GNS Science

Aggregate opportunity modelling:

Understanding our resource and

planning for the future

Matthew Hill – GNS ScienceAusIMM NZ Branch Conference | 18 September 2018

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GNS Science – New Zealand’s Geological Survey

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Project Genesis

• New Zealand’s economy is demanding large quantities of

industrial minerals and aggregate for building materials and

agriculture.

• Identifying aggregate resources in close proximity to their end

use is essential for on-going urban development and

construction.

• The cost of transporting aggregate doubles every 30 km so

local sources are critical.

• Managing the future demand requirements and planning for

aggregate supply is essential.

• We identified a need by the aggregate and extractives

industry to locate areas of aggregate potential for future

resources.

Source:

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New Zealand Aggregates• Domestic production of aggregate is approximately 31 Mt

per year* with 75% consumed in the North Island.

• A wide range of rock types are quarried as aggregate

material which include greywacke, sandstone, basalt,

andesite and limestone.

• In situ hard rock and alluvial gravel deposits are located

around New Zealand.

• Long-distance transport is generally uneconomic so

sources of aggregate are required near the end users.

• This model builds on previous aggregate research by

GNS Science (Christie et al., 2000) and the University of

Auckland (Black, 2009 & 2014).

Figure above from Christie et al. (2000)* Chilton (2018)

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Aggregate Resource Opportunity Modelling

• This project has used a mineral potential model

approach for aggregate resources in NZ.

• Instead of restricting it to geological criteria as in a

typical mineral systems approach we have

included:

– Environmental restrictions;

– Areas of high aggregate demand;

– Required supporting infrastructure; and,

– Consideration of cultural sensitivity.

• When these factors are combined with our

geological knowledge, a map showing the best

opportunities for aggregate extraction is produced.

Image by L. Homer

New Zealand Geologyand Current Aggregate

Quarries

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This study joins a family of 8 national-scale mineral potential models being developed by GNS

Base metals(Cu-Pb-Sn-Zn)

Aggregate

LithiumRare Earth Elements

Intrusion-related (Au-W-Bi-Mo-Sn)

Epithermal Au-Ag

Orogenic Au-W-Sb

Ni-Co-Cr-PGE

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The Modelling ProcessExpert scientists Spatial analysis Mineral potential model

Mapping reviews

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• National Geological Map (QMAP)

• DOC

• Ministry for the Environment

• Landcare Research

• Geophysical surveys

• LINZ, NZTA, NZP&M

• Satellite data

Data Sources

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Aggregate Rock Sources• Our model includes a map of in situ source rocks from

the current 2018 QMAP database.

• It also includes data from the Ministry of Environment to locate large rivers and geological mapping from QMAP to locate river alluvium.

• Geophysical data was used in this source map to locate buried basalt or other highly magnetic deposits.

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• The resulting map shows areas where there are ideal rock types for aggregate resources.

• These different hard rock and alluvial rocks are weighted in the modelling process.

• The model does not take into account any engineering qualities of the rock.

• The model also does not include lithological differentiation; e.g. argillite-rich vs. sandstone-rich zones in the greywacke.

Magnetic rocks

Rivers & alluvium

Lithology

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Environmental Restrictions

• Our model uses maps of restricted land for mining

activities such as:

– Schedule 4 land (see the Crown Minerals Act)

– Department of Conservation public conservation areas

– And, the Threatened Environment Classification; i.e.

areas of significant native vegetation.

• The model takes into account the different land

access restrictions with appropriate weightings in the

model.

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• This map shows the main areas of environmental land

categories.

• Each area is weighted in the final model with Schedule 4

land the most restricted, DOC land less restricted, areas of

native vegetation possible restriction, and other areas that

have easier access.

• Future models will benefit by including data from local and

regional councils on parkland and reserves.

LCDB classes

Threatened environments

DOC land

Schedule 4 land

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Demand Requirements

• It is important that future quarry locations are near the

end-users and demand markets.

• Our model identifies several key end-users:

– Residential areas

– NZTA major projects

– Major highways

– And, local road networks

• Areas where there are existing quarries fulfilling the

market are down-weighted in the model.

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• Areas of high demand are located along the main

road networks and near populated areas.

• Data is weighted in the model by the distance from

these features.

• The model will be improved by using more data from

the NZTA on their future major infrastructure projects

and by using estimates of future city aggregate

requirements around New Zealand.

Existing quarries

Highways and multi-lane roads

Sealed road networks

Metalled road networks

Residential areas

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Infrastructure

• Development of a quarry is ideally close to existing

infrastructure.

• These include facilities such as:

– Large roads

– The railway network

– Transmission lines for power

– And labour market supply.

• The slope of the surrounding terrain is also considered.

Processing sites that can be fed aggregate material from

above and those that do not have large overburden are

considered more favourable.

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• Fortunately, many of the key areas of infrastructure are

already near areas of high demand.

• Each layer in the model is weighted based on a distance

classification.

• Information on the load-bearing capability of roads

(suitability for use by aggregate carrying trucks) will be

useful in future models.

Major road

Railway network

Transmission lines

Gradient

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Cultural Sensitivity• As with all extractive activities consideration for the local

cultural sensitivity is important.

• It is unfortunate that the demand for aggregate from

urban areas and the urban populations’ sensitivity to

mining often clashes and places limitations on

operators.

• We include population density and cultural artefacts in

our model to take this into consideration.

• Also included are land classification indexes from

satellite data to help identify the current land use.

• Existing quarry density is also a good indicator of

mining sensitivity.

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• This map highlights areas for suitable quarrying

activities where there is likely reduced cultural

sensitivity.

• Map classifications are weighted differently in the

model based on their importance.

• Future maps could include areas of Iwi interest and

places of high scenic or tourism value.

Population density

Cultural artifacts

Quarry density

Cadastral parcel size

LCDB classes

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Combining the 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.

• This modelling uses very simple mathematics so is therefore

easily understood.

• More complex modelling methods are available and could be

used in future studies.

Major road

Railway network

Transmission lines

Existing quarries

Highways and multi-lane roads

Sealed road networks

Metalled road networks

Residential areas

LCDB Classes (vegetation)

Threatened environments

DOC land

Schedule 4 land

Magnetic rocks

Rivers & alluvium

Lithology

Population density

LEVEL 1

Fuzzy gamma

LEVEL 2 LEVEL 3

Source MaterialMap

Mineral Potential

Model

Fuzzy gamma

Fuzzy gamma

Fuzzy AND

Fuzzy OR

Fuzzy gamma

Cultural artifacts

Quarry density

Cadastral parcel size

Gradient

LCDB classes (land use)

Environmental Map

Demand Requirements Map

Infrastructure Map

Cultural Sensitivity Map

AGG

REG

ATE

MO

DEL

LIN

G P

RO

CES

S TR

EE

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Aggregate Resource Opportunity Model

• Our model uses 21 maps to identify criteria suitable and not suitable for quarry development.

• Each of the components in the maps is expertly weighted to reflect the importance of the mapped area to quarry development.

• These maps are combined into five maps of source material, environmental considerations, demand requirements, infrastructure and cultural sensitivity.

• The five maps are combined into a single mineral potential map to help identify the most suitable locations for future quarries.

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Example of wheremore information isrequired in model.

Additional data that would improve model could include:

• Regional and local council park and reserve areas

• Consideration of land value to Iwi

• Future population expansion predictions

• Major city aggregate consumption forecasting

• Major future NZTA projects

• Rock engineering properties

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FINAL MODEL NO ENVI-MAP LITHOLOGY

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Aggregate Resource Opportunity without Environmental Map

Modelling completed using only source material, demand requirements, infrastructure and cultural sensitivity maps.

FINAL MODEL NO ENVI-MAP

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Summary• We need to protect land at district planning stages and

use our knowledge for future resource management.

• It is important to understand the economic effect of

restricting access to aggregate sources.

• This study delineates areas that warrant more detailed

study and potentially is a catalyst for new industry

exploration.

• It could be improved through additional land use data

and by creating models using advanced rock and

engineering parameters.

• We are working to improve this model through

consultation with end-users, academic researchers and

industry experts.

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I would like to thank:

Tony Christie, Mark Rattenbury, Delia Strong, Fabio Caratori Tontini,

Steve Edbrooke, David Heron, Richard Kellett, Rob Smillie, Bob Brathwaite,

Rose Turnbull, Patti Durance, Regine Morgenstern &

Dave Jennings (GNS Science).

Mike Chilton (Aggregate and Quarry Association) and Heyward Bates

Joey Au, Greg Hollard and Andy O’Loan (NZP&M)

Holcim’s Bombay Quarry, Ridge Road Quarry Ltd, and Winstone Aggregates.

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This research has been supported by the Strategic Science Investment Fund to GNS Science.