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Distant off-fault damage and gold mineralization: The impact of rock hetero-geneity

H. Moir, R.J. Lunn, S. Micklethwaite, Z.K. Shipton

PII: S0040-1951(13)00544-1DOI: doi: 10.1016/j.tecto.2013.08.043Reference: TECTO 126045

To appear in: Tectonophysics

Received date: 14 January 2013Revised date: 16 July 2013Accepted date: 31 August 2013

Please cite this article as: Moir, H., Lunn, R.J., Micklethwaite, S., Shipton, Z.K., Distantoff-fault damage and gold mineralization: The impact of rock heterogeneity, Tectono-physics (2013), doi: 10.1016/j.tecto.2013.08.043

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Distant off-fault damage and gold mineralization: The impact of rock heterogeneity

H. Moira(heather.moir@strath.ac.uk), R.J. Lunna(rebecca.lunn@strath.ac.uk), S. Micklethwaiteb

(steven.micklethwaite@uwa.edu.au)and Z. K. Shiptona(zoe.shipton@strath.ac.uk)

a Department of Civil and Environmental Engineering, University of Strathclyde, 107 Rottenrow, Glasgow,

G4 0NG, Scotland

b Centre for Exploration Targeting (M006), School of Earth and Environment, University of Western

Australia, Crawley, WA 6009, Australia

ABSTRACT

Field observations have established that fault-related damage can occur at locations, far from the

principal slip surface, which are well outside the fractured region currently predicted by models of fault

damage. We use a finite element model to simulate fracture initiation due to fault linkage and show how

variations in rock properties allow off-fault damage to develop at surprisingly large distances away from

the main fault. Off-fault damage continues to grow even after two adjacent, closely spaced fault segments

have interacted and linked. We demonstrate this process was important for the formation of fracture-

hosted gold deposits in the Mount Pleasant goldfield, Western Australia. The strength of lithological

contacts also has a significant impact on off-fault damage location and intensity. Our approach may go

some way to explaining the non-intuitive distribution of mineralization in certain mineral systems, as well

as being applicable to predict subsurface fracturing and fluid flow in hydrothermal/geothermal reservoirs.

KEY WORDS

Numerical modelling, fault zone, stepover, gold

1. INTRODUCTION

Within a single lithology, properties can vary due to original deposition mechanisms, weathering and

subtle changes in the original mineral composition, such changes can localize stress and initiate

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fracturing. Sandstones can vary in grain size, degree of micro-fracturing, number and orientation of

deformation bands (Guo et al., 2009). A granite exposure may exhibit changes in mineralogy that will

affect its mechanical properties. Such changes may be on a scale of a few centimeters or several

kilometers, Glazner et al., (2004) suggest that such variation in granitic bodies is common at all scales.

It is now well understood that damage can develop along the full length of a fault, due to the roughness of

the principal slip surface (Griffith et al., 2010), or at specific fault configurations such as tips and

stepovers (Kim et al., 2003). It is widely stated that heterogeneity affects fracture initiation, propagation

and termination (Helgeson and Aydin, 1991; Blair and Cook., 1989; d'Alessio and Martel, 2004; Tang et

al., 2007; Gudmundsson et al., 2010). Previous numerical models investigating the effects of material

heterogeneity have taken one of two approaches. Tang et al., (2000, 2007) simulate fracture evolution

within a rock with an underlying random distribution of mechanical properties, they show that in

heterogeneous samples initial location of micro-fractures is sensitive to local variations in material

properties however once the micro-cracks have evolved into macro-cracks, which occurs well before the

peak stress is reached, these macro-cracks become the dominant heterogeneity within the system and

interact in a predictable way resulting in failure of the specimen. Other authors have modelled joint

evolution in layered sedimentary sequences and shown that propagating fractures can be initiated,

arrested or deflected at lithological boundaries (Helgeson and Aydin, 1991; Bai and Pollard, 2000;

Gudmundsson et al., 2010). What is not well understood is the development of off-fault damage at

substantial distances from the principal slip surface. For example, tip zone damage extends ~0.5 fault

lengths beyond the tip of one fault on the island of Malta (Figure 5 of Kim et al., 2003). Bistacchi et al.,

(2010) found off-fault damage proximal to a contractional jog, where two fault systems intersect in the

Eastern Alps. Similarly, Cochran et al (2009) postulated that long-lived off-fault damage 1.5 km from the

Calico fault, California could be a dynamic effect, however, they did not consider how lithological

variations may be responsible for the same damage.

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Fault damage critically influences the formation of certain types of precious metal resource (Micklethwaite

et al., 2010), the stress state of active fault systems (Faulkner et al., 2006), and the transmission of fluid

through the crust where damage is directly linked to elevated permeability (Odling et al., 2004; Sheldon

and Micklethwaite, 2007; Rowe et al., 2009). Hence, it is important to understand the circumstances

under which it can occur at substantial distances from the fault. Is it possible that mechanical

heterogeneity could be responsible for the development of the distant off-fault damage described by the

authors above?

Here, we apply a novel finite element approach that both calculates the stress and strain fields associated

with fracture networks and simulates the growth and propagation of fractures (Willson et al., 2007). We

model fracture evolution and fault linkage at a stepover cutting variable lithological units. The approach is

applied to a well-constrained case study site; fracture-hosted gold deposits in the Mount Pleasant

goldfield, Australia, associated with a stepover in the Black Flag fault system (Micklethwaite and Cox,

2004, 2006). There are a large number of variables, many of which are interdependent, that effect gold

mineralisation, such as rock chemistry, fluid pH, redox and gold solubility, fluid flux etc. In order to

comprehensively model the full gold mineralisation process one would have to develop a level of

sophistication that is computationally and theoretically unachievable at the moment. Here we only model

the first-order control, which is large-scale rock damage development leading to substantial transient

permeability enhancement (on the scale of our models fluid flow can be considered a second-order

variable). In doing so, we find we can reproduce the known locations of gold deposits, and that changes

in lithological variations enable fault-related fractures to develop at large lateral distances away from the

principal slip surface, even after linkage of the stepover.

2. THE BLACK FLAG FAULT SYSTEM

Gold mineralization along the Black Flag fault is associated with stepover-related damage. The damage

intersects distinct changes in lithology and so represents an ideal case study for the application of our

mechanical model, MOPEDZ. Previous approaches successfully related the distribution of gold

mineralization to stress changes (Micklethwaite and Cox, 2004, 2006) and damage development

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(Sheldon and Micklethwaite, 2007) around the stepover using Coulomb failure stress change calculations

and damage mechanics. However, these studies were unable to explain variations in the distribution of

gold deposits within the damage zone; restricted as they were to treating the Black Flag fault as two

unlinked segments and the host rock as an elastic isotropic medium.

The Black Flag fault is a dextral strike-slip fault, >50 km long, cutting Archean volcano-sedimentary and

intrusive rocks. Mafic to ultramafic lavas are unconformably overlain by volcaniclastic and sedimentary

rocks intruded by a mafic sill and the Liberty granite (Hagemann and Cassidy 2001). The sequence is

deformed into a shallow south-plunging antiform with the granite in its core, surrounded by the mafic sill

and lavas (Figure 1). Here the Black Flag fault forms a right-stepping, hard-linked stepover, ~2 km long

(Micklethwaite and Cox, 2004), associated with a pronounced minima in the along strike displacement

profile (Micklethwaite and Cox, 2004).

Gold deposit location has a skewed spatial distribution relative to the stepover (Figure 1). Deposits are

preferentially developed northwest of the stepover, stretching ~5 km from its midpoint, and importantly

there is a concentration of mineralization around the margin of the Liberty granite (Cassidy and Bennett,

1993). Mineralization is hosted largely by veins linked to short, small displacement faults and shear zones

(e.g. Gebre-Mariam et al., 1993), as well as in the weathering profile derived from underlying veins.

3. COMPUTATIONAL MODELING

To examine the influence of lithology variation on fracture/fault evolution we performed computer

simulations based on the MOPEDZ finite element model (described in Willson et al., 2007; Lunn et al.,

2008). We estimate spatial and temporal fault evolution within a volume of rock with heterogeneous

material properties. Faults are initiated by increasing the applied boundary stress (Figure 2). To achieve a

controlled mechanical failure, displacement boundary conditions are required; load control tends to result

in rapid catastrophic failure, both numerically and in laboratory test rigs, whereas rigs which operate

under displacement control result in reproducible failure patterns. Pre processing using load control on

the boundaries determines the size of the initial step to be used when running under displacement control

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at which point the ratio of �1 to �3 is known. After the first step (in which all 4 boundaries are displaced

and failure is initiated) only the top and bottom boundaries are displaced (the left and right boundaries are

maintained at a fixed load). This gradual displacement is carried out as a series of iterative steps that

allow the fault structure to evolve. The magnitude of the boundary displacement in any one iterative

failure step is controlled such that only a small number (<6) of cells fail in any one step (to maintain

stability of the model).

Once the first fracture failure is initiated, subsequent failures are propagated by increasing the boundary

displacement, while keeping σ3 fixed. In MOPEDZ as an element fails (in either shear or tension) its

material properties are altered (Appendix 1). Although the first failures are triggered by displacement of

the boundaries, the alteration of the material properties of those failed cells causes a change in both the

direction and magnitude of local σ1 and σ3 near to those failures (Lunn et al., 2008). This alteration of the

local stress may be sufficient to trigger additional failures without any further displacement of the model

boundaries. These subsequent failures can be adjacent to previous failures, i.e. representing the

lengthening of a macroscopic fracture, or they can occur in locations that are disconnected from any

previous failure, or they may be further fracturing of the same element or any combination of these. The

σ1 boundaries are only displaced further once the alteration of material properties of the damaged cells no

longer triggers any further spontaneous failures. It is important to note that each element in the mesh

may represent, at a sub–element scale, any number of micro or macroscopic cracks in the field. Details of

this approach are given in Appendix 1. At the scale of these simulations, each element in the finite

element mesh represents an area of approximately 150m x 150m, and could contain any number of

failures at a sub-grid scale.

The authors have previously presented numerical simulations of the linkage of pre-existing faults for

homogeneous rocks and have shown that the style and location of linkage structures, that evolve from a

network of pre-existing fractures/joints, are governed by three key features (Lunn et al., 2009; Moir et al.,

2010):

1. The orientation of the pre-existing fractures to the maximum compressive stress.

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2. The relative geometries of the pre-existing fractures (e.g. right stepping, left stepping).

3. The ratio of the maximum compressive stress, σ1, to the minimum compressive stress, σ3.

Previous results are in agreement with conceptual models and field observations of other researchers

(e.g. Martel, 1990; Peacock and Sanderson, 1995; Crider and pollard, 1998; Crider, 2001; Kim et al.,

2004; Myers and Aydin, 2004; Flodin and Aydin, 2004; Joussineau et al., 2007). Based on a comparison of

the trace of the Black Flag fault with results from Lunn et al., 2009, an initial stress ratio of σ1 = 2σ3 was

selected for all simulations.

In this paper, we fix the governing variables described above (fault orientation, initial fault geometry and

the ratio of principle stresses) and investigate the effect of host rock heterogeneity on the growth of two,

unlinked, overlapping faults. The location of the gold deposits associated with the boundary of the granite

body in Figure 1 suggest that the geometry and location of lithological changes may have an effect on the

location of the off-fault failures. To explore this hypothesis, initial simulations explore fault linkage

adjacent to an idealised circular inclusion with varying mechanical properties within a 400 km² region

(Figure 3a-3d); the initial investigation of a circular inclusion avoids any additional effects related to

geometry, since ‘corners’ or ‘tips’ are well known to cause stress concentrations (Eshelby, 1957, 1959).

Results are compared against a simulation with no inclusion. We then apply the model to the well-studied

Black Flag fault, to explore the influence of lithology changes on the predicted locations of associated

gold deposits (Figures 4 - 6).

4. RESULTS

Simulation results are presented as plots of the norm of the strain tensor (Figure 3). These plots show

more detail than simple fracture damage plots (which just show failure), as they also highlight elements

that are under a high strain but have not yet failed. The strain plots are not appropriate for direct

comparison with field data since all simulations start from an initial condition of zero strain. Strain is

plotted as the Euclidean norm of the strain tensor, which is one of the methods of representing its scalar

magnitude (Mathews and Fink, 2004). Plots show accumulated strain from the start of the simulation (left-

to-right on each of Figures 3(ii) – (iv)). To highlight the evolution of the linkage structure and the initiation

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of any new fractures or faults, three frames are presented from approximately 370 evolutionary steps in

each simulation. All plots illustrated in Figure 3 are for a central area of the modeled domain (Figure 2), to

avoid any effect of the boundaries.

Predicted fracture linkage geometries are replicated for a homogeneous rock with a Young’s modulus of

65MPa (Figure 3a) and are consistent with previous models (Lunn et al., 2009) and field observations

(Myers and Aydin, 2004). Figures 3b and 3c explore the effect on fault propagation of a discrete circular

inclusion within the neighboring host rock. In Figure 3b, a relatively strong inclusion in the host rock close

to the fault linkage zone (e.g. an igneous intrusion) accommodates less strain than the surrounding host

material. This strain contrast is insufficient to cause any fracture damage, however, and the final fault

linkage geometry remains unaffected in comparison to Figure 3a(iv). If the inclusion is weaker (Figure 3c)

such as a salt diapir, the linkage structure initially develops as before. In parallel, the weak inclusion

rapidly accommodates significant strain by comparison to the neighboring host rock. This leads to the

initiation of tensile failures (Figure 3c(iii)) on the boundary of the inclusion, which then propagates parallel

to the main fault trace (Figure 3c(iv)).

Figure 3d explores the effect of smoothing the boundaries of the lithological interface between the

inclusion and the host rock using a linear smoothing function. A gradual change in material properties

could potentially arise from contact metamorphism or a zone of hydrothermal alteration along the

lithological boundary. This effect is created in Figure 3d(i) by smoothly varying the properties of the host

rock with increasing distance from the inclusion. Results in Figure 3d show that the ‘smoothed’ margin

allows a more gradual accommodation of strain perpendicular to the inclusion boundary, and that despite

the properties of the inclusion being the same as those in Figure 3c, failure of the inclusion is now

inhibited.

4.1 The Black Flag Fault System

We simulate fracture/fault evolution in the Black Flag fault system by modeling the linkage of two simple

straight regional fault segments as they link (Figure 4b) across units with material properties appropriate

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to the mapped host rocks shown in Table 1. Initially, as bounding stresses are increased and linkage of

the fault segments occurs, different lithologies accommodate differing amounts of strain (Figures 4c-h).

Fault linkage is then followed by multiple tensile failures on the granite boundary and into the granite,

producing small dilational structures, not connected to the pre-existing faults (Figures 4f-g). These

features begin to link and failures occur within the granite body. Finally, these small structures link, by

propagation of an antithetic shear fault along the granite boundary that connects them all to the main fault

trace (Figure 4h) and tensile failure is also generated on the boundary of the second granite body to the

north. To demonstrate that this final stage of tensile failure on the northern granite boundary is fault-

related (and not simply due to the lithological contrast) the same simulation was run without the fault

present. Without the fault, initial failure is at a different location on the granite boundary (Figure 5b) and is

followed by failure of the Sandstone boundary (Figure 5c), which propagates along the interface (Figure

5d).

A comparison of the full model predictions for linkage of the Black Flag Fault System (Figure 4h) with the

mapped gold deposits in Figure 4a shows a high level of correspondence between the location of the off-

fault gold deposits and the predicted fracturing. Simulations suggest that the mechanical heterogeneity of

the host rocks permits damage to continue to evolve even after linkage of the main fault trace, with

damage developing preferentially along the margin of the Liberty granodiorite and into the granite. At

present the location to the north, which MOPEDZ suggests may be a site for further failure and possible

gold deposits, has not been explored.

To investigate the effect of boundary strength on fracture development, a strip of elements was

introduced between the mafic and volcanic rocks with a Young’s modulus of 90% of the weaker (volcanic)

rock (Figure 1). No information was available in the literature on the strength of these lithological contacts,

so this value is arbitrary. The introduction of this boundary significantly affects fracture geometries (Figure

6a). Even before the main fault linkage structure has fully developed, a zone of fracturing develops along

the weak contact. At the end of the simulation, there are no failures on the granite boundary. In contrast,

when a similarly weak boundary is introduced around the granite bodies, significantly more failures are

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predicted on that boundary (Figure 6b). However, it should be noted that the first locations to fail are

similar to those in Figure 4f. A comparison of the final fault zone geometries in Figures 4h and Figure 6

demonstrates not only the importance of discrete changes in lithological mechanical properties but also

the major role of the lithological contact itself.

5. DISCUSSION AND CONCLUSIONS

The finite element modeling provides new insights into the development of off-fault damage observed at

large distances from associated master structures (e.g. Kim et al., 2003; Cochran et al., 2009). Abrupt

changes in host rock material properties (e.g. changes in stratigraphy or the presence of intrusive bodies)

allow new structures to form even in preference to the extension of existing ones. In addition, a relatively

small variation in the strength of the contact between different lithologies (10%) has a significant effect on

the initiation and orientation of new structures. The presence of a weak boundary tends to focus failure

along the boundary and inhibit it on distal boundaries. Few, if any, data are available to characterise the

strength of material contacts. The considerable effect that just 10% variation in contact material properties

has on model simulation results demonstrates a clear need for future research to analyse the strength of

material contacts. This could be achieved through laboratory testing of cores that contain lithological

contacts.

Our modeling approach produces results that are consistent with the damage and gold deposit

distribution in the Black Flag fault system. Simulations show two important new predictions: (1) Material

heterogeneity results in continued damage away from the central Black Flag fault trace, even after the

fault segments have hard-linked; (2) Off-fault fracturing occurs at the margin of the granite boundary,

even when the margin itself is not weak. This latter finding explains the concentration of mineralisation

along the margin of the Liberty granite in the Mount Pleasant gold camp. Damage develops into the

granite and is not just confined to its boundary, similar to the distribution of veining and mineralization

observed (e.g. Cassidy and Bennett, 1993). Our results also highlight the boundary of the northern

granite body as a possible additional location for mineralization (Figure 4h).

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In summary, mechanical heterogeneity associated with variations in lithology exerts a first-order control

on fracture/fault evolution. Off-fault damage is able to develop at large distances away from principal slip

surfaces, and that damage continues to evolve even after linkage on adjacent stepovers. This finding has

important implications for prediction of subsurface fracturing both for locating mineral deposits and for

identifying high permeability fractured zones in hydrothermal/geothermal reservoirs.

ACKNOWLEDGMENTS

HM was supported by a University of Strathclyde Faculty of Engineering scholarship. A Royal Society of

Edinburgh Travel Grant enabled the collaboration between SM, ZKS and RL.

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FIGURE CAPTIONS

Figure 1 - Geological map showing the Black Flag fault in Western Australia cutting several lithologies.

Gold mines associated with the fault are also shown.

Figure 2 -Typical initial setup showing the orientation of σ1 and σ3 (simulated far-field stress), directions of

σ1 and σ3 remains constant for all simulations. Gray area is host rock, black is host rock containing faults

(n.b. the pixellated nature of the pre-existing joints is a product of the model). The model boundaries are

under displacement control (size of the initial step determined prior to run with boundaries under load

control), following the initial failure only the top and bottom boundaries are displaced. To avoid

consideration of structures generated at the boundary only results for the central window (within the white

dashed box) are presented. The number of mesh elements varies for the simulations presented in this

paper but are always constrained such that each element in the finite element mesh represents an area

approximately 150m wide (all mesh elements are square).

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Figure 3. Different initial configurations for numerical simulations and plots of the norm of the strain tensor

which give a scalar representation of the magnitude of the strain tensors (the brighter the colour the

higher the strain) showing the change in strain during the evolution of a linkage structure (3 frames from

370).a(i) Initial configuration for homogeneous host rock, Youngs modulus = 65GPa. a(ii) – a(iv)Strain

evolution. b(i) Stronger discrete area is introduced to the simulation. b(ii) – b(iv) The stronger area is

accommodating more strain but not sufficient for failure to occur. c(i) Weaker discrete area is introduced

to the simulation. c(ii) – c(iv) The weak area accommodates more strain than the stronger one and failure

is triggered (initially in tension) on the boundary of the discrete area. d(i) Edges of the discrete area are

smoothed (gradually increasing from Youngs Modulus from 50GPa to 65GPa along with increasing

strength of the other material properties). d(ii) – d(iv) No failures not connected to the pre-existing

features or the linkage structure, failure on the discrete boundary is inhibited.

Figure 4. (a) Map of a jog in the Black Flag fault (repeat of Figure 1), (b) Initial set-up for MOPEDZ

simulation. (c) - (h) Six frames from 400 hundred showing the linkage structure evolution. Different

lithological units can be seen to accommodate differing amounts of strain. Initial fractures in tension on

the granite boundary later develop into shear failure. The locations of these fractures (not physically

connected to the pre-existing fractures or the linkage structure) have a similar location to the gold mines

highlighted in (a). A location highlighted on the more northerly granite exposure (h) may be a new

prospect for finding more gold deposits.

Figure 5 - Black Flag simulation with no pre-existing faults. Prior to predicted failure each unit is

exhibiting different strain response (a). Initial predicted failure location on the granite boundary (b) never

failed in previous simulation (Figure 4). The next iteration of MOPEDZ predicts a failure on the Sandstone

boundary (c), this failure begins to propagate along the boundary (d).

Figure 6 - Final frame of simulations with weak boundaries. (a) Weak boundary between mafics and

volcanics. n.b. no failures on the granite boundary. (b) Weak granite boundary, fails in the same location

as Figure 4, but more intensely.

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Table 1 – Material properties used during the simul ations.

Rock Type Mafics Sandstone Volcanics Granite Pre-existing Fractures

Young’s Modulus (GPa)

80 50 70 60 5

Poissons’s ratio 0.25 0.2 0.2 0.2 0.4 Shear strength (MPa) 174 108 152 130 10.8 Coefficient of friction 0.6 0.6 0.6 0.6 0.06

Tensile strength (MPa) 13.3 8.3 11.7 10 0.83

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Fig. 1

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Homogeneous Young's Modulus (65GP a)

σ1

σ1

σ3 (right)

Boundaries of finite element model (displacement control)

Area of model presented in results

Pre-existing faults

2D finite element mesh with properties of the host rock

20km

(top)

(bottom)

Fig. 2

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Fig. 3

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Fig. 4

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Fig. 5

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Fig. 6

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Highlights

(1) Mechanical heterogeneity exerts first-order control on fracture/fault evolution

(2) Off-fault damage can develop at large distances from principal slip surfaces

(3) Damage continues to evolve even after linkage on adjacent stepovers