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Journal of Structural Geology 66 (2014) 382e399

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Journal of Structural Geology

journal homepage: www.elsevier .com/locate/ jsg

Quantifying the growth history of seismically imaged normal faults

Edoseghe E. Osagiede a, b, Oliver B. Duffy b, *, Christopher A.-L. Jackson b, Thilo Wrona b

a Department of Earth Sciences, University College London, WC1E 6BT, UKb Basins Research Group (BRG), Department of Earth Science & Engineering, Imperial College, London SW7 2BP, UK

a r t i c l e i n f o

Article history:Received 21 January 2014Received in revised form28 April 2014Accepted 31 May 2014Available online 9 June 2014

Keywords:Normal fault growthFault kinematicsSeismic reflection dataVertical seismic resolutionSeismic forward modelling

* Corresponding author.E-mail address: o.duffy@imperial.ac.uk (O.B. Duffy

http://dx.doi.org/10.1016/j.jsg.2014.05.0210191-8141/© 2014 Elsevier Ltd. All rights reserved.

a b s t r a c t

Throw-depth profiles and expansion index plots are typically used to constrain the growth history ofseismically imaged normal faults. However, the ability to accurately correlate displaced stratigraphichorizons across faults and hence constrain stratigraphic thickness changes is typically limited by thevertical resolution of, and noise within, the seismic reflection dataset. Vertical seismic resolution is afunction of seismic velocities and the source wavelet frequency used during data collection. Here, we testhow variations in source wavelet frequency and seismic noise influence imaging of normal faults, and ourability to determine the fault growth history from the construction of throw-depth profiles andexpansion index plots. To achieve this, two input models were developed to mimic the geometry andgrowth history of polycyclic growth faults and blind normal faults. These models provided an input for aseries of 2D seismic forward models from which we produced synthetic seismic profiles. The modelswere run at different peak frequencies and seismic noise levels, so as to mimic variations in seismic dataquality associated with changes in the depth of burial. Throw-depth profiles and expansion index plotswere derived from the synthetic seismic profiles and used to constrain the fault kinematics, and theseresults were compared to those derived from the input models. Our results indicate that, at lower peakfrequencies and higher seismic noise levels, fault height can be underestimated, and strikingly, that thefault growth history can be misinterpreted. The results of our study indicate that geologists need to beaware of the imaging resolution of seismic reflection data when using these data to determine faultgrowth history of normal faults. Furthermore, hydrocarbon explorationists should be aware that seismicreflection data, the principal exploration tool, may not allow accurate determination of fault length andheight, which may impact risking of hydrocarbon traps that require at least a component of fault seal.

© 2014 Elsevier Ltd. All rights reserved.

1. Introduction

1.1. Constraining the growth histories of normal faults

Normal faults typically grow via one or a combination of thefollowing two mechanisms: i) growth of a single fault via a sys-tematic increase in displacement, length and height (e.g.,Watterson, 1986; Marrett and Allmendinger, 1991); and ii) growthas a result of along-strike or along-dip linkage of previously isolatedfault segments (e.g. Segall and Pollard, 1980; Martel et al., 1988;Peacock and Sanderson, 1991; Mansfield and Cartwright, 1996;Pollard and Fletcher, 2005; Jackson and Rotevatn, 2013). Toconstrain the depth of nucleation and growth history of a normalfault using outcrop, seismic or model-derived data, two types of

).

plots are constructed based on quantitative analyses of fault throw:i) throw versus depth plots, herein termed ‘T-z’ plots; and ii)expansion index plots (e.g. Thorsen, 1963; Bischke, 1994;Cartwright et al., 1998; Pochat et al., 2004, 2009; Hongxing andAnderson, 2007; Baudon and Cartwright, 2008a,b,c; Jackson andRotevatn, 2013; Tvedt et al., 2013). In the case of an idealisedblind isolated fault, the T-z profile will be symmetrical, with faultthrow progressively and smoothly decreasing from a maximum atthe fault centre to zero at the upper and lower tips (Kim andSanderson, 2005); the site of fault nucleation is usually taken tocorrespond to the point of maximum throw on the T-z plot (Fig. 1)(e.g. Cartwright et al., 1998; Hongxing and Anderson, 2007).However, T-z and expansion index plots may also be influenced byfactors such as variations in mechanical properties and/or lithology(e.g. Roche et al., 2012), tectonic reactivation and/or inversion(Mansfield and Cartwright, 1996; Cartwright et al., 1998; Hongxingand Anderson, 2007), and fault segment linkage (e.g. Kim andSanderson, 2005; Jackson and Rotevatn, 2013; Tvedt et al., 2013).

Fig. 1. (a) Idealised throw distribution on an isolated normal fault with the maximum throw located towards the centre of the fault and throw gradually decreasing to zero at thefault tip (after Barnett et al., 1987); (b) throw-depth (T-z) profile along the dashed line shown in (a).

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Throw gradients, which are a direct derivative of T-z plots, can alsobe used to distinguish between growth faults and blind faults (e.g.Childs et al., 2003; Jackson and Rotevatn, 2013).

When using high-quality 3D seismic reflection data, the abilityof the interpreter to effectively use T-z profiles and expansion indexplots to deduce the fault growth history and nucleation site isdependent on how accurately: i) the seismic reflection data imagethe true fault geometry; ii) the interpreter is able to correlate dis-placed hanging-wall and footwall horizons; and iii) the interpretercan constrain the thickness of equivalent footwall and hanging-wallstratigraphic units. These three factors are determined by the ver-tical and horizontal resolution of the seismic reflection data, which,in turn, are directly related to the frequency content (i.e. dominantfrequency and bandwidths), acoustic velocity and therefore factorssuch as burial depth, lithology, porosity and fluid fill. Furthermore,seismic data quality is also affected by: i) the signal-to-noise ratio ofthe seismic reflection data, which is also sensitive to burial depth;ii), the complexity of the overlying geology and velocities; iii) thegeometry and orientation of the seismic survey that acquires thedata; and iv) the processing methods used after data collection. Thelimitations imposed by the resolution of seismic reflection data inparticular can result in, for example, an underestimation of faultlength and height (Pickering et al., 1997; Kim and Sanderson, 2005;Xu et al., 2010; Rotevatn and Fossen, 2011), and the inability toresolve subtle changes in throw and stratigraphic thicknesses thatwould help constrain fault growth history. These issues are likely ofinterest to hydrocarbon explorationists who are responsible fordetermining the timing of trap formation and understanding therisks associated with fault reactivation (e.g. Langhi et al., 2010). Thepotential impact of vertical seismic resolution as a source of un-certainty and error in the quantitative analysis of the growth his-tory of seismically imaged normal faults has been recognised (e.g.Mansfield and Cartwright, 1996; Pickering et al., 1997; Cartwrightet al., 1998; Pochat et al., 2004; Kim and Sanderson, 2005; Baconet al., 2007), although no previous attempt has been made toevaluate the extent and possible implications of this effect.

This study uses a suite of relatively simple, forward seismicmodels to evaluate the effect of vertical seismic resolution on: i)how accurately seismic reflection data image and constrain thegeometry of normal faults; and ii) the ability to effectively apply T-zprofiles and expansion index plots to seismic reflection data todetermine the kinematic history of normal faults. To achieve this,two idealised normal fault models were constructed, one of whichillustrated the key geometric characteristics of faults formed by

fault growth by blind tip propagation (‘blind fault model’), and onethat grew by polycyclic growth faulting (‘polycyclic growth faultmodel’). These models were used as inputs for 2D synthetic seismicmodels, within which different peak frequencies and seismic noiselevels were varied so as to mimic variations in seismic reflectiondata quality related to depth of burial. T-z and expansion indexplots were generated from these synthetic seismic profiles, andthese data, with the subsequent interpretations of fault nucleationand growth histories, were compared to those constrained from theoriginal, idealised, input geologic models.

1.2. Seismic resolution

Seismic reflection data are limited in terms of the thickness (i.e.vertical resolution), width (i.e. horizontal resolution) and orienta-tion of the geological features that they can image. In this paper wefocus on issues related to the vertical resolution of seismic reflec-tion data and, although issues related to seismic resolution mayappear to be of concern to geophysicists, when seismic reflectiondata are used to constrain fault growth history, the potential limi-tations of seismic resolution also become critical for structuralgeologists.

The ability of seismic reflection data to image a geologicalfeature (e.g. a bed, bedset or fault zone) is mainly a function of thevertical seismic resolution. In other words, vertical seismic reso-lution is a measure of how thick a bed has to be for its top andbottom to be imaged by discrete reflections in seismic reflectiondata (e.g. Brown, 2011). Vertical seismic resolution is dependent onthe wavelength (l) of the seismic wavelet, which in turn isdependent on the dominant frequency (f) of the wavelet, and theseismic interval velocity (v), a relationship described by Eq. (1);

l ¼ v

f(1)

It is well-established that the Earth acts as a low pass filter, aslow frequencies are attenuated less with depth than are higherfrequencies and thus higher frequencies dominate at shallowerdepth while low frequencies are dominant at greater depths(Brown, 2011). Seismic velocity generally increases with depth,primarily as a result of increasing compaction. The net impact ofincreasing attenuation and seismic velocity with depth is that thevertical resolution of seismic reflection data generally decreaseswith depth (e.g. Brown, 2011).

Fig. 2. (a) Representative geological model with beds of 10 m thickness; (b) corresponding synthetic seismic wavelet wiggle trace at frequencies of 10 Hz, 25 Hz and 100 Hz; (c) plotof peak frequency against stratigraphic bed thickness highlighting when all ten stratigraphic beds are: i) fully-resolved without any interface interference (shaded dark-grey); ii)resolved but with interface interference (shaded light-grey); and (iii) unresolved (unshaded). Note that the dashed line represents the limit of visibility, with values determinedfrom our seismic modelling, and equates to approximately 1/8 of a wavelength, whereas the solid line represents the limit of separability, with values determined by calculating of1/4 of a wavelength and using an average velocity of 2000 m/s.

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In this study, we adopt the terminology of Brown (2011) todescribe the different elements of vertical seismic resolution. First,we define the limit of separability, which is commonly assumed tobe the ‘vertical seismic resolution’, as simply the thickness at whichthe reflections from two successive interfaces starts to interfere;the limit of separability is typically taken as being equal to one-quarter of a wavelength (Widess, 1973) and is equivalent to thetuning thickness. Second, the limit of visibility is the minimumthickness at which the reflections from two successive interfacescan be seen, and it can be as low as one-thirtieth of a wavelength,depending on the amount of noise in the seismic reflection data(signal-to-noise ratio) and the acoustic impedance contrast at theinterfaces (Brown, 2011).

2. Methodology

2.1. Model building

Two 2D idealised models of normal faults were developed: onerepresenting fault growth by blind tip propagation (‘blind isolatedfault model’) and another representing fault growth by polycyclicgrowth faulting (‘polycyclic growth fault model’). In both cases, themodels were characterised by a single, isolated, planar normal faultdipping at 60�.

Given that vertical seismic resolution tends not to be an issue ifbed thicknesses are much greater than the limit of separability (1/4of a wavelength), it was first necessary to conduct preliminary tests

Table 1Input values of acoustic parameters used for conversion to acoustic impedancemodel.

(A) Polycyclic growth normal fault Vp (m/s) Density (g/cm3)Sandstone 2150 2.18Shale 1850 2.20Base model bed 2700 2.50(B) Blind normal fault Vp (m/s) Density (g/cm3)Top model bed 1700 2.00Sandstone 2150 2.18Shale 1850 2.20Base model bed 2550 2.40

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to constrain the minimum thickness of beds to be used in theidealised normal fault models. To do this, 20 test models, eachconsisting of 10 horizontal beds of alternating sandstone and shale,were created and used as templates to generate simple syntheticseismic profiles (Fig. 2). Bed thicknesses were kept constant be-tween each test model, with bed thicknesses ranging from 1 to 20mwithin each model (Fig. 2). Typical sandstone and shale velocity anddensity values (Table 1) were assigned to the respective lithologies,with a 300 m/s difference in velocity between sandstone and shale(e.g. Schwab et al., 2007; Falivene et al., 2010) and simple syntheticseismic profiles were generated for each test model at peak fre-quencies ranging from 5 Hz to 100 Hz, at increments of 5 Hz(Fig. 2c). This range of peak frequencies was chosen to representrealistic frequencies at a range of burial depths in natural sedi-mentary basins (Table 2). An example model with a bed thicknessof 10 m, and the corresponding wavelet wiggle traces at 10 Hz,25 Hz and 100 Hz are presented in Fig. 2a and b. The results of thesetest models were used to generate a plot indicating whether all theinterfaces (i.e. bedding contacts) within a model of a certain bedthickness are resolved at a given peak frequency (Fig. 2c). If, for agiven model, all the interfaces within the model have visible re-flections (e.g. the 25 Hz and 100 Hz wavelet wiggle trace in Fig. 2b)then the model is classified as ‘resolved’, whereas if the number ofvisible reflections is less than the number of interfaces in the inputmodel (e.g. the 10 Hz wavelet wiggle trace in Fig. 2b) then themodel is classified as ‘unresolved’. The boundary between theresolved and unresolved portions of the plot equates to the limit ofvisibility, which is approximately 1/8 of a wavelength. The limit ofseparability, derived using an average seismic velocity of 2000 m/sand calculating l/4, is also shown on Fig 2c.

Using the peak frequency against bed thickness plot shown inFig. 2c, and by considering the typical frequencies observed innatural sedimentary basins at a range of depths that we will test inthis study (20e75 Hz; see Table 2), we can determine that, for a bedthickness of 10 m, there is a transition from: (i) resolved; (ii)resolved with interface interference; to (iii) unresolved (red line onFig. 2c). As such, by using a minimum bed thickness of 10 m it islikely that, at low frequencies (e.g. 20 Hz), not all beds will beresolved, thus questioning whether graphical techniques (e.g. T-zprofiles and expansion index plots) will be able to accurately

Table 2Acquisition year, water depth and dominant frequency of 3D seismic reflection data from

Seismic survey Dominant frequen

Location Acquisitionyear

Waterdepth (m)

Shallow (ca. 500 mbelow sea bed)

Santos Basin, offshore Brazil 2001/2002 ca. 2150 40Egersund Basin, offshore Norway 2005 ca. 115 50Exmouth Sub-basin, NW Shelf,

offshore Australia2000 ca. 850 e

Rockall Basin, offshore Ireland 1997 ca. 1500 e

Troll field, northern North Sea 1998 ca. 400 59

constrain fault kinematics. In contrast, at higher frequencies (e.g. 75Hz), it may be expected that all the beds are resolved and that therewill be less or no uncertainty associated with constraining faultkinematics using the graphical techniques. It is our aim to quantifythis degree of uncertainty at a range of different frequencies.

2.2. Seismic modelling

Seismic modelling refers to the generation of a synthetic seismicprofile from an input geologicmodel. Like a seismic reflection survey,the generation of a synthetic seismic profile requires that an acousticimpedance contrast, which is the product of density and seismicvelocity variations, exists between or across geological features tocreate a detectable signal. In this study, we follow the traditionalapproach to seismic forward modelling (e.g. Fagin, 1991; Schwabet al., 2007; Cacas et al., 2008; Falivene et al., 2010; Holgate et al.,in press) and used typical subsurface velocity and density valuesfor sandstone and shale (Table 1), which were then used to convertthe geologicmodels to acoustic impedancemodels. Although densityand velocity typically increase with depth, in this study these valueswere kept constant to ensure similar acoustic impedance contrastsbetween beds at a range of depths so as to isolate the effect of seismicresolution as a function of dominant frequency and seismic noise.We generated zero-phase Ricker wavelets with peak frequencies of20 Hz, 25 Hz, 50 Hz, and 75 Hz (Ricker,1953). These peak frequenciescorrespond to maxima in the amplitude spectra of the wavelet. Thedominant frequencies of these wavelets are about 30 percent greaterthan the peak frequencies (Kallweit and Wood, 1982). We believethat these dominant frequencies cover the typical range encounteredin many 3D seismic reflection datasets from a number of global lo-cations and at a range of depths (Table 2).

To simulate a migrated seismic section, the synthetic seismicprofiles were generated using a simple 1-D convolution, zero-offset(vertical incidence) ray-tracing algorithm, which is the most widelyused seismic modelling method (e.g. Fagin, 1991; Schwab et al.,2007; Cacas et al., 2008; Falivene et al., 2010). The polarity of thesynthetic seismic profiles is SEG normal, with a positive acousticimpedance contrast represented by a red reflection and a negativeacoustic impedance contrast represented by a black reflection. Totest the impact of seismic noise on the extraction of quantitativedata from seismically imaged normal faults, synthetic seismicprofiles were also generated for cases where relatively low (5%standard deviation of input parameters including density and P-wave velocity), medium (10% standard deviation), and high (20%standard deviation) amounts of seismic noise were added to themodels. The synthetic seismic profiles were generated in depth.

2.3. Kinematic analysis

Two quantitative fault analysis methods were utilised in thisstudy to determine the nucleation and propagation history of theseismically-imaged faults: T-z profiling (e.g. Cartwright et al., 1998;

different basins, at different depth intervals below the sea-bed.

cy (Hz)

s Intermediate(ca. 1000 ms below sea bed)

Deep (ca. 2000 msbelow sea bed)

Very deep (ca. 4000ms below sea bed)

30 25 e

35 30 15e 49 21

e e 2154 48 e

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Hongxing and Anderson, 2007), and expansion index plots (e.g.Thorsen, 1963). The first of these techniques, T-z profiling, involvesmeasuring the throw (vertical separation) of a given horizon acrossa normal fault, and plotting it against the corresponding depth ofthe hanging-wall cut-off. Note that in this study, depth is measuredas the vertical distance from the upper tip of the fault to thehanging-wall cut-off of the given horizon (e.g. Cartwright et al.,1998). For the expansion index plots, the ratio of the stratigraphicthickness of a seismically defined unit in the hanging-wall andfootwall is calculated (e.g. Thorsen, 1963). Values of 1 indicate thatno across-fault thickness change occurs and suggests that the faultwas inactive during deposition of the studied unit; values >1indicate stratigraphic thickening into the hanging-wall, which maydefine a period of fault activity (Thorsen, 1963; Cartwright et al.,1998; Rouby et al., 2003; Hongxing and Anderson, 2007).

T-z profiles were constructed for the input fault models, inaddition to the normal faults in the synthetic seismic profilesgenerated for a range of peak frequencies and noise levels. In thecase of the original blind fault model, the fault-tip monoclinesdirectly above and below the upper and lower tips respectivelywere taken as the points of zero throw of the fault. To obtain throwvalues from the synthetic seismic profiles, the hanging-wall andfootwall cut-offs of individual horizons were manually picked atsites of maximum reflection amplitude. The uncertainty in pickingthe exact footwall and hanging wall cut-off within the reflection ofan interface is, at most, ±1 m; this scale of error is deemed negli-gible and would not significantly alter the generated T-z profileshapes or the resulting interpretations of the fault growth histories.Combined T-z plots were constructed, allowing a direct comparisonof the T-z profiles of the input model and the T-z profiles con-strained from the synthetic seismic profiles from the model runs atdifferent peak frequencies and noise levels. These combined T-zplots help assess the impact of vertical seismic resolution atdifferent peak frequencies or noise levels on the ability to extractthrow data of sufficient quality that permits fault kinematics to beaccurately constrained. Note that expansion index plots were onlyconstructed for the polycyclic growth fault model as the blind faultmodel by definition lacks syn-sedimentary growth sequences.

3. Configuration of the idealised normal fault input models

Two idealised normal fault models with well-constrainedgrowth histories were generated to simulate: (i) polycyclicnormal fault growth (‘polycyclic growth fault input model’), and (ii)fault growth by blind-tip propagation (‘blind isolated fault inputmodel’). For simplicity, only clastic sediments, sandstone and shale,have been included in the input models. Furthermore, the modelswere simplified by assuming a homogenous character to thesandstone and shale units, that is, there is no variation in acousticproperties within individual units. In both models, the fault isplanar and dips at 60⁰, as is typical of natural normal fault (30⁰e60⁰;Jackson and White, 1989; or �45⁰e�65⁰; Westaway and Kusznir,1993).

3.1. Polycyclic growth fault input model

A polycyclic growth fault is a normal growth fault that expe-riences several periods of activity punctuated by periods of inac-tivity and burial. Faults demonstrating this style of growth arecommon worldwide, with well-documented examples in the Gulfof Mexico (e.g. Cartwright et al., 1998), North Sea (e.g. Færseth,1996; Whipp et al., 2014), the Alpine Basin, SE France(Bouroullec et al., 2004) and offshore Brazil (Baudon andCartwright, 2008). In the polycyclic growth fault input model(Fig. 3a) we assume that, during periods of fault activity, sediment

accumulation rate outpaces the rate of hanging-wall subsidence,such that the hanging-wall basin is ‘overfilled’ and sediment isdeposited on the footwall. Some of the beds thus thicken acrossthe fault and are classified as syn-sedimentary growth sequencesthat document syn-depositional fault activity (Fig. 3). Other beds,which do not thicken across the fault, are classified as non-growthsequences, representing a period when the fault was inactive andits upper tip was buried by an isopachous blanket of sediment(Fig. 3).

The T-z profile of the polycyclic growth fault input model(Fig. 3b) has segments that are defined by positive throw gradients(where throw increases with depth), which correspond to times offault activity, and vertical segments (where throw shows no vari-ation with depth), which correspond to intervening periods whenthe fault was inactive and its upper tip was buried (Fig. 3b)(Thorsen, 1963; Hongxing and Anderson, 2007). The maximumthrow of this idealised fault is 56 m and it corresponds to the Sh Abed (Fig. 3). Similarly, periods of fault growth and inactivity areeasily identified on the expansion index plot (i.e. where expansionindex ¼ >1; Fig. 3c). Overall, the polycyclic growth fault inputmodel has experienced three episodes of growth punctuated bytwo periods of inactivity and upper tip burial (Fig. 3).

3.2. Blind isolated fault input model

Blind, isolated normal faults typically grow free from the in-fluence of the free surface or adjacent faults, and grow by radialpropagation of the tip line. It is typically assumed that the pointof maximum displacement remains stationary (Watterson, 1986).As such, blind, isolated normal faults are characterised by: i) arelatively simple distribution of throw on the fault surface,marked by a throw maximum in the fault centre that graduallydecreases radially towards the elliptical tip line along whichthrow is zero (Fig. 1) (e.g. Watterson, 1986; Barnett et al., 1987;Nicol et al., 1996; Baudon and Cartwright, 2008a); ii) no signifi-cant change in stratigraphic thickness from hanging-wall tofootwall, with throw typically accommodated by dilation andcompaction in the host rock (Barnett et al., 1987); and (iii) thepresence of fault-propagation folds at the upper and lower tips(Hardy and McClay, 1999; Willsey et al., 2002; Baudon andCartwright, 2008a).

These general geometric characteristics provided the basis forour idealised blind normal fault input model (Fig. 4a). The faultheight was set at 310 m, and the positions of the upper and lowertips of the fault are well constrained; this is important to notebecause one aim of this study is to understand how well seismicreflection data can constrain fault tip locations and, therefore, faultheight and near-tip throw gradients. The lower tip lies betweenthe displaced top of shale unit A (cf. discontinuous deformation ofLong and Imber, 2010) and the folded (non-displaced) bottom ofshale unit A (cf. continuous deformation of Long and Imber, 2010),whereas the upper tip lies between the displaced bottom of shaleunit F and the folded (non-displaced) top of shale unit F. Atriangular zone of deformation or ‘trishear zone’, which is char-acterised by fault propagation monoclinal folds that broaden up-wards above the upper fault tip, is denoted by dashed lines inFig. 4b.

The T-z profile for the blind, isolated fault input model (Fig. 4c)displays an approximately symmetrical throw distribution that iscomparable to the ‘C-type’ pattern described by Muraoka andKamata (1983). The site of nucleation of the fault, as determinedby the point of maximum throw (10 m), is located approximately atthe centre of the fault, with throw decreasing to zero at the upperand lower tips. The throw gradient of both the upper and lowerparts of the fault is low (ca. 0.06), such that the increase or decrease

Fig. 3. (a) Original idealised geological model for a fault that has experienced polycyclic growth. Note that the minimum thickness of stratigraphic units is 10 m. Footwall strat-igraphic units are all 10 m thick but thicknesses vary in the hanging-wall as a function of syn-depositional fault activity. (b) T-z profile of the original model showing two episodes ofreactivation (marked by an increase in throw with depth i.e. a positive throw profile) separated by periods of burial (marked by no change in throw with depth i.e. a vertical throwgradient. (c) Expansion Indices plot of the original model indicating periods of growth and non-growth.

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in throw along the fault surface is gradual, which is typical of iso-lated blind normal faults (Childs et al., 2003).

4. Synthetic seismic forward modelling of idealised faultinput models

In this section we describe the results of our synthetic seismicforward modelling of the two input models. Here we examine theresults of synthetic seismic models that had: i) different peakfrequencies (20 Hz, 25 Hz, 50 Hz, and 75 Hz), but with the zero

noise; and ii) low, medium and high levels of seismic signal-to-noise ratio, but with a constant peak frequency of 50 Hz. Wethus try and isolate the influence of peak frequency and signal-to-noise on the seismic imaging of normal faults. In this section wealso describe the T-z profiles and expansion index plots con-structed for the seismically imaged faults. We then use these plotsto evaluate how our interpretation of fault growth history variesbetween the input models, for which the history is known, and theseismically imaged normal faults fromwhich the growth history isinferred.

Fig. 4. (a) Original idealised geological model of a blind normal fault; (b) zoomed-in section of the fault indicating the zone of ductile deformation (trishear zone) at the upper andlower tips. Note that in general there is no change in stratigraphic thickness of a given unit from hanging-wall to footwall; (c) T-z profile of the original model indicating the point ofmaximum throw and site of nucleation.

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4.1. Peak frequency

4.1.1. Polycyclic growth fault modelThe synthetic seismic profile generated using a 20 Hz peak

frequency (Fig. 5a) contains a very high amplitude, positivereflection coefficient (red) reflection in the lower part of the sec-tion; this prominent reflection marks the contact between therelatively low impedance shale A and the underlying high imped-ance model base. The fault is imaged on the seismic section as anapproximately 50 m-wide distorted zone rather than a discreteplane (Fig. 5a). Furthermore there are significant contrasts betweenthe seismic expression of hanging-wall and footwall beds, with: i)the hanging-wall containing more reflections than the footwall;and ii) the hanging-wall generally displaying higher reflectionamplitudes than the footwall. These differences are interpreted asbeing a function of the generally thicker and thus fully resolvedhanging-wall beds.

As fewer interfaces can be resolved in the synthetic seismicprofile than were present in the input model (cf. Figs. 3a and 5a),fewer horizon cut-offs could be identified and used to construct a T-z profile for the fault (cf. Figs. 3a and 5b). Note that a potential errorrelates to our uncertainty in accurately correlating hanging-walland footwall reflections. These issues notwithstanding, the con-structed T-z profile increases in throw with depth, whilst on theexpansion index plot every bed shows an expansion index of >1,with a maximum of 1.5 in Bed 4 (Fig. 5b and c). Taken together,these seismically-derived data suggest that the fault was a syn-sedimentary growth fault throughout its entire history and didnot experience any periods of inactivity. This contrasts markedly tothe ‘true’ fault growth history derived from the quantitative anal-ysis of the original idealised model, in which three episodes ofgrowth are punctuated by two episodes of inactivity (Fig. 5b and c).

When compared to the 20 Hz model, a synthetic seismic profilegenerated using a peak frequency of 25 Hz shows: i) a higher

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number of resolved interfaces; ii) thinner reflections (i.e. shorterwavelengths); iii) a narrower (36 m wide) zone of distortion at thefault trace; and iv) higher reflection amplitudes (cf. Fig. 5a and d).Most critically, therefore, compared to the 20 Hz peak frequencycase, more horizon cut-offs are observed and can be correlated inthe 25 Hz model (cf. Fig. 5b and e). The T-z profile for the 25 Hz caseis characterised by three portions where fault throw increases withdepth, separated by two portions where throw shows no variationwith depth (Fig. 5e). The expansion index plot suggests a shortextra period of growth during the deposition of Bed 17, such thatthere are four stratigraphic packages with an expansion indexabove 1.0 (Fig. 5f). However, in general, the periods of growthbroadly correlate with portions of the T-z profile that show an in-crease in fault throw with depth, and are separated by beds or bedssets which show no significant expansion into the hanging-wall(Fig 5f). Taken together, and with the exception of the minorperiod of growth indicated by thickness variations in Bed 17(Fig. 5f), these quantitative analyses suggest that the fault has hadthree main periods of growth punctuated by two periods of inac-tivity and burial (Fig. 5e and f). As such, the quantitative analysis ofthe synthetic seismic profile has reproduced the growth historyconstrained from the input model (Fig. 3), despite less “beds”, andthus horizon cut-offs being resolved in the synthetic seismic profilethan are present in the input model (cf. Figs. 3, 5d-f).

At a peak frequency of 50 Hz, all the interfaces in the originalmodel are resolved in the synthetic seismic profile (Fig. 5g). How-ever, when compared to the 20 and 25 Hz models, the 50 Hz modelshows some significant differences including: i) reflections of thetop and bottom of some of the beds in the hanging-wall are sepa-rated by distinctive, very low amplitude zones; ii) thinner re-flections; iii) a narrower (ca. 15 m) zone of distortion around thefault trace; and iv) lower reflection amplitudes in the hanging-walland higher reflection amplitudes in the footwall (cf. Fig. 5a, d and g).The lower reflection amplitudes in the hanging-wall are inter-preted to be a result of bed thicknesses that are greater than thelimit of separability (see Fig 2c); thus, unlike in the 20 and 25 Hzmodels, constructive interference does not occur between adjacentreflections. In contrast, the higher reflection amplitudes in thefootwall are interpreted to be due to the fact that the footwall bedsare approximately the same thickness as the limit of separabilityestimated for a peak frequency of 50 Hz (10 m; Figs. 2c and 3a). Assuch, the ratio of bed thickness to tuning thickness is 1 and at thisratio, reflections from two closely spaced interfaces will construc-tively interfere, resulting in the higher amplitudes (Fig. 5g). Allother observations here are similar to those of the 25 Hz peakfrequencymodel. In general, observations from the 50 Hzmodel areindicative of increased seismic resolution controlled by an increasein peak frequency from 25 Hz to 50 Hz.

The fault growth history interpreted from the T-z profile(Fig. 5h) and expansion index plot (Fig. 5i) for the 50 Hz syntheticseismic profile are similar to those of the 25 Hz peak frequency case.As such, there are three clear periods of fault growth punctuated bytwo periods of fault inactivity and burial, matching the true faultgrowth history constrained from the input model (Fig. 5h and i).However, unlike in the 25 Hz peak frequency case, all possible bedboundaries are imaged and hence all possible horizon cut-offs andbed thicknesses can be plotted. The resulting plots are thus ofhigher accuracy in the 50 Hz case than the 20 Hz or 25 Hz cases(Fig. 5h and i).

At a peak frequency of 75 Hz the synthetic seismic profile showssome significant differences when compared to the 50 Hz model,most significantly thinner reflections, lower reflection amplitudesand a narrower (ca. 8 m) zone of distortion around the fault trace;the fault plane is therefore expressed by a discrete reflection (cf.Fig. 5g and j). The reflection thickness and the width of the zone of

distortion around the fault trace are interpreted to have reduced asa result of improved vertical resolution, whereas the lower ampli-tudes are interpreted to be the result of an absence of constructiveinterference between reflections from successive interfaces as bedthicknesses (�10 m) are greater than the limit of separability(approximately 6.7 m) at 75 Hz peak frequency (Fig. 2c). Quanti-tative analysis of the 75 Hz synthetic section produces a T-z profile(Fig. 5k) and an expansion index plot (Fig. 5l) which are similar tothose derived from the 50 Hz peak frequency model (Fig. 5h and i).As such, the interpreted fault growth history is the same and is aclose match to true fault growth history.

A T-z plot showing the profile constructed from the originalpolycyclic growth normal fault model along with those constructedfrom the 20 Hz, 25 Hz, 50 Hz, and 75 Hz peak frequency syntheticseismic profiles is presented in Fig. 6a. This figure allows a directcomparison of the effect of seismic resolution (as a function of peakfrequency) on the constrained T-z profile (Fig. 6a). The combinedplot shows that the T-z profile constrained from synthetic seismicprofiles generated at peak frequencies �25 Hz closely matches thatof the original idealised model (Fig. 6a). On the other hand, the T-zprofile of the normal fault as imaged from the 20 Hz syntheticseismic profile does not match that of the original idealised poly-cyclic growth fault model (Fig. 6a). This observation is importantbecause it emphasises the effect that the close relationship be-tween bed thickness and the limit of visibility, imposed by seismicresolution, has on accurately extracting a T-z profile from, andsubsequently interpreting the growth history of, a seismicallyimaged normal fault.

4.1.2. Blind fault input modelAt a peak frequency of 20 Hz the synthetic seismic profile dis-

plays three key characteristics: i) all the interfaces in the originalmodel (Fig. 4) are resolved (Fig. 7a); ii) amplitudes are generallyhigh due to constructive interference between reflections fromsuccessive interfaces; and iii) the zone of distortion in the areaaround the fault trace is subtle, likely due to the throw of the in-terfaces in the model being insufficient to fully juxtapose beds ofdifferent acoustic impedances (Fig. 7a). The corresponding T-zprofile (Fig. 7b) constructed from the 20 Hz synthetic seismicprofile suggests a fault height of ca. 275m and a symmetrical throwdistribution, with the point of maximum throw located approxi-mately at the centre of the fault (at a depth of ca. 575 m; Fig. 7b).Throwgradually decreases to zero at the fault tips, typical of a blind,isolated fault, with throw gradients at the upper and lower tipsbeing ca. 0.11 (Fig. 7b). The exact locations of the upper and lowertips are poorly-constrained because throw on the uppermost andlowermost displaced horizons is �2 m and thus below the limit ofvisibility at this peak frequency (cf. Fig 2c).

The observations from the synthetic seismic profile at 25 Hzpeak frequency (Fig. 7c) are similar to those described for the 20 Hzpeak frequency synthetic seismic profile, except for a slightdecrease in reflection amplitude and thickness (cf. Fig. 7a and c).The corresponding T-z profile (Fig. 7d) is identical to that derivedfrom the 20 Hz seismic section, leading to the interpretation thatthe fault grew by blind tip propagation.

At a peak frequency of 50 Hz (Fig. 7e) the synthetic seismicprofile shows significantly thinner reflections when compared tothose of the 25 Hz model, consistent with an increase in seismicresolution as a result of an increase in peak frequency (cf. Fig. 7c ande). The T-z profile (Fig. 7f) constructed from the 50 Hz syntheticseismic profile shows a broadly similar form to that observed at 20and 25 Hz, and is typical of a blind, isolated fault; i.e. it has asymmetrical shape, and is characterised by relatively low throwgradients (ca. 0.07) at its upper and lower tips. However, due toimproved vertical seismic resolution, the low throw values at the

Fig. 5. Polycyclic growth normal fault model outputs and quantitative analyses for different peak frequencies. (a) raw synthetic seismic profiles at 20 Hz peak frequency and corresponding (b) T-z and (c) Expansion Index plots.; (d) rawsynthetic seismic profiles at 25 Hz peak frequency and corresponding (e) T-z and (f) Expansion Index plots. (g) raw synthetic seismic profiles at 50 Hz peak frequency and corresponding (h) T-z and (i) Expansion Index plots. (j) rawsynthetic seismic profiles at 75 Hz peak frequency and corresponding (k) T-z and (l) Expansion Index plots.

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Fig. 6. Combined T-z plots. (a) T-z plots constrained from polycyclic growth normal fault input model and from synthetic seismic profiles generated at different peak frequencies; (b)T-z plots constrained from blind, isolated normal fault input model and from synthetic seismic profiles generated at different peak frequencies; (c) T-z plots constrained frompolycyclic growth normal fault input model and from synthetic seismic profiles generated at different seismic noise levels; (d) T-z plots constrained from blind, isolated normal faultinput model and from synthetic seismic profiles generated at different seismic noise levels.

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Fig. 7. Blind normal fault model outputs and quantitative analyses for different peak frequencies. (a) synthetic seismic profile at 20 Hz peak frequency and (b) the associated T-z plot. (c) synthetic seismic profile at 25 Hz peak frequencyand (d) the associated T-z plot. (e) synthetic seismic profile at 50 Hz peak frequency and (f) the associated T-z plot. (g) synthetic seismic profile at 75 Hz peak frequency and (h) the associated T-z plot.

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Fig. 8. Polycyclic growth normal fault model outputs and T-z plots for different seismic noise levels. Synthetic seismic profiles at: (a) low seismic noise level (5% standard deviation);(b) medium seismic noise level (10% standard deviation) and (c) high seismic noise level (20% standard deviation). (d) T-z plot constructed from low seismic noise synthetic seismicprofile. (e) T-z plot constructed frommid seismic noise synthetic seismic profile. Note that due to the obliterated nature of the high noise synthetic seismic model it was not possibleto construct a T-z profile.

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upper and lower tips of the fault now lie above the limit of visibilityof the synthetic seismic profile, such that the measured fault heighthas apparently increased from ca. 275 m to 310m, which is the trueheight of the fault in the input model.

The synthetic seismic profile generated at 75 Hz peak frequencyshows thinner reflections than those of the 50 Hz synthetic seismicprofile (Fig. 7g) and the corresponding T-z profile (Fig. 7h) is similarto that constructed for the 50 Hz peak frequency case. For example:i) the T-z profile is symmetrical; ii) the fault tips are characterisedby low throw gradients (ca. 0.07), and iii) the measured fault heightis 310 m.

A plot showing T-z profiles for the original blind, isolated normalfault model, along with those constrained from the different peakfrequency cases, is presented in Fig. 6b, allowing a direct compar-ison of the effect of the effect of peak frequency on the interpretedT-z profiles. The key observation from the composite plot is that atlower peak frequencies, that is, 20 or 25 Hz, the extent to which theupper and lower tips have propagated is significantly under-estimated with respect to the true fault height (Fig 6b). Forexample, at 20 Hz, where the limit of visibility is ca. 10 m, themeasured fault height is ca. 35 m less than the true fault height, anunderestimation of ca. 11%. Furthermore, the upper tip is ca. 21 mdeeper and the lower tip is ca. 14 m shallower that the true tiplocations (Fig 6b).

4.2. Seismic noise

The set of synthetic seismic models described in Section 4.1 allsimulate idealised, noise-free and perfectly processed seismicsections, however, the likelihood of generating such sections fromseismic surveys is virtually non-existent, even for a well-processed,industry-standard survey, collected in good environmental condi-tions with an optimally designed survey. In this section, the impactof lower signal-to-noise ratio on seismic imaging and kinematicanalysis of both the polycyclic and the blind fault models isexplored using synthetic seismic models generated with low (5%standard deviation of input parameters such as density and P-wavevelocity), medium (10% standard deviation), and high (20% stan-dard deviation) seismic noise levels, and at a constant peak fre-quency of 50 Hz.

4.2.1. Polycyclic growth fault input modelOn the low-noise model (Fig. 8a) a zone of distortion at the fault

trace is observed, but it is less discrete than in the correspondingnoise-free model (cf. Figs. 5g and 8a). Furthermore, stratigraphicinterfaces are imaged and can still be easily correlated across thefault, although they are slightly distorted by noise and are of loweramplitude than the noise-free model (cf. Figs. 5g and 8a). The T-zprofile constructed from the low-noise model (Fig. 8d) suggests theupper tip of the fault is 20 m deeper than the true position on theidealised model (Fig. 3). This is most likely due to throw across thetopmost faulted interface on the original model lying below thelimit of visibility of the synthetic seismic, such that the reflectionappears unfaulted. Also, the reflection below this on the syntheticseismic profile is expressed as an upper fault tip monocline and istaken as the upper fault tip, although in the original model thisinterface is clearly faulted (cf. Figs. 3 and 8a). Despite these issues,the general form of the T-z profile is similar to that from the noise-free, 50 Hz model (Fig. 5h) and hence the interpretation of faultgrowth history is in agreement with that constrained from theidealised model (Figs. 3, 5h and 8d).

At a medium level of seismic noise, the reflections show a muchgreater degree of distortion than for the low seismic noise case andthe fault trace reflection is almost completely obliterated (cf. Fig. 8aand b). Due to distortion of the low amplitude reflections, fewer

throw and depth points have been used to construct a T-z profilethan in the noise-free case (cf. Figs. 5h and 8e). The T-z profile in-dicates that the upper tip is mis-located by ca. 40 m; approximatelytwice that of the low seismic noise case (cf. Fig. 8d and e). The faultgrowth history, as constrained from the gradients on the T-z profile,matches that determined from the idealised model, with the highthrow gradient near the upper tip (0.53) indicating a third and finalperiod of syn-sedimentary growth faulting (Figs. 3 and 8e).

In the high-noise model (20% standard deviation) no fault planereflection is present, interface reflections lack continuity, and it isdifficult to confidently correlate reflections across the fault (Fig. 8c).In fact, with the exception of the high-amplitude reflectionmarkingthe interface between the sediments and the model base, it mightbe easy to incorrectly surmise that no fault is present in the model(Fig. 8c). Because of poor seismic imaging of the fault and faultedstratigraphy, it is not possible to construct a T-z profile for the high-noise model.

The combined T-z plot shown in Fig. 6c allows for a directcomparison of the T-z profile constrained from the original poly-cyclic growth fault model, the noise-free 50 Hz peak frequencysynthetic seismic profile, and the low (5% standard deviation) andmedium noise (10% standard deviation) cases. The plot shows thatat low and medium levels of noise, the general profile can bereconstructed to match that constrained from the original idealisedmodel (cf. Figs. 3 and 6c). However, as seismic noise increases, theaccuracy with which the upper tip can be located decreases(Fig. 6c).

4.2.2. Blind fault input modelWith low levels of noise, the synthetic seismic profile (Fig. 9a)

contains fairly well-defined reflections, although it is difficult toidentify a discrete fault plane reflection (cf. the noise-free case inFig. 7e). Beds in the input model with thicknesses greater than thelimit of separability at 50 Hz peak frequency (i.e. >10m), which hadclearly resolved top and bottom contacts in the noise-free model,are now characterised by chaotic ‘internal’ reflections (cf. Figs. 7eand 9a). At low levels of noise, the T-z profile is symmetrical,with low upper and lower tip throw gradients of 0.06e0.12(Fig. 9d), which are both consistent with the interpretation that thefault evolved as a blind, isolated structure, in agreement with theinput model (cf. Figs. 4 and 9d). However, based on the T-z profile,the fault height is estimated to be ca. 278 m, which is a ca. 10%underestimation of the true fault height (cf. Figs. 4 and 9d).

In the mid-noise model, bedding contacts are less well-definedthan in the low-noise models (cf. Fig. 9a and b). In addition, the T-zprofile derived from the mid-noise models is more asymmetric,with the point of maximum throw being much closer to the lowerthan the upper tip (cf. Fig. 9d and e). There is a gradual change inthrow in the upper section of the fault, with throw gradient nearthe upper tip being ca. 0.09. In contrast, the change in throw in thelower section of the fault is relatively rapid and defined by asignificantly higher fault-tip throw gradient (ca. 0.32; Fig. 9e). As inthe low-noise model, the fault height based on the T-z profile fromthe mid-noise model is underestimated, in this case by ca. 29%.

In the high-noise model, bedding interfaces are very poorlydefined and no fault plane reflection can be identified (Fig. 9c), thelatter likely due to the maximum fault throw (10 m) being belowthe limit of visibility imposed by this level of seismic noise. As such,the fault in the original geologic model is now indistinguishable (cf.Figs. 4 and 9c).

A combined T-z plot is presented in Fig. 6d that allows directcomparison of the T-z profile constrained from the original blindnormal fault model, the noise-free 50 Hz synthetic model, and thelow- and medium-noise models. The plot indicates that, as theamount of seismic noise increases, there is a reduction in the

Fig. 9. Blind normal fault model outputs and T-z plots for different seismic noise levels. Synthetic seismic profiles at: (a) low seismic noise level (5% standard deviation); (b) mediumseismic noise level (10% standard deviation) and (c) high seismic noise level (20% standard deviation). (d) T-z plot constructed from low seismic noise synthetic seismic profile. (e) T-z plot constructed frommid seismic noise synthetic seismic profile. Note that due to the obliterated nature of the high noise synthetic seismic model it was not possible to constructa T-z profile.

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accuracy with which: i) fault tips can be located; and ii) fault throwgradients can be constrained.

5. Discussion

5.1. Implications for constraining the growth history of normalfaults

When attempting to constrain the growth history of normalfaults, a series of factors must be considered, including whether thefault: i) grew as an isolated fault, or interacted and/or linked withadjacent segments; ii) propagated blind or interacted with the freesurface as a growth fault, or grew by a combination of bothmechanisms; and iii) had a polycyclic history, characterised byseveral discrete periods of activity and reactivation.

Our polycyclic growth fault models, in which we test differentpeak frequencies as a proxy for variations in vertical seismic reso-lution, indicate that low vertical seismic resolution (i.e. low peakfrequencies) can result in misinterpretation of the fault growthhistory. This issue is well illustrated in the T-z profile (Fig. 5b) andthe expansion index plot (Fig. 5c) constrained from the 20 Hz peakfrequency synthetic seismic profile, which show that, due to thelimit of visibility imposed by the 20 Hz peak frequency, the plots areconstrained by relatively few reflection cut-offs and therefore twosignificant periods of fault inactivity and burial are missed (cf.Fig. 3b). In the case of Fig. 5e and f, it can be seen that fault growthhistory can be constrained more accurately by using the moregeneral trends visible on the T-z plot rather than those on theexpansion index plot. In particular, Bed 17 displays only a verymodest across-fault thickening that erroneously implies a shortperiod of fault growth in a period that is otherwise characterised byfault dormancy. This leads us to suggest that interpreters should bewary of over-interpreting expansion index plots that have beenconstructed from low-resolution seismic reflection data. Failing toidentify the polycyclic history of a fault or erroneously interpretingperiods of activity that did not occur both have significant impli-cations for understanding the tectonic history of a sedimentarybasin. For example, did several pulsed stretching events and pe-riods of fault reactivation occur or not? Furthermore, in the contextof hydrocarbon exploration, failure to accurately constrain thetiming and nature of fault activity may result in the misinterpre-tation of the timing of fault trap generation and breachwith respectto the timing of hydrocarbon filling. This potential source of errormust be considered when establishing seal risk because leakage isgenerally more likely during phases of fault reactivation than dur-ing phases of fault inactivity (e.g. Wiprut and Zoback, 2002; Lyonet al., 2005; Cartwright et al., 2007; Baudon and Cartwright,2008c; Langhi et al., 2010).

Our study indicates that vertical seismic resolution has a majorimpact on calculated throw gradients on seismically imagednormal faults. This is particularly evident in the blind fault model(Fig. 6d), in which the medium noise model (green profile) ischaracterised by an abnormally high, lower fault tip throw gradient(ca. 0.32) when compared to the true gradient (ca. 0.06) observed inthe input model. High throw gradients near fault tips are typicallyinterpreted as a function of mechanical interaction between adja-cent faults (e.g. Schlische et al., 1996), mechanical restriction of thefault tip during vertical or lateral propagation (e.g., Muraoka andKamata, 1983; Roche et al., 2012) or interaction with the free sur-face (Childs et al., 2003; Jackson and Rotevatn, 2013). Our resultsimply that poor seismic resolution may, for example, result in ablind, isolated normal fault, which would otherwise be charac-terised by a simple ‘C-type’ T-z profile (e.g. Muraoka and Kamata,1983), being defined by a relatively asymmetric profile and thus

erroneously being interpreted as having interacted with an adja-cent fault, mechanical barrier in the host rock or the free surface.

5.2. Defining the geometry of normal faults and implications fordefining hydrocarbon traps

Constraining the true geometry of a normal fault is critical to theevaluation of hydrocarbon trapping potential. Fault height, length,dip, and the exact location of the fault are key geometrical pa-rameters that must be constrained when defining a fault trap andestimating hydrocarbon volumes, and ultimately, when deter-mining the optimal location to place an exploration or productionwell (e.g. Rotevatn and Fossen, 2011). The seismic forward modelsgenerated in this study illustrate how vertical seismic resolutioncan impact the accuracy of these geometric parameters. Forexample, in the case of the blind isolated fault model, low seismicresolution results in incorrect positioning of the fault tips and asignificant underestimation of fault height (ca. 15% for the lowerpeak frequencies, noise-free cases and 40% for the models mediumto high seismic noise) (Fig. 6b and d); this may also lead to anincorrect aspect ratio (i.e. height-width ratio) being determined forthe fault (sensuNicol et al., 1996). In a fault-dependent hydrocarbontrap, the estimated prospect size and volume is strongly influencedby the limit of the seismically mappable size (height and length) ofthe fault, and so vertical seismic resolutionmay be significant whenclassifying if a prospect is economically viable or not (see alsoRotevatn and Fossen, 2011). Furthermore, our polycyclic growthfault synthetic model (e.g. Fig. 5a) shows that the fault trace, whichin the idealised model is defined by a discrete line, is imaged as abroad distorted zone; it is therefore difficult to constrain the truelateral position of the fault trace. In our models, the width of thiszone of distortion decreases with increasing peak frequency, suchthat the uncertainty associated with defining the lateral position ofthe fault trace is less in the 75 Hz peak frequency case (high seismicresolution) than in the 20 Hz peak frequency case (low seismicresolution) (cf. Fig. 5a and j). It therefore follows that hydrocarbonvolume estimations will have less associated uncertainty whenconstrained from high peak frequency data than low peak fre-quency seismic reflection data.

6. Conclusions

In this study, two models were developed to mimic the geom-etry and growth history of polycyclic growth faults and blindnormal faults. These models provided an input for a series of 2Dseismic forward models run at different peak frequencies andseismic noise levels, with the aim of exploring the impact verticalseismic resolution has on the quantitative analysis of seismicallyimaged normal faults, and consequently, on the ability of theinterpreter to accurately constrain fault kinematics. Our resultsindicate:

� When trying to establish the effect of vertical seismic resolutionon the ability to accurately constrain fault kinematics fromseismically imaged normal faults, a key aspect to consider is thethickness of the displaced beds relative to the frequency of theseismic reflection data. For example, a peak frequency of 20 Hzwill impose a limit of separability of 25 m (assuming an averageseismic velocity of 2000m/s). If bed thicknesses are below 25m,not all interfaces may be imaged and there may be major un-certainty associated with the eventual interpretation of faultkinematics. However, this is unlikely to be a problem if bedthicknesses are >25 m thick.

� When vertical seismic resolution is low relative to typical bedthicknesses (i.e. under conditions of low peak frequency and

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high noise) the application of quantitative fault analyses can,strikingly, lead to misinterpretation of fault kinematics. Wedemonstrate examples where these analyses result in: i) failureto identify periods of fault inactivity and burial; ii) the inter-pretation of ‘extra’ periods of fault activity that did not occur; iii)incorrect calculation of throw gradients, adding significant un-certainty when trying to determine the degree to which thefault interacted with the free surface, other faults or mechanicalbarriers in the host rock. These issues may be of particular sig-nificance to hydrocarbon explorationists as they may lead tomisinterpretation of the timing of fault trap generation andbreach with respect to the timing of filling by hydrocarbons.

� When vertical seismic resolution is high relative to typical bedthicknesses (i.e. under conditions of high peak frequency andlow noise) the application of quantitative fault analyses gener-ally leads to fault growth histories being accurately constrained.

� When attempting to determine fault geometry, it should benoted that at low seismic resolution (i.e. low peak frequencyrelative to bed thickness) there may be a significant componentof error when trying to locate the fault tips or the lateral positionof the fault. In our study, fault heights could be underestimatedby 15e40%. In an applied sense, this may potentially lead tounderestimation of prospect volumes in a fault-dependent hy-drocarbon trap.

Acknowledgements

We thank Ikon Science for providing access to the RokDocseismic forward modelling software. Mark T. Ireland and ananonymous reviewer are thanked for providing constructive com-ments.We also thank Nick Holgate, CraigMagee, ArunaMannie andClara Rodriguez for providing frequency data at different depthsfrom seismic reflection datasets in natural sedimentary basins.

Appendix A. Supplementary data

Supplementary data related to this article can be found at http://dx.doi.org/10.1016/j.jsg.2014.05.021.

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