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Presented:

Date:

Location:

© SRK Consulting (UK) Ltd 2011. All rights reserved.

Deposit Geology and Structure

Paul Stenhouse

31/03/2014

Minex Central Asia Forum, Astana, Kazakhstan

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What is structural geology?

Structural geology is the analysis of geological features formed or affected

by deformation of the Earth’s crust

• There is no scale or time limits implied in this definition, so structural geology

can include everything from recent exhumation joints to Archean orogenic belts.

• Structural geology includes regional tectonics, understanding the geometries of

geological bodies, fracturing and fluid flow.

• Geological structures and deposit geometry influence a number of potential

issues relating to geotechnics and hydrogeology.

Structural geology is not geotechnics

Photo courtesy of I. Gilbertson Photo courtesy of GNS Science

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Why is structural geology important?

• Structural features such as faults, shear zones and lithological contacts

can form weaknesses in the rock mass.

• Large-scale structures are often the major control on stability in

competent rocks

Pit wall failures along structures

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Why is structural geology important? • Faults can be both conduits and barriers to water flow.

• Some faults can compartmentalise fluids, localising zones of increased

fluid pressure and potentially driving rock failure.

• Some faults are major fluid conduits, allowing ingress of fluid into the pit

or underground.

• The affect of water ingress can vary from a minor inconvenience to a

major production issue e.g. Cigar Lake.

Groundwater ingress along faults

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Palabora Mine: Initiation of underground caving below pit

Triggers further

redistribution of strain

adjacent to the Mica

fault.

Time-dependent fracturing of rock

bridges eventually causes parallel

structures to fail

Why is structural geology important?

Caving undercut the

Mica fault – critical!

Getting this wrong costs money

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Why is structural geology important?

Identification of structures is critical

Slip on fault intersecting rock crusher Mine workings create stress

concentration on faults

Mine3D - Mine Modeling Pty Ltd

• By removing rock during mining operations stress is focused on the

remaining rock mass and on the contained structures

• Stress concentrations on a critically stressed structure may result in fault

slip (mining induced earthquakes)

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Resource geology models vs. geotechnical/

hydrogeological models

How are they different?

• Resource geologists typically only consider structures that have a

significant effect on mineralisation. Many of which are early and/or

healed.

• Late, low-displacement faults are often not material to a resource but

associated fracturing can be very important for geotechnics and

hydrogeology.

• Some resource geologists will only model the ore without considering

the distribution of waste lithologies and what effect they may have on

issues such as geotechnics, hydrogeology and acid rock drainage.

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Geological modelling: Data required

Generally, the more datasets you use the more robust the model is.

Possible data sources include:

• Geological mapping

• Drillhole logging (lithology, RQD, recovery, mag-sus etc.)

• Drilling notes (water hits, mud loss etc.)

• Remote sensing and geophysics (magnetics)

• Structural measurements from oriented drill core or televiewer logs

• Drill core photos

• Grade data, particularly where grade control data is available

• Microseismic data (typically only in operations)

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Steps in building a waste model

1. Collate available data

2. Review regional/tectonic setting and any regional datasets to

understand the geological context of the project

3. Use mapping and any geophysical or remote sensing imagery to

establish contacts and major structures

4. Check lithological logging codes are appropriate and consistent.

Modify as necessary

5. Link surface mapping to drillhole intercepts to develop 3D contact

surfaces. Use cross-sections if available.

6. Look for offsets or changes in the orientation of a surface (contour if

necessary) to define major faults and fold axes. These should be

verified using core photos.

7. Interpolate any physical properties if required.

This list is not exhaustive and needs to be modified depending on geological setting and available data

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Iron Ore: Geological modelling

Initial understanding:

• Stratiform iron ore deposit with

excellent outcrop of the ore

units but poor waste lithology

outcrop.

• Large drilling database, but

with problems related to

inconsistent lithology logging

and core orientation errors.

A brief interpretation of satellite imagery was completed, followed by ground-truthing of the satellite interpretation and previous mapping.

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Iron Ore: Lithologies

• The original lithological logging

was simplified down to 5

geotechnical units based on a

waste/ore subdivisions and

geotechnical characteristics

• Contacts for each domain were

modelled in 3D using surface and

drillhole data.

• Banding in the BIF and footwall

gneiss was not as significant an

issue as expected, due to

extensive recrystallisation and

small-scale folding.

• A quartzite domain in the

immediate footwall of the ore was

identified as a key unit due to its

position and increased fracturing.

Fractured quartzite

Recrystallised BIF

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Iron ore: Folding

Section through simplified lithological model

Footwall quartzite

Ore

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Iron Ore: Folding

• The synformal geometry of the deposit means that pit walls are likely to be sub-parallel to layering.

• The impact of folding on slope stability can vary depending on a range of variables, including fold geometry, scale, vergence and plunge.

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Iron Ore: Domaining

• The folded geometry meant

that the deposit had to be

divided into 3 separate

domains prior to geotechnical

analysis.

• Bedding dip decreases as the

fold hinge is approached. So

vertical changes in bedding

and pre-fold fractures also

need to be considered.

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Iron Ore: Faulting

• During the modelling

process a major fault was

identified.

• This fault was based on

multiple datasets,

including offset of

contacts in the 3D model,

a major lineament in the

satellite imagery and

faulting in core photos.

• All other faults are low-

displacement and don’t

affect the large-scale

geometry of the deposit.

Offset stratigraphy In 3D model

Drill core from broad fault/shear zone

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Alteration modelling in Porphyry Cu deposits

Argillic alteration data

Leapfrog high Argillic isoshellsArgillic domain (very weak)

BayugoBoyangan

Bayugo

Bayugo

Boyangan

• Geological modelling and domaining needs to be relevant to the deposit. • Lithology may not be the primary control on variations in geotechnical/ hydrogeology characteristics. • The same approach is still applicable to alteration modelling.

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Steps in building a fault model

This combines faults from the geological model with faults that were not

captured in the geological model (i.e. low displacement faults).

1. Identify the dominant structural trends in the area. Possible data sources

include geophysics, remote sensing, geological maps and research

papers.

2. Try and match this with structural data collected from oriented core.

3. Log brittle faulting. Data should be collected on fault rocks, thickness,

associated fracturing etc. This can be supplemented with data from

geotechnical logs e.g. RQD, recovery, fractures per metre.

4. Import data from the geological model, fault logging and relevant

structural measurements into 3D software.

5. Try to model continuous faulted zones. Start with the largest, highest

confidence faults and progressively build the model to include as much

detail as is reasonable with the available data.

6. Ensure all faults have cross-cutting relationships

7. Change faults from surfaces to volumes using drillhole intercepts or true

thickness data.

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Orogenic Au: Fault modelling

Initial Understanding:

• Structurally controlled Au deposit

• Mineralised structures are healed

• No outcrop

• Host gneiss is very competent and low porosity so structures are a key

control on geotechnical and hydrogeological properties.

Typical drill core:

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Orogenic Au: Lineaments The first step was to quickly assess the large-scale structure using

regional geology maps, geophysics and a Lidar topographic survey

Regional Magnetics Project-scale topography

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Orogenic Au: Photo logging

• No detailed fault logging was

available.

• Recovery and RQD were

unreliable.

• Therefore, all diamond holes

were logged for faults using

high quality core photos.

Faulted Intervals

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Orogenic Au: 3D modelling

• Modelling identified zones of

faulting that traversed the

proposed pit. However, no

continuous slip surfaces could

be identified.

• This is common in low

displacement faults that have

reactivated early structures

and has important implications

for geotech and hydrogeology.

• A median surface was

modelled in lieu of a

continuous slip surface.

Initial fault interpretation

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Orogenic Au

• The fault envelope was wider

than individual damage zones,

so simplified domains were

created based on the

maximum width of the faulted

envelope.

• In addition to the model, it is

also useful to summarise fault

attributes in a table format.

Fault ID

Intercepts Confidence Min Thickness (m)

Max thickness (m)

Median thickness (m)

Visible Gouge

Asymmetric Damage

Fracture Intensity

Subsidiary Faults (+/10m)

Comments

Fault 1 6 2 0.7 7.7 2.2 No No Low to moderate

Yes Fault not identified in 2 of the 6 intercepts.

Fault 2 15 4 0.5 10.1 2.8 Common Variable High to moderate

Yes Increased background fracture spacing.

Fault 3 18 5 3.1 62.0 13.0 Common West side Low to moderate

Yes Maximum possibly related to fault intersection.

Fault 4 8 3 2.5 10.6 6.9 Common Variable Low to moderate

Yes

Fault 5 11 4 10.2 19.7 16.8 No data No data No data No data No core photos, logging and mapping only

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Variability in faults

Faults have complex traces, both along-strike and down-dip

Fomm ir-rih Bay, SW Malta

• Normal fault

•Displacement = 0.9 cm • Offset and overlapping segments • Straight and curved segments • Lenses of more intense fracturing • Varying thickness • Varying fault rocks e.g. gouge, cataclasite, breccia

This complexity makes 3D modelling of faults difficult and has important implications for the distribution of fracturing and permeability

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Variability in faults: Fracture distribution

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0 0.2 0.4 0.6 0.8 1

Miqtub branch-line

Other branch-lines (9) Apical lenses

Fault

zone

Breached relay

Cu

mu

lati

ve

fra

cti

on

of

fra

ctu

re d

en

sit

y

Cumulative fraction of fault trace

Assume uniform aperture

‘Standard’ FZ:

85% fault trace length

23% total fracture density

Irregularities:

77% total fracture density

15% fault trace length

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Fault scaling: Displacement vs. length

Displacement vs. fault trace length

earthquake dimensions

0.01m 0.1m 1.0m 10m 100m 1km 10km 100km103km 104km

100km

10km

1km

100m

10m

1m

0.1m

0.01m

0.001m

1000km

Length (m)

•Data from all available sources

indicates that there is any relationship

between the maximum displacement

and the lengths of a fault.

•Given that many of the faults we deal

with are low displacement, this places

obvious limits on lateral continuity.

Source: Fault Analysis Group

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Conclusions

• Structural geology impacts on both geotech and hydrogeology,

so the level of structural understanding on a project should grow

in parallel with the understanding in other disciplines.

• Fundamental (basic) geological observations combined with

conceptual structural models are required to characterise the

distribution of geotechnical/hydrogeological properties.

• A deposit-scale geology model, focussed on features that are

relevant to the project, should form a framework for all

geotechnical and hydrogeology studies.

• Faults are extremely complex. All technical disciplines need to

understand the implications and inherent limitations of any fault

model that has been produced.

• Only through the integration of 3D structural geology with

geotechnical/hydrogeological models, will mining risk be more

reliably understood and managed.