin
Multiple basins identified in remote regions of Western Australia that contain potential economic sediment hosted paleoplacer gold systems similar to Witwatersrand, South Africa
Nullagine – resource of 421k oz. inferred gold defined in 2012 from initial drilling by Novo Resources Corp. in gold bearing conglomerates
Novo Resources Corp. exploration identified a gold bearing conglomerate on the opposite side of the basin over 1km long with grades in excess of 10 gpt up to 50 gpt at surface.
Marble Bar Basin
Nullagine Basin

11. Marble Bar Basin
Question: Does the Marble Bar Basin hold the same potential as seen at Nullagine in 2012?
Over 175,000hectares (436,000 acres) of land to explore.
Historical mines (alluvial and hard rock) in in the late 1930’s and early 1940’s on the south east flank of basin
Tassie Queen
Just in Time
Comet
Sporadic ground work within interior and flanks shows that favorable conditions exist from stream sediment samples in areas of easy access.
50 km
65 km
Historical
Mining
© Harris Corp, Earthstar Geographics LLC © 2013 Microsoft Corporation

12. Marble Bar Basin Complications 50 km 65 km
Over 175,000hectares (436,000 acres) of land to explore.
Much of the land is only accessible via helicopter, ATV or foot resulting in inadequate modern exploration.
Sporadic ground work has been limited to easy access areas. Very little is known about the vast majority of the basin.
Work in this region is expensive for lodging, food, and salaries
50 km
65 km
Historical
Mining
© Harris Corp, Earthstar Geographics LLC © 2013 Microsoft Corporation

13. Marble Bar Geology
Area covered in volcanic basalt with sediment lenses that have the potential to host gold
Marble Bar Basin is part of the Fortescue Group consisting primarily of Archean rocks with little overlying Tertiary rocks
Volcanic
Cover
Sediment Package
Basement Rocks
1:100k geology map from GSWA (Geological Survey of Western Australia)

14. Marble Bar Geology Characteristics of the target conglomerates
Quartz pebbles and boulders
Matrix is a mixture of silica with clays such as sericite, illite, and smectite
Note: matrix mixture includes kaolinite. However, kaolinite is a common clay remobilized from weathering elements such as wind and water
Low mafic content
Low epidote, chlorite, and amphibole
Low carbonates

15. Remote Sensing Why choose remote sensing?
Proven successful in identifying certain rock types where rocks are exposed
Marble Bar sits in barren dry climate ideal for remote sensing
Inexpensive when using ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) multispectral data
Covers large areas – single tile 60 km²
Contains 14 bands that cover VNIR (Visable Near Infrared), SWIR (Shortwave Infrared) and TIR (Thermal Infrared) spectral ranges.
Spectral bands of SWIR and TIR are useful in identifying clays and silica material
Bands can be combined into ratios based on certain mineral signatures

16. ASTER Spectral Ratios and Minerals
Key spectral signatures of the Marble Bar Basin
SWIR – 6 bands (channels)
Carbonates, Clay, and Mafic
TIR – 5 bands (channels)
Carbonates, Mafic, and Silica/Quartz

17. ASTER Spectral Ratios and Minerals
Spectral Example – Quartz – SiO2
Quartz Rich Rock – B14/B12 (Kalinowski, A., & Oliver, S. , 2004)
Silica Rich Rock – B13/B10
(Kalinowski, A., & Oliver, S. , 2004)
TIR
Band 10
Band 11
Band 12
Band 13
Band 14

18. Issues with ASTER
Broad paint brush complicates supervised classification and choosing regions of interest (ROI)
30m pixel resolution in SWIR
90m pixel resolution in TIR
Line striping or smearing of image
Most common in TIR bands
Mineral spectrums can overlap and cause misidentification
Spectral profile comparisons are complicated
Poor imagery
Cloud cover
Fire within imagery

19. Aster Imagery Workflow
Identify
Area
of Interest
Acquire
Imagery
Layer Stack Tiles
Mosaic Tiles
Experiment
Phase
Create
Individual Ratios
Review
Ratio Results
Band Math
Unsupervised
Classification
Re-work Ratios
Analyze Results
Map Results
Plan
Exploration
Program
Software Used
ENVI – ASTER Processing
ArcGIS - Mapping

20. Aster Ratios – Quartz Rich Rock
Ratio = b14/b12
(Kalinowski, A., & Oliver, S. , 2004)
Highlights areas with quartz rich rocks. This can include sandstones, quartz pebble conglomerates, veins, etc.
© Harris Corp, Earthstar Geographics LLC © 2013 Microsoft Corporation
©METI and NASA 2001

21. Aster Ratios – Silica Ratio = B13/B10
(Kalinowski, A., & Oliver, S. , 2004)
Highlights areas with silica rich rocks and sands. This can include crystalline silica found in the matrix of sandstones, quartz pebble conglomerates, veins, etc.
© Harris Corp, Earthstar Geographics LLC © 2013 Microsoft Corporation
©METI and NASA 2001

22. Aster Ratios – Sericite, Muscovite, Illite, and Smectite
Ratio = (b5+b7)/b6
(Kalinowski, A., & Oliver, S. , 2004)
Highlights clays or soils rich in sericite, muscovite, illite, or smectite.
**Burn areas show in SWIR bands. When analyzing you must be aware of this.
Burn Area
© Harris Corp, Earthstar Geographics LLC © 2013 Microsoft Corporation
©METI and NASA 2001

23. Aster Ratios – Mafic Rocks
Ratio = b12/b13
(Kalinowski, A., & Oliver, S. , 2004)
Highlights mafic rocks such as basalt, dolerite, and gabbro. These are all extrusive or intrusive igneous rocks.
© Harris Corp, Earthstar Geographics LLC © 2013 Microsoft Corporation
©METI and NASA 2001

24. Aster Ratios – Epidote, Chlorite, and Amphibole
Ratio = (b6+b9)/(b7+b8) Highlights areas with minerals that are associated with igneous rocks at Marble Bar.
© Harris Corp, Earthstar Geographics LLC © 2013 Microsoft Corporation
©METI and NASA 2001

25. Aster Ratios – Carbonates
Ratio = B13/B14 Areas that have a high carbonate signature. Most likely remobilized calcite or calcrete.
© Harris Corp, Earthstar Geographics LLC © 2013 Microsoft Corporation
©METI and NASA 2001

26. Aster Ratios – Final Results
Band Math = (R1+R2+R3)-(R4+R5+R6) R1-Quartz Rich Rock R2- Silica R3 – Sericite, Muscovite, Illite, and Smectite R4 – Mafic Rocks R5 – Epidote, Chlorite, and Amphibole R6- Carbonates Highlights show potential Au bearing rocks worthy of follow ups.
© Harris Corp, Earthstar Geographics LLC © 2013 Microsoft Corporation
©METI and NASA 2001

27. Aster Ratios – Final Results with Historic Stream Sediment Data
Historic stream sediment samples collected by multiple parties from 2005 through 2009.
Positives
Anomalous grades or better confirm areas for potential conglomerates
Issues:
Sampling methods unknown
Stream sediment data not distributed evenly
Currently do not have elevation data to perform adequate stream flow analysis
© Harris Corp, Earthstar Geographics LLC © 2013 Microsoft Corporation
©METI and NASA 2001

28. Aster Ratios – Final Results with Stream Sediment Data and Geology
Geology conforms closely with results
Three distinct areas that are part of the Hardy Sandstone unit have different signatures.
© Harris Corp, Earthstar Geographics LLC © 2013 Microsoft Corporation
©METI and NASA 2001

29. Aster Ratios - Targets
Areas Identified from Aster data that show potential conglomerates
Numerous areas are showing linear type features that could be exposed conglomerates
Most importantly ASTER is telling us where not to go
© Harris Corp, Earthstar Geographics LLC © 2013 Microsoft Corporation
©METI and NASA 2001

30. Additional Items or Work
Acquire DEM better than 30m resolution
Stream flow analysis to get a better understanding of the sources for the stream sediment samples
Continue to work with ASTER data throughout project
Ground work will reveal better information on modifying ASTER ratios
Acquire aerial multispectral data for additional analysis
Collect training sites during field work
Better resolution allowing for detailed spectral signature work

31. Time Line of Project Project proposal Refined Project proposal
January
Project proposal
February
Refined Project proposal
March – April
Acquired Imagery
Research Subjects
Analyzed Data
Late April - Early May
Met with team and began field planning
Class presentation
Mid May – July
Field work
ASTER changes and refinements
Mid July – August
Surface samples return
Evaluate results of remote sensing work
Plan Drill Program
October 29-30
Present results of field work at Geological Society of America Annual Meeting, Denver Colorado

32. Acknowledgements Dr. Jay Parish Dr. Quinton Hennigh
Penn State Advisor
Dr. Quinton Hennigh
Novo Resources Corp.
Funding and use of data

33. References
The ASTER L1B data was purchased through the online Data Pool at the Earth Remote Sensing Data Analysis Center (ERSDAC), ( Department of Resources, Energy, and Tourism. (2013) Aster Spectral Bands. Retrieved 29 April 2013 from ASTER - Advanced Spaceborne Thermal Emission and Reflection Radiometer Hennigh, Dr. Quinton. (2013, April 30). Personal Interview Regarding Paleoplacer Deposits and the Witswatersrand Deposit. (K. Box, Interviewer) Kalinowski, A., & Oliver, S. (2004, October). ASTER Mineral Index Processing Manual. Retrieved February 26, 2013, from Australian Government Geoscience Australia: Rajesh, H. M. (2004, June 28). Application of remote sensing and GIS in mineral resource mapping - An overview. Retrieved February 26, 2013, from J-STAGE - Japan Science and Technology Information Aggregator, Electronic: van der Meer, F. D., van der Werff, H. M., van Ruitenbeek, F. J., Hecker, C. A., Bakker, W. H., Noomen, M. F., et al. (2011, August 10). Multi- and Hyperspectral geologic remote sensing: A review. Retrieved March 27, 2013, from University of OULU Dashboard: Agar, B. (n.d.). ASTER Alteration and Mineral Mapping; Las Pampas, Cajamarca, Peru. Retrieved February 26, 2013, from ASTER Altera:

34. Questions?