The Use of Geoinformatics in Mineral Exploration and Exploitation

Marguerite WalshMSc Geographical Information Systems and Remote Sensing18th March 2015

Van der Meer, et al, 2014

Introduction Benefits geologists, scientists and

exploration managers Mineral exploration and exploitation is

a huge source of employment around the world

Main focus on remote sensing

History of Remote Sensing in Geology Graham Hunt & John Salisbury

(1970s/1980s) Based on laboratory spectral analysis of

minerals and rocks

Geologic Remote Sensing Mineral exploration Hyperspectral geology Mineral resource mapping Seismic activity

Dr. F. van der Meer

Remote Sensing (1)

AdvantagesClassification for

mappingTarget identification“bird’s eye view” – can cover

large areas quickly Can see any patterns or trends

– differences in tone, texture and structure

Remote Sensing (2)

IssueCloud cover Features on the

ground can be hidden beneath vegetation

Sub surface features

SolutionRadarRadar

Radio Echo Sounding

Satellite sensors1000s of options.Archive of dataTemporal

resolutionOrbit of satelliteSpectral

resolutionSpatial

resolutionCost

Spectral Signatures (1)

• Multiple bands that show what the human eye cannot see• Visible, near infrared,

short-wave infrared and thermal infraredhttp://www.akitarescueoftulsa.com/label-the-

electromagnetic-wave-diagram/

“Many minerals have unique and diagnostic spectral properties, and features such as the band centre, strength, shape, and width are used to identify species with high confidence” (Calvin et al, 2015)

Spectral Signatures (2)

USGS Spectral Library

• Multispectral imaging and thematic mapping• Reflection data and absorption properties

• Photogeology

• USGS Spectral Library

“Spectrally Active” minerals can be mapped with Remote Sensing

Environment of formation

Main spectrally active alteration minerals

High sulphidation epithermal

Alunite, pyrophyllite, dickite, kaolinite, diaspore, zunyite, smectite, illite

Low sulphidation epithermal

Sericite, illite, smectite, chlorite, cabonate

Porphyry: Cu, Cu-Au Biotite, anhydrite, chlorite, sericite, pyrophyllite, zeolite, smectite, canbonate, tourmaline

Carlin-type Illite, dickite, kaolinite

Volcanogenic massive sulphide

Sericite, chlorite, chloritoid, carbonates, anhydrite, gypsum, amphiobole

Archean Lode Gold Carbonate, talc, tremolite, muscovite, paragonite

Calcic skarn Garnet, clinopyroxene, wollastonite, actinlite

Retrograde skarn Calcite, chlorite, hematite, illite

Magnesium skarn Forsterite, serpentine-tak, magnetite, calcite

Van der Meer, et al, 2014.

Landsat (1)

“Landsat represents the world's longest continuously acquired collection of space-based moderate-resolution land remote sensing data. ” (USGS, 2013)

Operational 1972-present

U.S.G.S., 2014.

Landsat (2)

Joint project of the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA)

Data every 16/18 days11 BandsResolution 30-60mFree imagesEasily accessible(U.S.G.S., 2012)

Case Study 1: USGS National Map of Surficial Mineralogy

• Mapping exposed surface mineral groups• 3 applications:

• undiscovered mineral deposits • environmental effects associated with mining and • unmined, hydrothermally-altered rocks

• Done using:• 180 Landsat scenes and• 1630 ASTER scenes

Case Study 1: USGS National Map of Surficial Mineralogy

• Already done for the western part of the US – extending eastwards

• More detailed and accurate mineral and vegetation maps

• Active & abandoned mining districts

• Done using:• ASTER• (AVIRIS)• HyMap or• SpecTIR

• An algorithm was developed to automatically analyse Landsat 8 imagery

Rockwell, 2013

Case Study 1: USGS National Map of Surficial Mineralogy

This data is available as GIS shapefiles to add into ArcMap

Rockwell, 2013

ASTER

The “work horse” for geologic Remote Sensing (van der Meer, 2014).

Mapping of surface mineralogy ASTER band ratios as proxies14 different wavelengths

Spectral signatures of different minerals shown through 9 ASTER spectral bands(Beiranvand Pour & Hashim, 2012)

ASTER spectral signatures

• ASTER has 5 thermal bands – different outcrops of minerals can be identified due to differences in specific heat capacity

• Algorithms to extract the spectral information

Case Study 2: ASTER & Detecting areas of high-potential gold mineralization Hydrothermal alteration zones

(gold and copper)Methods: band ratio & mineral

extraction methodField mapping was also

undertaken Gabr et al, 2010

Study Site: Abu-Marawat, the Eastern Desert of Egypt

• Abu Marawat Deposit is a gold rich, polymetallic deposit

• Historical area of gold and copper mining dating back to the time of Pharaohs and Pyramids

Alexander Nubia Inc., 2011

Spectral Signatures

Gabr et al, 2010

Result:ASTER band ratio image

The white colour represents mineralized parts of the alteration zone – potential for significant, undiscovered gold ore

Case Study 3: ASTER & Morenci Mine, Arizona

ASTER (15m) Satellite Image of Morenci Mine, Arizona - USA

Satellite Imaging Corporation, 2001-2014.

ASTER Summary

Issues of cloud cover and vegetation

Each terrain is different and so algorithms and ratios will vary

Do not look at the ASTER data in isolation

Integration with other geoinformatics technologiesGIS data layers

– to get a better understanding of the site◦Topographical◦Geophysical◦Geochemical data

Adding layers on transport, relief, elevation etc

Some of the GIS data layers used by the USGS in

their geological studieshttp://woodshole.er.usgs.gov/project-pages/

longislandsound/data/gis.html

Case Study 4: GIS analyses and satellite data in northern Chile to improve exploration for copper mineral deposits

• La Escondida mining District

• Atacama Desert, Northern Chile

• The highest producing copper mine in the world.

• Also produces some silver and gold

La Escondida mine(left) 1975 before extraction began(right) 2008 with huge expansionUNEP, CATHALAC., 2015.

Data integration and analyses within a geographic information system

Different thematic layers of the database in the vicinity of La Escondida mining district.

Upper layers represent optimized Landsat data derived from band ratioing, principal component analysis (PCA), and inverse PCA.

Lower layers represent topographic data, lithology, and aeromagnetic data.

Bottom layer is one of the calculated favourability maps.

Ott et al., 2006.

The End ResultFavourability map of altered rocks at La Escondida mining district

Case Study 5: Geothermal Resources in Nevada

ASTER imageryUsed both remote sensing and

geographical information systemsThermal properties as surface indicators

of geothermal resourcesSpectral data taken in the field using a

spectrometer to validate resultsIntegration into GIS databases with

other relevant geologic information“to make comparisons and site assessments.”

However blind geothermal systems may have very little or no surface expression at all

Thermal Anomalies at the Brady’s Site, Fernley, Nevada.

The End ResultMineral Map of 4 different areas

• Successful in Nevada where there is sparse vegetation cover

• In vegetated areas – LiDAR may be more appropriate

• UAVs with imaging spectrometers will also help map small scale features

FurgoFurgo is one of the leading

companies when it comes to mining projects.

Mining Development and Management – Fugro supports mine information systems by delivering accurate geospatial knowledge over the entire lifecycle of a mine.

aerial surveying data - baseline data for feasibility studies, mine mapping and permitting, stock pile calculations and volumes, rehabilitation and waste dump mapping.

Regional geochemical and geological surveys

Airborne geophysics

Satellite monitoring and mapping optical radar Multispectral Mapping Site selection Emergency response

Aerial mapping Geophysics Photography LiDAR Management and mapping

The Future UAVs – Unmanned Aerial Vehicles

• Unmanned Aerial Systems will improve the ability to map small-scale surface features associated with geothermal systems in remote, rugged or vegetated terrain.(Calvin et al, 2015)

• Can also be used to monitor mines for maintenance and efficient business management.

• As with all UAV applications there may be different issues with standards, ethics and regulations.

On the left is an aerial view of a mine in the USA captured using the INTEGRATOR UAV pictured above on the right

The Future: Sentinel-2

E.S.A., n.d.

Sentinel-2 Specifications

Sentinel-2A and Sentinel-2B 2A - April 2015 2B - 1st half of 2016

To ensure the continuity of SPOT, Landsat and ASTER imagery

High resolution optical imagerySpectral resolution: 13bandsSpatial resolution: 10m, 20m and

60mTemporal resolution: 5days

Sentinel-2 Methods

• Band ratios serve as proxies to derive different minerals• A dataset was simulated from a

reflectance-at-surface airborne hyperspectral image• Simulation studies

Case Study 6:Cabo de Gata, SE Spain

A volcanic field which consists of calc-alkaline volcanic rocks (andesites & rhyolites) (Van der Meer, et al,

2014.)

Case study to test the potential of Sentinel-2

Cabo de Gato Volcanic fieldMetamorphic minerals

Process

Input (airborne

hyperspectral data from the HyMAP sensor)

Geometric correction

Spatial subset

Spectral resampling

Spatial degradatio

n

Comparison of

scatterplots

Output (Scatter plots)

Scatterplots between simulated Sentinel-2 and simulated ASTER bands

CABO DE GATAA. Photograph of the study siteB. Interpretation of the geology in the areaC. 3D perspective with a natural colour composite image derived from

HyMAPD. HyMAP band ratio image showing hydrothermal alteration mineralogy.

Van der Meer, et al, 2014.

Van der Meer, et al, 2014.

The End ResultBand Ratio Products• Simulated Sentinel-2• Simulated ASTER• Real ASTER

Geological & Mineral Interpretation

Van der Meer, et al, 2014.

Results

Ratio mapping Scatterplots Good correspondence between the

ASTER and Sentinel-2 ratios for ferric/ferrous iron, ferric oxides, ferrous silicates, gossan and NDVI

Geologic mapping The simulated Sentinel-2 was visually

compared to a geological map & mineral maps.

Simulated image products demonstrate a good correspondence between ASTER and Sentinel-2 VNIR and SWIR bands

Conclusion

Issues• Cloud cover and vegetationReproducibilityExpense – software and

datasets / raw imagesThe gap between academia and

industryFurther study into use of radar in

mineral geology

Conclusion

Positives• Geoinformatics – many

applications and uses• Long and reliable history• So many different dimensions

and components can be considered at once

• UAVs and Sentinel-2 in the future

Bibliography• Alexander Nubia Inc, 2011. Abu Marawat Gold-Copper. Available online at: http://

www.alexandernubia.com/cms/pages/13 [Accessed 28 February 2015 ]• Beiranvand Pour,A., & Hashim, M., 2012, The application of ASTER remote

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• Furgo., 2015. EXPERTISE>OUR>SERVICES SURVEY>AERIAL MAPPING>Mining Development and Management. Available online at: http://www.fugro.com/our-expertise/our-services/survey/aerial-mapping#tabbed2 [Accessed 28 February 2015 ]

• Gabr,S.,Ghulam,A., & Kusky,T., 2010. Detecting areas of high-potential gold mineralization using ASTER data, Ore Geology Reviews, Vol.38, P.59–69.

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Bibliography• Satellite Imaging Corporation, 2001-2014. ASTER Satellite Image of Morenci

Mine in Arizona. Available online at: http://www.satimagingcorp.com/gallery/more-imagery/aster/aster-arizona-morenci-mine-es/ [Accessed 02 February 2015 ]

• Rockwell, B.W. and Bonham, L.C., 2013, USGS National Map of Surficial Mineralogy: U.S. Geological Survey Online Map Resource. Available online at: http://cmerwebmap.cr.usgs.gov/usminmap.html [Accessed 14 March 2015]

• Rockwell, B.W., 2013, Automated mapping of mineral groups and green vegetation from Landsat Thematic Mapper imagery with an example from the San Juan Mountains, Colorado: U.S. Geological Survey Scientific Investigations Map 3252, 25-p. pamphlet, 1 map sheet, scale 1:325,000, http://pubs.usgs.gov/sim/3252/

• UNEP, CATHALAC., 2015. La Escondida, Chile. Latin America and the Caribbean – Atlas of Our Changing Environment. Available online at: http://www.cathalac.org/lac_atlas/index.php?option=com_content&view=article&id=22:la-escondida-chile&catid=1:casos&Itemid=5 [Accessed 02 February 2015 ]

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