Regional GIS based exploration targeting studies in data poor environments

Transcription

1 Regional GIS based exploration targeting studies in data poor environments A case study of gold prospectivity mapping in Nigeria Matthew Greentree, Mathieu Lacorde and Bert De Waele

2 Acknowledgements Australian Mines Ltd SRK Consulting (Australasia) Fabio Vergara (ex - SRK) and Jason Beltran (SRK)

3 Background Australian Mines Ltd acquired 65 mineral concessions (total area of 4,374 km 2 ) in northern Nigeria. SRK was engaged to develop a geological framework to support gold exploration in north Nigeria. Compile geological and exploration data Develop a consistent geological interpretation Identify controls on mineralisation Map areas considered prospective (or not) Ranking of targets for future work programs

4 Prediction vs detection Project District Geological framework Direct detection Increased geological understanding and Expenditure Province Tectonic setting and history Continental Geodynamic and lithospheric setting Prediction Hronsky and Groves, 2008

5 Gold in Nigeria Nigeria represents a knowledge gap in our understanding of Precambrian geology of Africa Over the past 20 years West Africa has become significant gold producer (mostly from Ghana, Burkina Faso and Mali) Most gold in West Africa is produced from Archean and Proterozoic rocks (Birimian and Tarkwaian). Nigeria with only limited modern exploration having been carried out represents an opportunity for mineral explorers!

6 Regional Geology Archean ( Ga) high grade metamorphic basement Located between the West African and Congo Cratons referred to as the Togo-Benin-Nigeria (TBN) Shield. Metamorphosed during the Pan-African orogeny at ca. 600 Ma (eg Garba, 2000) with north-south foliation being developed and granites emplaced.

7 Precambrian in West Africa Study Area 279,167km 2

8 Known gold mineralisation Two broad deposits styles of gold mineralisation documented 1. Structurally controlled hosted in schist belts with gold localised in fold axes e.g. Segilola, Birnin Gwari 2. Granite schist contact mineralisation e.g Bin Yauri

9 Mineral system elements Targeting Criteria Schist belts Quartz veins Deposit type Type 1 Type 2 Yes Yes, in contact with granites Mineral System element Source/Pathway/Trap Comment deposits occur within schist belts.. Yes Yes Pathway/Focus hosted within quartz veins. Regional structures Yes Yes Pathway deposits occur within few kilometres from regional structures striking NW to NE. Secondary structures Granite contact isoclinal upright folds Can be adjacent to granites Yes if granite present, Granitemetasedime ntary rock contacts Pathway/Focus Focus / Trap workings Yes Yes Evidence of mineralisation Deposits sit in secondary structures/splays of the main regional structures. Granite-metasedimentary contacts (hornfels?) are prospective for gold (Type 2) Local miners target steep vein hosted and alluvial deposits

10 Data compilation of 1:2 million mapping 52 individual polygon and polyline shape files that make up the geological datasets for Nigeria Numerous topological errors (gaps, overlapping polygons, duplicates etc) poor correlation with geophysics in many places airborne magnetic and radiometric data(~400 m line spacing). Needed re-interpretation and compilation of a revised map

11 Re-interpreted geology 1:2 million scale geological map was used as a guide Geophysics used to characterise rock units TMI and radiometric imagery was used to develop a new interpretation of structures

12 Project area geology 1. Basement gneiss - Archean and Paleoproterozoic protolith ages 2. Schist belts NNW striking Late-Proterozoic sedimentary and volcanic rocks metamorphosed to greenschist-facies, 13 belts are identified in project area 3. Pan-African granites syn- to late tectonic intrusions Neoproterozoic in age ( Ma) - five intrusive types identified

13 Major Structures Maru Fault striking NNE with a dextral movement sense, with over 20 km offset. Kalanghai Fault Strain, inferred from deformation affecting an intrusion exceeds 5 km. Several sub-parallel major shears are interpreted from geophysics extending up to 80 km.

14 Weights of Evidence analysis (WoE) Data driven technique (e.g. Bonham- Carter 1994) Tests spatial relationships between an Evidence layer and a training dataset (n=139) WoE method uses a Bayesian statistical approach to predict the occurrence of events

15 Weights and contrast measures strength of spatial association of evidence layer B to training points W+ > 0 indicates positive association with B present W+ = 0 indicates no association (equal to chance) W+ < 0 indicates negative association with B present W- > 0 indicates positive association with (not B) W- = 0 indicates no association (equal to chance) W- < 0 indicates negative association with (not B) Positive Contrast value (C = W + - W -) Indicates more training points than would be expected due to chance

16 Evidence data types Ordered Distance from a feature with weights calculated cumulatively on successive values All Faults Strike direction N-S, NE-SW, E-W, NW-SE Geological contacts Contact relationship (granite schist, schist)

17 Evidence layers Categorical values assess by category Lithology Age Rock packages

18 1:2 million geology (original) high contrast (C> 0.5) identified in the WoE study from the 1:2 million scale map. (A)N-S striking faults (<20km); (B)NE striking faults; (C) NW striking faults; (D) Geology (Biotite granite, mylonite, slate and rhyolite) and (E) granite margins (<5km)

19 1:2 Million geology SRK interpretation High contrast (C> 0.5) identified in the WoE study from the SRK interpretation. (A) Geology (Pk2 and Pk3 schists and biotite granites); (B) Granite contacts (< 3km); (C) All faults (< 30km) NE striking faults (<17km)

20 Comparison of two models 1:2 million interpretation (SRK) 1:2 million geological mapping (original)

21 Take home message There is abundant free data sources (SRTM, Aster, Landsat, Bing, Google maps etc) Other non geological information (e.g public health records) Develop confidence in your data Re-interpretation (if needed) of existing geological maps Consistent data allows for better analysis and understanding of geology and gold mineralisation Geological frame work important step in focusing exploration activities Important develop testable, unbiased geological and exploration models

22 Questions? Matthew Greentree Keep an eye out for the Special Issue of Natural Resources Research GIS-Based Geochemical Anomaly and Mineral Prospectivity Mapping in June 2017