Prospectivity mapping for orogenic gold in South-East Greenland

Transcription

1 Prospectivity mapping for orogenic gold in South-East Greenland Björn H. Heincke & Bo Møller Stensgaard Presented by Kristine Thrane Geological Survey of Denmark and Greenland Danish Ministry of Climate, Energy and Building

2 What is prospectivity mapping? Carranza (2009): descriptions, representations or predicitions about an indirectly observable and complex real-world-system via (quantitative) analysis of relevant data. In practice: Integration of various geoscience data to narrow the potential areas of deposits for a specific mineral system. Our prospectivity model for orogenic Au (Following approach from Joly et al. 2013): - Based on mineral system approach - Transfer relevant geoscience information into spatial maps - Use fuzzy logic analysis in an interference network - Knowledge-driven

3 Method STEP 1: Choose/develop a mineral system approach. Mineral system approach is a general framework that is based on an understanding of all critical geological, physical and chemical processes that are required to develop economic deposits for a specific mineral system. Critical processes for orogenic gold: (Wyborn et al., 1994, McCuaig et al., 2010) - Source : Au accumulation in the upper mantle - Pathways : Fluid flow through the crust - Physical Traps/Throttle : Fluids throttled and focused in areas of enhanced permeability - Chemical Scrubber : Hydrothermal mineralization and alteration of Au

4 Method STEP 2: Find representatives for critical processes Processes are inferred from observed geological features (targeting elements) Critical processes and their representations for an orogenic Au system Targeting elements are rarely directly measurable but are estimated from the responses of geoscience data (proxies) as spatial maps (evidential maps) From McCuaig et al., 2010

5 Method Step 3: Fuzzification of evidential maps by using membership functions. Functions are estimated by priori expert knowledge. Step 4: Using fuzzy operators in an interference network to combine all evidential maps in a meaningful logic to receive prospectivity maps. From Joly et al., 2013

6 Investigation area of South-East Greenland Tasiilaq Region Au samples from the Ujarassiorit program ~ Ma Aappaluttoq Volcanism, sedimentation, TTG intrusion ~2020 Ma Metadiabase dikes ~ Ma sedimentation, Ammassalik Intrusive Complex - AIC, From arc signatures Petersen & Thomsen, No in-situ Au deposits found ~ Ma Collisional orogeny - But: 1) several gold-bearing samples from public hunt-for-mineral programs 2) stream sediment samples with elevated concentrations of gold and gold-pathfinder elements ~1600 Ma Granite, diorite, gabbro intrusions

7 Investigation area of South-East Greenland Skjoldungen Region ~ 2825 Ma Undivided mafic, ultramafic rocks, paragneiss? ~ Ma TTG intrusions SAP ~ Ma Granulite facies ~ Ma Skjoldungen Alkaline Province (SAP) + other syenite intrusions ~2700 Ma Amphibolite facies, syntectonic granite intrusions Ma Shear zones, retrograde greenschist facies

8 Special challenges for applying a mineral mapping approach 1) Rather thin strip of non-ice covered land that is intersected by fjords non-uniform data coverage for many datasets; quality of evidential maps is affected by interpolation 2) Extreme topography variations some evidential maps are biased (e.g. mapping of faults in airborne geophysics) 3) Lack of known mineral occurrences limits the validation of the results Inland ice Stream sediment samples Elevations ASTER data and geological mapping is limited to the ice-free area

9 Application of the mineral mapping approach Used evidential maps: - Source : 3 (from regional magnetic & gravity and geological maps) - Pathways : 3 (from airborne magnetics and geological maps) - Physical trap : 3 (from geological maps and airborne magnetics) - Chemical Trap : 15 (stream sediments, ASTER satellite data and geological maps)

10 Application of the mineral mapping approach Data sets Geological information (from digital geological map): Type of targeting elements/proxies: Structural information: - Structural complexity ( Physical Trap ) - Intersections of structures with lithologies ( Physical Trap ) Targeting element Structural complexity : Lineaments/structures Evidential map: Density of structures Fuzzy evidential map: Fuzzy scores from 0 to 1 Fuzzification using membership functions

11 Application of the mineral mapping approach Data sets Geological information (from digital geological map) Type of targeting elements/ proxies: Lithological information: Supracrustal rock units - Intrusions as magmatic input ( Source ) - Chemically favorable host rock units for Au mineralisation (e.g. marble) ( Chemical Trap ) - etc. Digital geological map Stensgaard et. al. (2016) Intrusions - Structures, lineaments, faults - Geological units

12 Application of the mineral mapping approach Data sets Geophysics: Regional scale: Circum Arctic Mapping Project: Magnetic (CAMP-M) and Gravity (CAMP-G) compilations (Gaina et al., 2011) District scale: AEROMAG surveys from 2012 and 2013 (Rasmussen et al., 2013; Riisager & Rasmussen, 2013) Gravity: CAMP-G Magnetic: CAMP-M

13 Application of the mineral mapping approach Data sets Geophysics: Type of targeting elements/proxies: - Regional faults ( Source ) - Secondary faults and lineaments ( Pathways ) - Lineament intersections ( Physical Trap ) Targeting element/proxy 2nd order lineaments Evidential map: Distances from faults Fuzzy evidential map: Fuzzy scores from 0 to 1

14 Application of the mineral mapping approach Data sets Remote sensing ASTER data: NASA webpage Multispectral satellite system collecting 14 bands in the visible near infrared, shortwave infrared and thermal infrared (TIR) - Bands in the TIR are sensitive to the mineral composition - Spatial resolution in the TIR is 90 m Mineral indices that indicate favorable geologic units for Au mineralisations: - Carbonate Index - Quartz Index - Mafic Index used for Chemical Scrubber Evidential Fuzzy evidential map - map Natural neighbor - - Natural Kriging interpolation neighbor - - interpolation -

15 Application of the mineral mapping approach Data sets Stream sediment geochemistry: - Au, As, Bi, W, Cs, Mo, Sb and Ni/Mg ratio - Au: Direct indicator - As, Bi, W, Cs, Mo, Sb and Ni/Mg ratio: Indicative/pathfinder for gold mineralisation (All used for Chemical Scrubber ) Evidential Fuzzy evidential map - map Kriging - Kriging - - Distribution of sample location is sparse and increases uncertainties in evidential maps Cs As Mo

16 Application of the mineral mapping approach intermediate maps Source Pathways Intermediate fuzzy maps associated with the individual critical processes: - Combination of intermediate maps using fuzzy operators results in the final prospectivity maps. Physical Trap Geochemical Trap Made a lot of tests where we left out different information (e.g. Au stream sediments, all stream sediments, )

17 Prospectivity maps & their validation Using natural kriging for neighbor interpolation for of most maps Stream sediment samples with: >20 ppb ~190 ppb Robust model Little affected by individual maps!! No deposits Evaluation by using stream sediment samples >20 ppb Au Limits/inaccuracies: - Integrative effect by size of catchment areas - Uneven spatial distribution of sample locations - May be spatially shifted - No simple correlations with deposits

18 Interpretation Fuzzy score > 0.85 I: Tasiilaq Region with Ammassalik Intrusive Complex (AIC) II: Skjoldungen Alkaline Province (SAP) - Thym complex; Skjoldungen Alkaline province NO Au occurrences observed!! - Proterozoic orogeny overprinting Deep Archaean crustal rocks are not favorable for -Au Deep mineralization mantle tapping major structural Current suture prospectivity zones model does not -account Correlations for this with and gold-bearing has to refined rock samples (Petersen&Thomsen, 2014)

19 Conclusions - Despite the limitations associated with the study area, predictionrate curves (correlated with stream sediments) indicate that the resulting prospectivity maps are meaningful. - Final prospectivity maps appear stable independent of the use of individual maps. - In the Tasiilaq area, a higher potential for unrecognized Au occurrences is in agreement with conclusions from other studies. - But: The predicted high potential for Au in the Skjoldungen area is unlikely, because deep crustal rocks dominate here.