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BRUCE CRAVEN
March, 2014
www.sgc.com.au
Introduction
SGC in the Remote Sensing World
• In remote sensing terms, SGC are predominantly data processers and interpreters
Magnetics, radiometrics, gravity, electromagnetics (EM) and DTM
• SGC commonly processes and uses non‐geophysical data, including remote sensing, but rarely undertakes detailed interpretations of RS datasets • Our preference is to work in collaboration with the established specialists for detailed imagery interpretations
• SGC provides geophysical perspectives to specialist imagery interpretations
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Introduction (cont.)
My Background
• Dominantly exploration background, including near and in mine
• Mixture of geological and geophysical roles
• Interpretation objective is geologically driven and coherent interpretations, using a variety of datasets; whatever is available and useful
Geophysical & Remote Sensing Methods
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MAGNETICS
Ground, airborne, down hole or satellite surveys. GRAVITY
Ground, airborne, down hole or satellite surveys. RADIOMETRICS
Ground, airborne or down hole surveys.
EM
Ground; airborne; down hole. Resistivity mapping is becoming more common at all mapping/exploration scales.
ELECTRICAL (e.g. I.P.) Ground; down hole; hole to hole
SEISMIC
Ground, marine, hole to hole
• DIGITAL TERRAIN
From photography, radar, remote sensing, routine (modern) airborne geophysical surveys. • REMOTE SENSING Airborne, satellite
• RADAR
Ground, down hole, airborne or satellite
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PRINCIPLES AND PURPOSE OF INTERPRETATION
• Understand the nature of the data, its information content and limitations
• What can be derived from a data set? Can it help you?
• Understand how the data / information is presented at all stages
• Start and end at first principles and ‘facts’ (i.e. what is known)
• Maintain the integrity of the original data
• Portray the information so that it conveys (where possible)
• Structure & lithology inferred from the dataset
• The factual / control information
• Should be geologically logical, coherent and understandable
• Final presentation is geologically meaningful and recognizable
Hamersley Basin
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Major iron ore province
Well known stratigraphy
Poorly understood, complex structure
Difficult access; rugged terrain
Good exposure, but laterite / alluvial cover common
Very high contrast, complex magnetic environment
1:25,000 scale imagery interpretation (Nick Lockett)
1:100,000 scale magnetics‐radiometrics interpretation 3
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Geology GSWA 1:250,000
Landsat 742
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Ternary Radiometrics (API)
RTP Aeromagnetics (open file)
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RTP Aeromagnetics (API)
Digital Terrain Model (SRTM)
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Hamersley Basin: A Closer Look
• Comparison of 1:25,000 imagery and 1:100,000 magnetics interpretations
• Low resolution section of the magnetic dataset
• Widespread remanent magnetism
• Quite different information contents
RTP Aeromagnetics (API)
Landsat 742
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SGC 1:100,000 Magnetics Interpretation
Nick Lockett 1:25,000 Satellite Imagery
Interpretation
East African Rift: Kilosa-Kilombero
• Petroleum exploration in modern, active sedimentary basins within the East African rift system
• Widespread coeval volcanics • Significant Archaean‐Palaeoproterozoic basement influence on internal basin development
• Good geology‐topography correlation, but does not reflect basin depths
• 1970’s low resolution magnetics & uneven gravity coverage. • Satellite gravity 8
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Landsat 742
Digital Terrain Model
(SRTM)
RTP 1VD Aeromagnetics
Satellite Residual Gravity
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SGC 1:500,000 Magnetics
Interpretation
Baker 1:250,000 Satellite Imagery
Interpretation
Chile: Salar Grande
• Early stage porphyry / epithermal / IOCG copper‐gold & uranium play; coastal ranges, northern Chile
• Limited pre‐existing exploration or geological control
• 100m line spacing aeromagnetics‐radiometrics flown
• Field checking and mapping, using magnetics, basic satellite imagery and DTM data
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RTP Aeromagnetics
RTP Aeromagnetics
Potassium
Radiometrics
Magnetics
Interpretation
Ternary Radiometrics
Landsat 742
Digital Terrain Model
(SRTM)
Interpreted Geology
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Peru: Southern Coast
• Coastal Ranges IOCG / Porphyry Copper province
• Recent (block) faulting trends (north‐easterly) in DTM / Landsat. Variable thickness post mineralization cover
• Jurassic and older faulting and alteration trends are clearly easterly and north‐westerly in the magnetics
• Vertical throw on recent block faults can be >300m (from DTM)
Landsat 742
Digital Terrain Model
(SRTM)
RTP Aeromagnetics
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Papua New Guinea: Yandera
• Complex porphyry copper‐gold system within Bismarck Complex, near Bundi Fault Zone
• Rugged, high rainfall, jungle covered area
• Heavy vegetation cover limits the effectiveness of satellite imagery
• Aeromagnetics and radiometrics (to a lesser extent) show reasonable correlation with major geological elements and add detail Landsat 543
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RTP Aeromagnetics
Ternary Radiometrics
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Digital Terrain Model
1:250,000 Geology
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New Zealand: Otago
• Prospective Mesozoic meta‐pelitic terrane north‐west of Macraes gold camp (flat dipping Macraes Shear) • Good exposure of prospective lithologies but obscured significant Cenozoic sediments and volcanics
• Glass Earth airborne EM and magnetics show geological complexity and structure that is not readily evident in the geology, Landsat and DTM data
Landsat 742
Digital Elevation Model (Glass Earth DIGHEM)
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RTP Aeromagnetics
Airborne EM 8000Hz (Glass Earth DIGHEM)
Qmap 1:250,000 Merged
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Closing Comments
• Commonly available or routinely collected geophysical datasets can complement and enhance remote sensing datasets and interpretations
• Magnetics, gravity and EM datasets can generate useful information in areas where remote sensing datasets struggle; e.g. through cover and or heavy vegetation
• Magnetics, gravity and EM datasets provide subsurface (3D) as well as near/at surface information ‐ increasingly important • Combination of remote sensing and geophysical datasets is likely to optimize the overall interpretation and outcome
AVERAGE DEPTH FOR GREENFIELD AND BROWNFIELD
DISCOVERIES
Source: MinEx Consulting © August 2012
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Acknowledgements
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API (Australian Premium Investments); Hamersley Basin
Swala Energy; East African Rift
Hot Chili Ltd; Salar Grande
Marengo Mining Ltd; Yandera
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