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Nickel and Cobalt Mineral Potential in New Zealand

1st May 2018

Patricia Durance, Matthew Hill, Regine Morgenstern, Rose Turnbull, Mark Rattenbury, Rob Smillie, NZP&M

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Key Points

The Ni-Co Mineral Systems Model Mineral system Model for Ni-Co New Zealand Geology and Mineralogy

GNS Science Mineral Potential Modelling Approach Data Sources: Data mining and New Analyses GIS-based Modelling Methods – Standard Approach to Mineral Systems

Ni-Co mineral potential in New Zealand Mineral potential maps for Ni-Co Ni-Co data gaps, knowledge gaps, opportunities, research questions

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(Dulfer et al., 2016).

Mineral System Model for Ni-Co Mineral Potential in New ZealandMagmatic Ni-Cu-(Co) ± PGE

layered intrusion deposit formation1. Magmatic deposits

Stratiform/Stratabound Ni-Cu basal ultramafic parts of Greenstone Belts

(Komatiitic, Dunitic, Picritic) Gabbroic Intrusion or Synorogenic-synvolcanic

2. Structure-related deposits3. Sedimentary deposits

Laterites (weathering)4. Cu-Au-Co Metasedimentary5. Others

Iron oxide-Cu-Au (IOCG)6. Seafloor Manganese nodules and crusts7. PlacerCo is mined as a by-product of Ni-Cu

Deposit types

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New Zealand Geology

1. Magmatic deposits Dunitic Ni-Cu Gabbroic-associated Ni-Cu-(Co)±PGE

2. Structure-related deposits (?)3. Sedimentary deposits

Laterites (weathering)4. Cu-Au-Co Metasedimentary (?)5. Seafloor Manganese nodules and crusts 6. Placer (?)

z

Add Minerals - list

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QMAP

Petlab

REGCHEM

MR4510

Geophysical surveys

Regional Soil Geochemistry surveys

*includes new analyses

Data Sources

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Some data-mining was undertaken for this project to

improve our geochemical and geological databases in

key locations that were known as high-relevant for the

Li, Ni-Co and REE mineralisation in NZ.

Key NZP&M mineral reports (1,811 new data points)

Scientific papers (479 new data points).

Areas of compilation focused on:

• West Coast (Hohonu Ranges, Paparoa Ranges &

Brunner Ranges); Cobb Valley, NW Nelson; Mandamus,

North Canterbury.

There is still more data that could be compiled.

Data Mining

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73 samples analysed at ALS laboratories, Brisbane (90 samples analysed in total; including QAQC)

Multiple techniques used; targeting specific ore and pathfinder elements (different digests; ICP-MS, ICP-AES)

New Targeted Geochemical Analyses

Lithium (23 samples)

Pegmatites (West Coast, Fiordland)

Hydrothermally altered clays/lake sediments (Taupo Volcanic Zone, Coromandel, Auckland, Northland)

REE (24 samples)

Alkaline rocks (Trachytes, granites from West Coast, Fiordland)

Heavy mineral sands (West Coast beaches)

Hydrothermally altered rocks (PaparoaMetamorphic Core Complex; altered rhyolitic clays)

Ni-Co (26 samples)

Ultramafics (Dun Mt, Cobb Igneous Complex, Anita Shear Zone, Hawes Head Ultramafics)

Gabbros and granitoids(NW Nelson, Westland, Fiordland)

Basalts, lamprophyres (Lyttelton volcanics,

Greyschist (Aspiring Lithologic Formation)

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The Modelling ProcessExpert scientists Spatial analysis Mineral potential model

Mapping reviews

Matt

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GIS Techniques in Mineral Potential Modelling

Rock chip sample buffering

Stream sediment catchment analysis

Geochemical knowledge applied to

geology

Soil surveys

Geophysical data

Mineral information (Petlab)

Fault and structural data

Mineral occurrences

Anomalous

No sample

Non-anomalous

Sampled, butnot analysed

Peraluminous

Weakly-Peraluminous

Sampled, butnot analysed

Metaluminous

-4 -2 0 2 4-3.6 -3.2 -2.8 -2.4 -1.6 -1.2 -0.8 -0.4 0.4 0.8 1.2 1.6 2.4 2.8 3.2 3.6

Z score

1E-05

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Model scale 100 x 100 m cells

STREAM SEDIMENTS

ROCK CHIP SAMPLES

GEOCHEMICAL STATISTICSSOIL SEDIMENT SAMPLES

DISTANCE ANALYSIS GEOCHEMICAL ROCK CLASSIFICATION

GEOPHYSICAL DATA

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Combining the Mappable Component Predictive Maps• Knowledge-driven rather than data driven method

• Data is assigned a Fuzzy membership which is an expert assigned weight of how important the data is (positive or negative) to the predictive map.

• Values also reflect the data quality and importance to the mineral system.

• We have used Fuzzy operators to combine the predictive maps; In particular, we used the Fuzzy gamma function– Effectively an averaging process

– It combined the datasets in the best possible way for this study at the NZ-wide scale.

• Missing data values are tracked through the modelling process.

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Mappable components of the Ni-Co mineral system

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Fuzzy Logic Spatial Modelling Process

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gyFl

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apSu

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Mineral Potential Maps for the Magmatic Ni-Co mineral systemResults: High Ni-Co Mineral Potential Areas

Riwaka Igneous Complex

Cobb Igneous Complex

Dun Mountain Ultramafic Group

Patuki Melange

Red Mountain

1 23

Hekeia Gabbro

West Dome4

OtomaIngneousComplex

Nelson and Marlborough

regionsTasman region

South West Coast region

Southland region

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Mineral Potential Maps for the Magmatic Ni-Co mineral system

Gaps: The cooler coloured areas are not necessarily fixed. These results can often be attributed to data gaps: Poorly or under-mapped geology and poorly defined boundaries, contacts

and structures Under-sampled / Not sampled Sampled but not analysed

This leads to holes or gaps in knowledge about the mineral system components New Zealand’s magmatic nickel deposits are under-studied The relationship between cobalt and nickel in ultramafic and mafic rocks

is not well understood. Very little is known about cobalt and the other types of deposits it may be

associated with.

Opportunities: Cobalt can and is coupled with other metals, in other globally established

structure-, sedimentary-, and metasedimentary-related deposit types including: copper, PGEs, iron and manganese, and a host of polymetallic vein-types.

For New Zealand, this presents opportunities to explore for cobalt in other settings such as the Otago schist.

Pounamu Ultramafics

Darren Complex

Otago Schist

DMOBPounamu

Ultramafics

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Missing data• Data challenges:

– Data exists but is not digital

– Data does not exist

– Data is incorrect or not correctly attributed

• Understanding our missing

data in modelling process.

• Filling in the most important

data gaps to increase our

knowledge of mineral

potential.

Analysed

No sample

Sampled, butnot analysed

Unsampledintrusion

AnalysedSample

Sampled, butnot analysed

SOLUTION: Data compilations

SOLUTION: Sample surveys

SOLUTION: Database design & QA/QC

-4 -2 0 2 4-3.6 -3.2 -2.8 -2.4 -1.6 -1.2 -0.8 -0.4 0.4 0.8 1.2 1.6 2.4 2.8 3.2 3.6

Z score

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0.1

1

10

100

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ent a

ssay PPB

PPM

STREAM SEDIMENTSROCK CHIP SAMPLES

GEOCHEMICAL ROCK CLASSIFICATION

GEOCHEMICAL STATISTICS