Tectonophysics 608 (2013) 461–467

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Tectonophysics

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

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

a Department of Civil and Environmental Engineering, University of Strathclyde, 107 Rottenrow, Glasgow G4 0NG, Scotland, United Kingdomb Centre for Exploration Targeting (M006), School of Earth and Environment, University of Western Australia, Crawley, WA 6009, Australia

⁎ Corresponding author.E-mail addresses: heather.moir@strath.ac.uk (H. Moir)

(R.J. Lunn), steven.micklethwaite@uwa.edu.au (S. Mickletzoe.shipton@strath.ac.uk (Z.K. Shipton).

0040-1951/$ – see front matter © 2013 Elsevier B.V. All rihttp://dx.doi.org/10.1016/j.tecto.2013.08.043

a b s t r a c t

a r t i c l e i n f o

Article history:Received 14 January 2013Received in revised form 16 July 2013Accepted 31 August 2013Available online 9 September 2013

Keywords:Numerical modelingFault zoneStepoverGold

Field observations have established that fault-related damage can occur at locations, far from the principal slipsurface, which are well outside the fractured region currently predicted by models of fault damage. We use a fi-nite elementmodel to simulate fracture initiation due to fault linkage and showhowvariations in rock propertiesallow off-fault damage to develop at surprisingly large distances away from themain fault. Off-fault damage con-tinues to grow even after two adjacent, closely spaced fault segments have interacted and linked. We demon-strate that this process was important for the formation of fracture-hosted gold deposits in the Mount Pleasantgoldfield,WesternAustralia. The strength of lithological contacts also has a significant impact on off-fault damagelocation and intensity. Our approach may go some way to explaining the non-intuitive distribution of minerali-zation in certain mineral systems, as well as being applicable to predict subsurface fracturing and fluid flow inhydrothermal/geothermal reservoirs.

© 2013 Elsevier B.V. All rights reserved.

1. Introduction

Within a single lithology, properties can vary due to original deposi-tionmechanisms,weathering and subtle changes in the originalmineralcomposition, such changes can localize stress and initiate fracturing.Sandstones can vary in grain size, degree of micro-fracturing, numberand orientation of deformation bands (Guo et al., 2009). A granite expo-sure may exhibit changes in mineralogy that will affect its mechanicalproperties. Such changes may be on a scale of a few centimeters orseveral kilometers, Glazner et al. (2004) suggest that such variation ingranitic bodies is common at all scales.

It is now well understood that damage can develop along the fulllength of a fault, due to the roughness of the principal slip surface(Griffith et al., 2010), or at specific fault configurations such as tipsand stepovers (Kim et al., 2003). It is widely stated that heterogeneityaffects fracture initiation, propagation and termination (Blair and Cook,1998; d'Alessio and Martel, 2004; Gudmundsson et al., 2010; Helgesonand Aydin, 1991; Tang et al., 2007). Previous numerical models investi-gating the effects of material heterogeneity have taken one of two ap-proaches. Tang et al. (2000, 2007) simulate fracture evolution within arock 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 howeveronce the micro-cracks have evolved into macro-cracks, which occurs

, rebecca.lunn@strath.ac.ukhwaite),

ghts reserved.

well before the peak stress is reached, these macro-cracks become thedominant heterogeneity within the system and interact in a predictableway resulting in failure of the specimen. Other authors have modeledjoint evolution in layered sedimentary sequences and shown that propa-gating fractures can be initiated, arrested or deflected at lithologicalboundaries (Bai and Pollard, 2000; Gudmundsson et al., 2010; Helgesonand Aydin, 1991). What is not well understood is the development ofoff-fault damage at substantial distances from the principal slip surface.For example, tip zone damage extends ~0.5 fault lengths beyond the tipof one fault on the island of Malta (Fig. 5 of Kim et al., 2003). Bistacchiet 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 damage1.5 km from the Calico fault, California could be a dynamic effect,however, they did not consider how lithological variations may beresponsible for the same damage.

Fault damage critically influences the formation of certain types ofprecious metal resource (Micklethwaite et al., 2010), the stress stateof active fault systems (Faulkner et al., 2006), and the transmission offluid through the crust where damage is directly linked to elevatedpermeability (Odling et al., 2004; Rowe et al., 2009; Sheldon andMicklethwaite, 2007). Hence, it is important to understand the cir-cumstances under which it can occur at substantial distances fromthe fault. Is it possible that mechanical heterogeneity could be responsi-ble for the development of the distant off-fault damage described by theauthors above?

Here, we apply a novel finite element approach that both calculatesthe stress and strain fields associated with fracture networks and simu-lates the growth and propagation of fractures (Willson et al., 2007). Wemodel fracture evolution and fault linkage at a stepover cutting variable

σ1 2D finite element mesh with properties of the host

20km

(top)

462 H. Moir et al. / Tectonophysics 608 (2013) 461–467

lithological units. The approach is applied to a well-constrained casestudy site; fracture-hosted gold deposits in the Mount Pleasant gold-field, Australia, associated with a stepover in the Black Flag faultsystem (Micklethwaite and Cox, 2004, 2006). There are a large num-ber of variables, many of which are interdependent, that effect goldmineralization, such as rock chemistry, fluid pH, redox and goldsolubility, and fluid flux. In order to comprehensively model thefull gold mineralization process one would have to develop a levelof sophistication that is computationally and theoretically unachievableat the moment. Here we only model the first-order control, which islarge-scale rock damage development leading to substantial transientpermeability enhancement (on the scale of our models fluid flow canbe considered a second-order variable). In doing so, we find that wecan reproduce the known locations of gold deposits, and that changesin lithological variations enable fault-related fractures to develop atlarge lateral distances away from the principal slip surface, even afterlinkage of the stepover.

2. The Black Flag fault system

Gold mineralization along the Black Flag fault is associated withstepover-related damage. The damage intersects distinct changesin lithology and so represents an ideal case study for the applica-tion of our mechanical model, MOPEDZ. Previous approaches suc-cessfully related the distribution of gold mineralization to stresschanges (Micklethwaite and Cox, 2004, 2006) and damage devel-opment (Sheldon and Micklethwaite, 2007) around the stepoverusing Coulomb failure stress change calculations and damage me-chanics. However, these studies were unable to explain variationsin the distribution of gold deposits within the damage zone; re-stricted as they were to treating the Black Flag fault as two unlinkedsegments and the host rock as an elastic isotropic medium.

The Black Flag fault is a dextral strike-slip fault, N50 km long, cuttingArchean volcano-sedimentary and intrusive rocks. Mafic to ultramaficlavas are unconformably overlain by volcaniclastic and sedimentaryrocks intruded by a mafic sill and the Liberty granite (Hagemannand Cassidy, 2001). The sequence is deformed into a shallow south-plunging antiform with the granite in its core, surrounded by the maficsill and lavas (Fig. 1). Here the Black Flag fault forms a right-stepping,hard-linked stepover, ~2 km long (Micklethwaite and Cox, 2004), associ-ated with a pronounced minima in the along strike displacement profile(Micklethwaite and Cox, 2004).

Gold deposit location has a skewed spatial distribution relative tothe stepover (Fig. 1). Deposits are preferentially developed northwest

0km 10km

Sandstone Granite

Volcanics Mafics

Fig. 1. Geological map showing the Black Flag fault in Western Australia cutting severallithologies. Gold mines associated with the fault are also shown.

of the stepover, stretching ~5 km from its midpoint, and importantlythere is a concentration of mineralization around themargin of the Lib-erty granite (Cassidy and Bennett, 1993).Mineralization is hosted large-ly by veins linked to short, small displacement faults and shear zones(e.g. Gebre-Mariam et al., 1993), as well as in the weathering profilederived from underlying veins.

3. Computational modeling

To examine the influence of lithology variation on fracture/fault evo-lutionwe performed computer simulations based on theMOPEDZ finiteelement model (described in Lunn et al., 2008;Willson et al., 2007).Weestimate spatial and temporal fault evolution within a volume of rockwith heterogeneous material properties. Faults are initiated by increas-ing the applied boundary stress (Fig. 2). To achieve a controlled me-chanical failure, displacement boundary conditions are required; loadcontrol tends to result in rapid catastrophic failure, both numericallyand in laboratory test rigs, whereas rigs which operate under displace-ment control result in reproducible failure patterns. Pre-processingusing load control on the boundaries determines the size of the initialstep to be used when running under displacement control at whichpoint the ratio of σ1 to σ3 is known. After the first step (in which all 4boundaries are displaced and failure is initiated) only the top andbottom boundaries are displaced (the left and right boundaries aremaintained at a fixed load). This gradual displacement is carried out asa series of iterative steps that allow the fault structure to evolve. Themagnitude of the boundary displacement in any one iterative failurestep is controlled such that only a small number (b6) of cells fail inany one step (to maintain stability of the model).

Once the first fracture failure is initiated, subsequent failures arepropagated by increasing the boundary displacement, while keepingσ3 fixed. In MOPEDZ as an element fails (in either shear or tension) itsmaterial properties are altered (Appendix 1). Although the first failuresare triggered by displacement of the boundaries, the alteration of thematerial properties of those failed cells causes a change in both thedirection and the magnitude of local σ1 and σ3 near to those failures

σ1

σ3(right)

σ3(left)

Boundaries of finite element model (displacement control)

Area of model presented in results

Pre-existing faults

rock

(bottom)

Fig. 2. Typical initial setup showing the orientation of σ1 and σ3 (simulated far-fieldstress), directions of σ1 and σ3 remain constant for all simulations. Gray area is hostrock and 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 displacementcontrol (size of the initial step determined prior to run with boundaries under loadcontrol), 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 centralwindow (within the white dashed box) are presented. The number of mesh elementsvaries for the simulations presented in this paper but are always constrained such thateach element in the finite element mesh represents an area approximately 150 m wide(all mesh elements are square).

463H. Moir et al. / Tectonophysics 608 (2013) 461–467

(Lunn et al., 2008). This alteration of the local stress may be sufficient totrigger additional failures without any further displacement of themodel boundaries. These subsequent failures can be adjacent to previ-ous failures, i.e. representing the lengthening of a macroscopic fracture,or they can occur in locations that are disconnected from any previousfailure, or they may be further fracturing of the same element or anycombination of these. The σ1 boundaries are only displaced furtheronce the alteration ofmaterial properties of the damaged cells no longertriggers any further spontaneous failures. It is important to note thateach element in the mesh may represent, at a sub-element scale, anynumber of micro- or macroscopic cracks in the field. Details of this ap-proach are given in Appendix 1. At the scale of these simulations, eachelement in the finite elementmesh represents an area of approximately150 m × 150 m, and could contain any number of failures at a sub-gridscale.

The authors have previously presented numerical simulations of thelinkage of pre-existing faults for homogeneous rocks and have shownthat the style and location of linkage structures, that evolve from a net-work of pre-existing fractures/joints, are governed by three key features(Lunn et al., 2008; Moir et al., 2010):

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

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

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

Previous results are in agreement with conceptual models and fieldobservations of other researchers (e.g. Crider, 2001; Crider and Pollard,1998; de Joussineau et al., 2007; Flodin and Aydin, 2004; Kim et al.,2004; Martel, 1990; Myers and Aydin, 2004; Peacock and Sanderson,1995). Based on a comparison of the trace of the Black Flag fault withresults from Lunn et al. (2008), an initial stress ratio of σ1 = 2σ3 wasselected for all simulations.

In this paper, we fix the governing variables described above (faultorientation, initial fault geometry and the ratio of principle stresses)and investigate the effect of host rock heterogeneity on the growth oftwo, unlinked, overlapping faults. The location of the gold depositsassociated with the boundary of the granite body in Fig. 1 suggeststhat the geometry and location of lithological changes may have aneffect on the location of the off-fault failures. To explore this hypoth-esis, initial simulations explore fault linkage adjacent to an idealizedcircular inclusionwith varyingmechanical properties within a 400 km2

region (Fig. 3a–d); the initial investigation of a circular inclusion avoidsany additional effects related to geometry, since ‘corners’ or ‘tips’ arewell known to cause stress concentrations (Eshelby, 1957, 1959). Re-sults are compared against a simulation with no inclusion. We thenapply the model to the well-studied Black Flag fault, to explore the in-fluence of lithology changes on the predicted locations of associatedgold deposits (Figs. 4–6).

4. Results

Simulation results are presented as plots of the norm of the straintensor (Fig. 3). These plots showmore detail than simple fracture dam-age plots (which just show failure), as they also highlight elements thatare under a high strain but have not yet failed. The strain plots are notappropriate for direct comparison with field data since all simulationsstart from an initial condition of zero strain. Strain is plotted as theEuclidean norm of the strain tensor, which is one of the methods ofrepresenting its scalar magnitude (Mathews and Fink, 2004). Plotsshow accumulated strain from the start of the simulation (left-to-righton each of Fig. 3(ii)–(iv)). To highlight the evolution of the linkagestructure and the initiation of any new fractures or faults, three framesare presented from approximately 370 evolutionary steps in each

simulation. All plots illustrated in Fig. 3 are for a central area of themodeled domain (Fig. 2), to avoid any effect of the boundaries.

Predicted fracture linkage geometries are replicated for a homoge-neous rock with a Young's modulus of 65 MPa (Fig. 3a) and are consis-tent with previous models (Lunn et al., 2008) and field observations(Myers and Aydin, 2004). Fig. 3b and c explores the effect on fault prop-agation of a discrete circular inclusionwithin the neighboring host rock.In Fig. 3b, a relatively strong inclusion in the host rock close to the faultlinkage zone (e.g. an igneous intrusion) accommodates less strain thanthe surrounding host material. This strain contrast is insufficient tocause any fracture damage, however, and the final fault linkage geome-try remains unaffected in comparison to Fig. 3a(iv). If the inclusion isweaker (Fig. 3c) such as a salt diapir, the linkage structure initially de-velops as before. In parallel, the weak inclusion rapidly accommodatessignificant strain by comparison to the neighboring host rock. Thisleads to the initiation of tensile failures (Fig. 3c(iii)) on the boundaryof the inclusion, which then propagates parallel to the main fault trace(Fig. 3c(iv)).

Fig. 3d explores the effect of smoothing the boundaries of the litho-logical interface between the inclusion and the host rock using a linearsmoothing function. A gradual change in material properties could po-tentially arise from contact metamorphism or a zone of hydrothermalalteration along the lithological boundary. This effect is created inFig. 3d(i) by smoothly varying the properties of the host rock withincreasing distance from the inclusion. Results in Fig. 3d show that the‘smoothed’ margin allows a more gradual accommodation of strainperpendicular to the inclusion boundary, and that despite the proper-ties of the inclusion being the same as those in Fig. 3c, failure of theinclusion is now inhibited.

4.1. The Black Flag fault system

We simulate fracture/fault evolution in the Black Flag fault systemby modeling the linkage of two simple straight regional fault segmentsas they link (Fig. 4b) across units with material properties appropriateto themapped host rocks shown in Table 1. Initially, as bounding stress-es are increased and linkage of the fault segments occurs, different li-thologies accommodate differing amounts of strain (Fig. 4c–h).

Fault linkage is then followed by multiple tensile failures on thegranite boundary and into the granite, producing small dilational struc-tures, not connected to the pre-existing faults (Fig. 4f–g). These featuresbegin to link and failures occur within the granite body. Finally, thesesmall structures link, by propagation of an antithetic shear fault alongthe granite boundary that connects them all to the main fault trace(Fig. 4h) and tensile failure is also generated on the boundary of the sec-ond granite body to the north. To demonstrate that this final stage oftensile failure on the northern granite boundary is fault-related (andnot simply due to the lithological contrast) the same simulation wasrun without the fault present. Without the fault, initial failure is at adifferent location on the granite boundary (Fig. 5b) and is followed byfailure of the Sandstone boundary (Fig. 5c), which propagates alongthe interface (Fig. 5d).

A comparison of the full model predictions for linkage of the BlackFlag Fault System (Fig. 4h) with the mapped gold deposits in Fig. 4ashows a high level of correspondence between the location of the off-fault gold deposits and the predicted fracturing. Simulations suggestthat the mechanical heterogeneity of the host rocks permits damageto continue to evolve even after linkage of the main fault trace, withdamage developing preferentially along the margin of the Libertygranodiorite and into the granite. At present the location to the north,which MOPEDZ suggests may be a site for further failure and possiblegold deposits, has not been explored.

To investigate the effect of boundary strength on fracture develop-ment, a strip of elements was introduced between the mafic and volca-nic rocks with a Young's modulus of 90% of the weaker (volcanic) rock(Fig. 1). No information was available in the literature on the strength

Homogeneous Young's Modulus

(65GPa)

Pre-existing faults

Increasing Displacement of σσ1 boundaries

0.02 0.04 0.06 0.08 0.1 0.12

Increasing Strain

Initial failures in tension

You

ngs

Mod

ulus

(G

Pa)

80

75

70

65

60

55

50

a(i) a(ii) a(iii) a(iv)

b(i) b(ii) b(iii) b(iv)

c(ii)c(i) c(iii) c(iv)

d(i) d(ii) d(iii) d(iv)

Fig. 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 (thebrighter the color the higher the strain) showing the change in strain during the evolution of a linkage structure (3 frames from a total of 370). a(i) Initial configuration for homogeneoushost rock, Young's modulus = 65 GPa. a(ii)–a(iv) Strain evolution. b(i) Stronger discrete area is introduced to the simulation. b(ii)–b(iv) The stronger area is accommodatingmore strainbut 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 istriggered (initially in tension) on the boundary of the discrete area. d(i) Edges of the discrete area are smoothed (gradually increasing fromYoung's Modulus from 50 GPa to 65 GPa alongwith 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 isinhibited.

464 H. Moir et al. / Tectonophysics 608 (2013) 461–467

of these lithological contacts, so this value is arbitrary. The introductionof this boundary significantly affects fracture geometries (Fig. 6a). Evenbefore the main fault linkage structure has fully developed, a zone of

fracturing develops along the weak contact. At the end of the simulationthere are no failures on the granite boundary. In contrast, when a similar-ly weak boundary is introduced around the granite bodies, significantly

Sandstone 50 Weakest

Volcanics 60

Granite 70

Mafics 80 Strongest

Young’s Modulus (GPa)

1

1a b

High

Low

0.12

0.1

0.08

0.06

0.04

0.02

Strain

Initial failures in tension Failures in similar

location to gold deposits

New prospect?

c d e

f g h

0km 10km

σσ

σ

Fig. 4. (a) Map of a jog in the Black Flag fault (repeat of Fig. 1), (b) initial set-up for MOPEDZ simulation. (c)–(h) Six frames from a total of 400 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 ofthese 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 onthe more northerly granite exposure (h) may be a new prospect for finding more gold deposits.

465H. Moir et al. / Tectonophysics 608 (2013) 461–467

more failures are predicted on that boundary (Fig. 6b). However, itshould be noted that the first locations to fail are similar to those inFig. 4f. A comparison of the final fault zone geometries in Figs. 4h

2nd failure location

a b

c d

Fig. 5. Black Flag simulation with no pre-existing faults. Prior to predicted failure each unit isboundary (b) that never failed in the previous simulation (Fig. 4). The next iteration of MOPEDthe boundary (d).

and 6 demonstrates not only the importance of discrete changes inlithological mechanical properties but also the major role of thelithological contact itself.

Initial failure

High

Low

0.12

0.1

0.08

0.06

0.04

0.02

Strain

exhibiting a different strain response (a). Initial predicted failure location on the graniteZ predicts a failure on the Sandstone boundary (c), this failure begins to propagate along

Weak boundary

Weak boundary

High

Low

0.12

0.1

0.08

0.06

0.04

0.02

Straina

b

Fig. 6. Final frame of simulations with weak boundaries. (a) Weak boundary betweenmafics and volcanics. n.b. no failures on the granite boundary. (b)Weak granite boundary,fails in the same location as Fig. 4, but more intensely.

466 H. Moir et al. / Tectonophysics 608 (2013) 461–467

5. Discussion and conclusions

The finite elementmodeling provides new insights into the develop-ment of off-fault damage observed at large distances from associatedmaster structures (e.g. Cochran et al., 2009; Kim et al., 2003). Abruptchanges in host rock material properties (e.g. changes in stratigraphyor the presence of intrusive bodies) allow new structures to form evenin preference to the extension of existing ones. In addition, a relativelysmall variation in the strength of the contact between different litholo-gies (10%) has a significant effect on the initiation and orientation ofnew structures. The presence of a weak boundary tends to focus failurealong the boundary and inhibit it on distal boundaries. Few, if any, dataare available to characterize the strength of material contacts. The con-siderable effect that just 10% variation in contactmaterial properties hason model simulation results demonstrates a clear need for futureresearch to analyze the strength of material contacts. This could beachieved through laboratory testing of cores that contain lithologicalcontacts.

Ourmodeling approach produces results that are consistentwith thedamage and gold deposit distribution in the Black Flag fault system.Simulations show two important new predictions: (1) Material hetero-geneity results in continued damage away from the central Black Flag

Table 1Material properties used during the simulations.

Rock type Mafics Sandstone Volcanics Granite Pre-existingfractures

Young's modulus (GPa) 80 50 70 60 5Poisson's ratio 0.25 0.2 0.2 0.2 0.4Shear strength (MPa) 174 108 152 130 10.8Coefficient of friction 0.6 0.6 0.6 0.6 0.06Tensile strength (MPa) 13.3 8.3 11.7 10 0.83

fault trace, even after the fault segments have hard-linked; (2) Off-fault fracturing occurs at the margin of the granite boundary, evenwhen themargin itself is not weak. This latter finding explains the con-centration of mineralization along the margin of the Liberty granite inthe Mount Pleasant gold camp. Damage develops into the granite andis not just confined to its boundary, similar to the distribution of veiningand mineralization observed (e.g. Cassidy and Bennett, 1993). Our re-sults also highlight the boundary of the northern granite body as a pos-sible additional location for mineralization (Fig. 4h).

In summary, mechanical heterogeneity associatedwith variations inlithology exerts a first-order control on fracture/fault evolution. Off-fault damage is able to develop at large distances away from principalslip surfaces, and that damage continues to evolve even after linkageon adjacent stepovers. This finding has important implications for pre-diction of subsurface fracturing both for locating mineral deposits andfor identifying high permeability fractured zones in hydrothermal/geothermal reservoirs.

Acknowledgments

HM was supported by a University of Strathclyde Faculty of Engi-neering scholarship. A Royal Society of Edinburgh Travel Grant enabledthe collaboration between SM, ZKS and RL.

Appendix A. Supplementary data

Supplementary data to this article can be found online at http://dx.doi.org/10.1016/j.tecto.2013.08.043.

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