3D-basin modelling of the Hammerfest Basin (southwestern Barents Sea): A quantitative assessment of...

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Marine and Petroleum Geology 45 (2013) 281e303

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Marine and Petroleum Geology

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3D-basin modelling of the Hammerfest Basin (southwestern BarentsSea): A quantitative assessment of petroleum generation, migrationand leakage

Enmanuel Rodrigues Duran a,*, Rolando di Primio b, Zahie Anka b, Daniel Stoddart c,Brian Horsfield b

a Statoil ASA, Mølnholtet 42, 9414 Harstad, NorwaybGerman Research Centre for Geosciences (GFZ-Potsdam), Section 4.3-Organic Geochemistry, Telegrafenberg. House B, 14473 Potsdam, Germanyc Lundin Norway AS, Strandveien 50 D, 13366 Oslo, Norway

a r t i c l e i n f o

Article history:Received 31 May 2012Received in revised form14 March 2013Accepted 29 April 2013Available online 23 May 2013

Keywords:3D petroleum basin modellingHammerfest BasinHydrocarbon leakageReservoir pressure oscillationsGlacial cycles

* Corresponding author. Tel.: þ47 95362852.E-mail addresses: [email protected], edu

Duran).

0264-8172/$ e see front matter � 2013 Elsevier Ltd.http://dx.doi.org/10.1016/j.marpetgeo.2013.04.023

a b s t r a c t

3D basin modelling of the Hammerfest Basin (southwestern Barents Sea) was performed in order toaddress the masses of petroleum generated, accumulated and lost during the evolution of the basin.Calibration of the model, based on observed maturity (vitrinite reflectance) and present-day tempera-tures, took into account (1) two main erosion episodes: an OligoceneeMiocene event, due to tectonicuplift and a Plio-Pleistocene glacial erosion event, and (2) variable heat flow from Late Palaeozoic toCenozoic. The maturity levels of the main source rocks (Kobbe, Snadd and Hekkingen formations) werereconstructed and show that the highest maturities have been reached in the western and northwesternmargin of the basin. The beginning of petroleum generation in the Kobbe, Snadd and Hekkingen sourcerocks has been predicted to occur during Late Triassic, Early Cretaceous and Late Cretaceous, respectively.Our model reproduces satisfactorily the distribution of the main oil and gas fields and discoveries thathave been found in the study area. Our results indicate that two events of hydrocarbons redistributionoccurred in the basin. The first event resulted in the main oil redistribution episode, which took placeduring the OligoceneeMiocene associated with tectonic uplift and gas expansion, and the second wasrelated to the main gas leakage events that occurred during the PlioceneePleistocene glacialinterglacialcycles in general and the episodes of glacial retreat in particular. Glacial loading and unloading cyclesresulted in overpressure fluctuations in the subsurface reservoirs. Modelling results indicate that duringthese episodes a portion (at least 0.247 Gt) of thermogenic gas leaked from the main Stø Formationreservoirs reached the sediment interface and was released to the surface in the Hammerfest Basin.

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1. Introduction

The Barents Sea comprises a large epicontinental sea boundedby young passive continental margins to the west and north,developed during the Cenozoic opening of the Norwegian-Greenland Sea and Eurasia basin (Dimakis et al., 1998; Faleideet al., 1984). The southwestern Barents Sea contains several ba-sins, highs and platforms (Fig. 1), among which the Loppa High, theStappen High, the Bjørnøya Basin, the Tromsø Basin, the NordkappBasin, and the Hammerfest Basin rank as the most interestingexploration areas (Nøttvedt et al., 1993). The latter is the bestknown as petroleum exploration has proven a variety of petroleum

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systems and discoveries, with almost all the accumulations beingdominated by natural gas (Doré, 1995; Johansen et al., 1993; Larsenet al., 1993).

During the Cenozoic evolution the Barents Sea was affected bythe opening of the Norwegian-Greenland Sea, tectonic uplift anderosion, and the onset of glacial cycles (Dimakis et al., 1998; Vorrenet al., 1991). These latter events probably caused depletion of pe-troleum accumulations (Ohm et al., 2008). Exploration hasdemonstrated that most fields have residual oil saturation down toor below the current spillpoint of the structures, indicating that thereservoirs are underfilled at present-day (Augustson, 1993; Skagen,1993). Although it is widely accepted that glacial processes led tosignificant erosion in the Barents Sea (Dimakis et al., 1998), thepossible effects of glacial loading and unloading on the petroleumsystems have received little attention. Cavanagh et al. (2006)indicated that such events can have a profound influence on the

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Figure 1. The southwestern Barents Sea. The red square represents the area for which the Hammerfest Basin model was built (AFC: Asterias Fault Complex; BFC: Bjørnøyrenna FaultComplex; MFC: Måsøy Fault Complex; ND: Nordvarg Dome; NFC: Nyslepp Fault Complex; RLFC: Ringvassøy-Loppa Fault Complex; SD: Samson Dome; SvD: Svalis Dome; SLHFC:Southern Loppa High Fault Complex; TFFC: TromseFinnmark Fault Complex). (For interpretation of the references to colour in this figure legend, the reader is referred to the webversion of this article.)

E. Rodrigues Duran et al. / Marine and Petroleum Geology 45 (2013) 281e303282

reservoirs pressureetemperature conditions, potentially riskingtrap integrity. Thus, as a consequence of such events, the petroleumaccumulated in the reservoirs, may have leaked through the sealand eventually reached the shallower parts of the basin, wheregaseous hydrocarbons could have been trapped as gas-hydrates ifthe right pressureetemperature conditions existed. In addition,changes in the sediment-surface temperature during glacialeinterglacial cycles likely affected the stability conditions of gashydrates, resulting in the potential short termed liberation of gas(Chand et al., 2008; Lamarque, 2008; Mienert et al., 2005; Max andLowrie, 1993; Solheim and Elverhøi, 1993).

To investigate these processes we constructed a detailed 3Dnumerical petroleum system model of the Hammerfest Basin(southwestern Barents Sea, Fig. 1), which was used as input to: (1)quantify the amount and timing of liquid and gaseous hydrocarbongeneration in the basin, (2) reconstruct the possible migrationpaths and quantify the volumes trapped in the reservoirs, and (3)evaluate the possible leakage of petroleum (oil and gas) from thereservoir through geologic time. We expended particular effort onsimulating the response of the petroleum system to both tectonicevents (uplift and erosion) and glacialeinterglacial cycles. It is ouraim that the methodology presented in this contribution, despitethe uncertainties of the modelling approach, may help to improveour understanding of the influence of the glacialeinterglacial dy-namics on the leakage of thermogenic fluids from subsurface res-ervoirs in the Hammerfest Basin, southwestern Barents Sea.

2. Geological evolution

The geological evolution of the southwestern Barents Sea hasbeen described in great detail by several authors (Henriksen et al.,2011b; Glørstad-Clark et al., 2010; Ritzmann and Faleide, 2009;Faleide et al., 2008; Ohm et al., 2008; O’Leary et al., 2004;Gudlaugsson et al., 1998; Doré, 1995; Reemst et al., 1994; Johansenet al., 1993; Larsen et al., 1993; Nøttvedt et al., 1993; Dengo andRøssland, 1992; Linjordet and Grung-Olsen, 1992; Dalland et al.,1988; Berglund et al., 1986) and is briefly summarized here. Thisevolution has been influenced by several tectonic events fromDevonian to PaleoceneeEocene times, which produced a complexstructural and sedimentary architecture in the area, characterizedby basins, highs and platforms (Fig. 1).

Figure 2 depicts the generalized lithostratigraphy and the maintectonic events affecting the southwestern Barents Sea. Late Paleo-zoic rift basins were formed between Norway and Greenland and inthewesternBarents Sea along theNEeSWCaledonian trend (Faleideet al., 2008). The oldest sequence of rocks in thewestern Barents Seais composed of Late DevonianeEarly Carboniferous rift-fill alluvialfan and floodplain clastic sediments mixed with carbonates andevaporites. These rocks were deposited in half-grabens during theinitial phase of crustal extension between Greenland and Norway(Dengo and Røssland,1992). In the Late Carboniferous active crustalextension ceased. During the Late CarboniferouseEarly Permian theBarents Sea was one large epeirogenic subsiding basin and

Figure 2. Lithostratigraphy of the Hammerfest Basin (adapted from Ohm et al., 2008). The potential source rocks (SR) and reservoirs (R) that have been proposed and found in thearea, as well as the general overview of the geologic and tectonic history are also shown.

E. Rodrigues Duran et al. / Marine and Petroleum Geology 45 (2013) 281e303 283

sedimentation changed from continental to shallow-marine silici-clastic deposition and ultimately to carbonate and evaporite depo-sition (Dengo and Røssland, 1992; Roufosse, 1987; Rønnevik andJacobsen, 1984; Rønnevik, 1981). Basin subsidence conditions pre-vailed during Permian times (Berglund et al.,1986), while in the LatePermianeEarly Triassic crustal warping was followed by cyclic infillof shales and sandstones (Ørret Formation) over the carbonateplatform developed in the CarboniferousePermian time. During theEarly-Middle Triassic, the deposition of three progradational unitsoccurred: the Havert, Klappmys and Kobbe formations (Nøttvedtet al., 1993). The mid Triassic saw the development of an isolatedseawayovermuchof theArctic in general and in theBarents Sea areainparticular,with development of anoxia resulting in the depositionof source rocks (Spencer et al., 2011; Isaksen, 1996; Bjorøy and Hall,1983). The Late Triassic was characterized by regional subsidenceand deposition of the large sediment volumes of the Snadd andFruholmen formations, which are considered as possible sourcerocks, together with the Kobbe Formation (Faleide et al., 2008;Johansen et al., 1993; Nøttvedt et al., 1993).

The Lower and Middle Jurassic consist of deltaic sedimentsrepresented by the Tubåen, Nordmela and Stø formations(Johansen et al., 1993; Nøttvedt et al., 1993). A global sea level riseduring Middle Jurassic to Late Jurassic triggered the marine sedi-mentation of the Fuglen Formation and the organic-rich shales of

the Hekkingen Formation, which is considered as the main oil-prone source rock of the study area (Nøttvedt et al., 1993;Berglund et al., 1986). A shift in the extensional stress-field vector toNWeSE is recorded by the prominent NE AtlanticeArctic riftepisode in the Late JurassiceEarly Cretaceous (Faleide et al., 2008).Since Early Cretaceous, the Hammerfest Basin developed as aseparate structural and depositional entity characterized by uplifts,flexures and faulting (Berglund et al., 1986). Thereafter, the marineshale series of the Knurr and Kolje formations were deposited,followed by a renewed transgression and deposition of the KolmuleFormation during AptianeAlbian times. In the Late Cretaceous anew significant marine transgression occurred resulting in thedevelopment of a condensed section (Kveite Formation) across theBarents Shelf (Nøttvedt et al., 1993). Tectonic activity during thePaleogene is mostly related to the opening of the North Atlantic andArctic oceans (Dengo and Røssland, 1992). The final lithosphericbreak-up at the Norwegian margin occurred near the PaleoceneeEocene transition (Faleide et al., 2008) atw55 Ma (Ogg et al., 2008;Gradstein et al., 2005). A thick Paleocene to Eocene sequence (TorskFormation) covered wide parts of the western Barents Sea. DuringMid-Oligocene, the final phase of separation and the developmentof a passive margin took place along the western Barents Shelf, andthe eastern areas were subjected to deep erosion due to tectonicuplift (Berglund et al., 1986). Finally, a marked deterioration of the


northern hemisphere climate took place at about 2.5 Ma andregional glaciations set in (Vorren et al., 1991). The erosion ofsediments and loading of the lithosphere due to the large ice-caps,followed by unloading and uplift during deglaciation, characterizethe late stage evolution of the Barents Sea (Reemst et al., 1994).

The Late Cenozoic evolution is, therefore, an important periodfor the petroleum potential of the Barents Sea, since it was char-acterized by large uplifts and erosions (Reemst et al., 1994) thatreduced subsurface temperatures and thus stopped petroleumgeneration. However, petroleum migration and accumulation inreservoirs took place before the uplift and erosion in Early Paleo-gene time (Linjordet and Grung-Olsen, 1992) and migration is stillactive today due to several processes including general basin tilting,fracturing of the cap rocks and gas expansion (Ohm et al., 2008).Additionally, the glacial loading and unloading of the basin likelyalso influenced the petroleum systems, via the redistribution andpossible leakage of the accumulated petroleum.

3. Construction of the basin model

The 3D petroleum system model constructed here is a dynamicrepresentation of the geological processes that occurred in thesedimentary Hammerfest Basin and their influence on the organicmaturation and fluid flow over geological time. Some of the mostimportant processes are deposition, compaction, erosion, organicmatter maturation, petroleum generation, expulsion, migrationand accumulation. The basic modelling principles that we havefollowed, including the analytical equations considered for thesimulation of the geological processes have been described in detailby Hantschel and Kauerauf (2009).

The goal of quantitatively addressing basin-scale petroleumgeneration and the leakage rates through time requires a full 3Dreconstruction of the processes involved. Specifically 3D basinmodelling can: 1) correctly describe the total volume of sedimentaryunits in the basin, especially important for the petroleum systemelements (source rock, migration paths, structure, reservoir andseal); 2) reproduce the heat flow and temperature field in the pastand present, allowing thus the correct calculation of e.g. source rockmaturation through time; and 3) treat petroleum migration as a 3Dprocess, thus obtaining a better constraint of petroleummovement,entrapment and leakage. From a variety of petroleum migration al-gorithms, we have used a hybridmodel, which is based on a domaindecomposition to solve Darcy flow equations in areas of low per-meabilities andapplies aflowpathanalysis inhighlypermeable areas(Hantschel and Kauerauf, 2009; Hantschel et al., 2000). Thisapproach allows faster computing time andabetter estimation of thepetroleum distribution and accumulation. On the other hand, in thecase of very large 3Dmodels, details on the geological structures andtrapsmaybe lost due to limitationson the grid size versus computingtime. In our case a grid size of 2�2kmwas thebest, in order to keep abalance between computing time and structural model resolution.

As it is obvious in Figure 13 and described in Section 4.4, the 3Dmodel accurately reproduces the major fields and discoveries in thearea as well as their characteristic shapes. This reflects the quality ofthe maps used (derived from seismic interpretation), whichreproduce the main large structural traps in the form of 4-wayclosures. However, as also seen in Figure 13 the model predictssome additional minor accumulations untested by exploration sofar. The presence of new leads in our migration modelling results isnoteworthy, albeit of no major consequence for the main objectiveof our study, which is to perform a total mass balance of petroleumgeneration, migration and leakage. The quest for new leads in sucha study would require a focus on the definition of e.g. subtlestratigraphic or fault-sealed traps, a task which was not within thescope of this communication.

In such regional modelling efforts simplifications alwaysabound, since all detailed processes cannot be modelled with thesoftware used and also because a focus on the main objective, tohave a first order volume estimation of the petroleum generated,expelled, migrated and accumulated in reservoir, is necessary. Forthe present model such simplifications correspond to: 1) a stronglysimplified structural model, where fault complexes, detailed faulttrends and properties, fractures and micro-fractures present in theHammerfest basin were not accounted for in the model. The onlyfault complex that was included was the one located in thesoutheast (TromseFinnmark Fault Complex), which was requiredin order to define the Goliat field; 2) the lithological assignmentwas simplistic but realistic, here we considered a simple and ho-mogeneous facies distribution along each stratigraphic level; 3) wedid not model the presence of flowing water below the ice-sheetand the associated effects since the software cannot handle suchfeatures. Some other simplifications are mentioned in the followingsections. Despite these limitations our model results, as discussedbelow, satisfactorily reproduced the locations, rough volumetrics,phase state and relative proportions of oil and gas in the knownreservoirs of the Hammerfest basin.

3.1. Input data

We carried out the 3D petroleum system modelling of theHammerfest Basin (Fig. 3) using the PetroMod v.11� software(Schlumberger). The basin geometry and main sequences are rep-resented by 16 structural maps (kindly provided by Lundin NorwayAS) derived from seismic interpretation. These maps correspond tothe top or base of the main stratigraphic sequences, from the LatePermian (Ørret Formation) to the current seabed (Fig. 3, Table 1).

Other input definitions included are: ages for each stratigraphicunit, the predominant lithologies (thermal properties, compactionbehaviour, etc.) and the petroleum system elements, total organiccarbon (TOC) and hydrogen index (HI) values for each source rock(Table 1), kinetic models of petroleum generation and cracking,heat flow maps, boundary conditions, erosion maps and the inputfor glacial modelling (ice thickness maps and their evolutionthrough time). Additionally, vitrinite reflectance (VR) and temper-ature (T) data from 24 wells were collected from the different wellreports (geochemical and completion reports) available in the NPDwebsite (Norwegian Petroleum Directorate, 2009) and used for themodel calibration. Figure 4 shows the plots of VR and T datatogether with the linear regression (R2) trends for wells located inareas where some of the main petroleum accumulations of theHammerfest Basin are present. This allows us to assess the qualityof this data. In the following sections we will provide more detailson the individual input variables used in our model.

3.1.1. Lithology and petroleum system elementsThe chronostratigraphy was based on the International Geologic

Time Scale (International Commision on Stratigraphy, 2010; Ogget al., 2008; Gradstein et al., 2005) and the lithology assignmentof each unit (Table 1) was based on both well data (NorwegianPetroleum Directorate, 2009) and published work (Ohm et al.,2008; Gabrielsen et al., 1990). No lateral or vertical facies changeswere considered for individual stratigraphic units, except for themain reservoir e Stø Formation e , where a lateral facies variation(obtained from well reports) was introduced (Fig. 5) to betterapproximate the distribution of reservoir facies (i.e. the effectiveporous carrier beds as compared to non-carrier silty and shaly in-tervals of the same formation), the drainage areas and the migra-tion pathways.

Several petroleum exploration wells have found potentialreservoir and source rock sequences at various stratigraphic levels

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in the Hammerfest Basin (Norwegian Petroleum Directorate, 2009;Ohm et al., 2008; Doré, 1995; Larsen et al., 1993; Berglund et al.,1986). The main sequences with good source rock potential andconsiderable lateral extent are the Jurassic Hekkingen Formationand several intervals of Middle-Upper Triassic age corresponding toKobbe, Snadd and Fruholmen formations (He et al., 2012; Ohmet al.,2008; Doré, 1995; Linjordet and Grung-Olsen, 1992; Berglund et al.,1986). For our model, we considered the Jurassic Hekkingen For-mation and the Triassic Snadd and Kobbe formations as the mainsource rocks of the petroleum system (Fig. 3, Table 1). The entirethickness of each source rock was considered as a generating in-terval and the assigned TOC and HI correspond to the average of thevalues reported in previous studies (Ohm et al., 2008; Linjordet andGrung-Olsen,1992; Berglund et al.,1986). It is important to point outthat the following assumptions were made: 1) homogeneous facieswithin the individual source rock layers. 2) The whole layer (totalthickness) is considered as a source rock. The Hekkingen Formationsource rock has an average thickness of approximately 60 m in thewestern and northern part of the basin where the kitchen area is;while the Triassic Snadd and Kobbe formations have averagethicknesses around 800 and 400 m, respectively. This can also beobserved in the profiles shown in Figure I from the auxiliary ma-terial. While these thicknesses appear large, it must be consideredthat the source rock quality and potentials are low. 3) TOC and HIvalues were constant in a given source rock layer.

We did not consider older source rocks, since the geologicalplays in which these source rocks are present, i.e. Middle to UpperPermian, Carboniferous to Permian and Lower Carboniferous, havenot been identified in the Hammerfest Basin (Norwegian PetroleumDirectorate, 2011). In addition no maps deeper than the ØrretFormation map, which only represent the upper part of thePermian, were available for this study. On the other hand, there isno well data confirming the presence of Permian and older sourcerocks in the Hammerfest Basin, since the majority of the wellsperforated did not pass the Triassic.

In terms of the reservoirs, the largest proportion of hydrocarbonresources proven to date is contained in the Jurassic strata. Themajor discoveries are in the Lower-Middle Jurassic sandstones ofthe Stø Formation, which contains about 85% of all the NorwegianBarents Sea reserves (Doré, 1995). Additionally, the Tubåen For-mation (Early Jurassic) also has some reservoir potential (Berglundet al., 1986). The seal rocks are mainly represented by two shaleformations: the Fuglen Formation and the Hekkingen Formation(Linjordet and Grung-Olsen, 1992).

3.1.2. Kinetic modelsHydrocarbon generation was simulated using a database of

phase-predictive compositional kinetics (di Primio and Horsfield,2006), consisting of a 14 component scheme and including sec-ondary cracking (this type of compositional kinetic models aretermed PhaseKinetics). The compositional kinetics were measuredon samples of the main source rocks of the Barents Sea and thekinetic dataset was provided by GeoS4 GmbH-Germany. The Pha-seKinetics approach links source rock organic facies to the petro-leum type it generates. Using a combination of open- and closed-system pyrolysis techniques, bulk kinetic and compositional in-formation is acquired; gas compositions are tuned based on a GOR-gas wetness correlation from natural petroleum fluids; correctedcompositions are integrated into a 14-component compositionalkinetic model (C1, C2, C3, i-C4, n-C4, i-C5, n-C5, C6, C7eC15, C16eC25,C26eC35, C36eC45, C46eC55 and C55þ, the carbon chain length rangesare named pseudo-compounds, e.g. C7e15 is also called PseudoC10), which allows the prediction of petroleum properties. Thecomponents Pseudo C10 to PseudoC60þ can be subjected to sec-ondary cracking, with the assumption that the only compound

Table 1Facies definition input and lithology parameters for PetroMod�. Gp.¼ Group, Fm.¼ Formation, fms.¼ formations, PSE¼ Petroleum system elements, OR¼Overburden rock, UR¼Underburden rock, SR¼ Source rock, SeR¼ Sealrock, RR¼ Reservoir rock, Soc¼ Critical oil saturation, Sgc¼ Critical gas saturation, TOC¼ Total organic carbon, HI¼Hydrogen index. Values in brackets in the first column (name column) correspond to the deposition age of eachstratigraphic unit as assigned in the input. Stø Fm. 01 and Stø Fm. 02 are the names used to differentiate the sandstones and siltstones facies, respectively. The glacial ages (ice) are presented in Table 2.

Name PSE TOC (%) HI (mgHC/gTOC)

Lithology Thermal conductivity(W/m/K)

Rediogenic heat Heat capacity(kcal/kg/K)

Mechanicalproperties

Permeability[log(mD)]

At 20 �C At 100 �C U(ppm)

Th(ppm)

K (%) At 20 �C At 100 �C Density(kg/m3)

Initialporosity (%)

Nordland Gp. (0.01e0 Ma) OR Siltstone (organic lean) 2.05 1.99 2.00 5.00 1.00 0.22 0.25 2720 55 0.71Torsk Fm. (65.5e30 Ma) OR Shale (organic lean, typical) 1.70 1.74 3.70 12.00 2.70 0.21 0.24 2700 70 �1.00Kveite-Kviting fms.

(96.6e65.5 Ma)OR Siltstone (organic lean) 2.05 1.99 2.00 5.00 1.00 0.22 0.25 2720 55 0.71

Kolmule Fm. (120e96.6 Ma) OR Shale (organic lean, silty) 1.77 1.79 3.00 11.00 2.60 0.21 0.24 2700 67 0.50Kolje Fm. (130e120 Ma) OR Shale (typical) 1.64 1.69 3.70 12.00 2.70 0.21 0.24 2700 70 �1.00Knurr Fm. (140.2e130 Ma) OR Shale (typical) 1.64 1.69 3.70 12.00 2.70 0.21 0.24 2700 70 �1.00Hekkingen Fm.

(155.6e140.2 Ma)SR 10 300 Shale (organic rich, 8% TOC)

Soc ¼ Sgc1.20 1.37 10.00 11.00 2.90 0.21 0.25 2500 70 �1.00

Fuglen Fm. (167.7e155.6 Ma) SeR Shale (organic lean, siliceous,typical)

1.90 1.88 2.00 4.50 2.00 0.21 0.24 2710 70 1.30

Stø Fm. 01 (184e167.7 Ma) RR Sandstone (typical) 3.95 3.38 1.30 3.50 1.30 0.20 0.24 2720 41 4.33Stø Fm. 02 (184e167.7 Ma) OR Siltstone (organic lean) 2.05 1.99 2.00 5.00 1.00 0.22 0.25 2720 55 0.71Nordmela Fm. (196.5e184 Ma) OR Siltstone (organic lean) 2.05 1.99 2.00 5.00 1.00 0.22 0.25 2720 55 0.71Tubåen Fm. (200e196.5 Ma) RR Sandstone (clay poor) 5.95 4.85 0.70 2.30 0.60 0.20 0.23 2700 42 4.84Fruholmen Fm. (210e200 Ma) OR Siltstone (organic rich,

2e3% TOC)2.00 1.96 2.50 6.50 2.00 0.22 0.26 2700 55 0.71

Snadd Fm. (237e210 Ma) SR 2 150 Siltstone (organic rich,2e3% TOC) Soc ¼ Sgc

2.00 1.96 2.50 6.50 2.00 0.22 0.26 2700 55 0.71

Kobbe Fm. (245e237 Ma) SR 3 200 Siltstone (organic rich,2e3% TOC) Soc ¼ Sgc

2.00 1.96 2.50 6.50 2.00 0.22 0.26 2700 55 0.71

Havert-Klappmys fms.(260e245 Ma)

UR Shale (organic lean, silty) 1.77 1.79 3.00 11.00 2.60 0.21 0.24 2700 67 0.50

Ørret Fm. (265e260 Ma) UR Siltstone (organic lean) 2.05 1.99 2.00 5.00 1.00 0.22 0.25 2720 55 0.71Basement UR Basement 2.72 2.35 0.00 0.00 0.00 0.19 0.22 2750 5 e

Ice None Ice-sheet 2.22(0 �C)

2.39(�20 �C)

0.00 0.00 0.00 0.49(0 �C)

0.46(�20 �C)

917 1 0.00

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Figure 4. Summary of temperature and vitrinite reflectance data, with the respective linear regressions coefficient (R2), used to evaluate the dispersion of the data used for modelcalibration. The data belong to the geochemical reports of the Norwegian Petroleum Directorate (2009), and correspond to the wells located in areas where some of the main fieldsof the Hammerfest Basin are present (N ¼ Number of samples or measurements).


generated is methane. The assumption that methane is the mainproduct generated by secondary cracking is supported by naturaldata as reported by di Primio et al. (2011). The kinetics of this oil-to-gas cracking reaction is based on those of Pepper and Corvi (1995a,b). The calculation of petroleum phase behaviour under the sub-surface conditions of petroleum migration and entrapment ispossible using these methods in combination with modern basinmodelling software.

3.1.3. Heat flowFor the reconstruction of the basin’s thermal history the basal

heat flow evolution needs to be defined. The Barents Sea has beeninfluenced by four phases of lithospheric stretching: DevonianeCarboniferous (375e325 Ma), Triassic (245e241 Ma), JurassiceCretaceous (157e97 Ma), and PaleoceneeEarly Eocene (60e50 Ma)(Skogseid et al., 2000; Reemst et al., 1994). Except for the Triassic(broad regional subsidence), these phases correspond to riftingevents where heat flow is expected to have been higher ascompared to the present-day value. The stretching factors (b) arebetween 1.4 and 1.6 (Reemst et al., 1994), which correspond to heatflow peaks of approximately 60e80 mW/m2 (Hantschel andKauerauf, 2009). Considering heat flow maxima or an increase inthe total magnitude, followed by decay to a background value, weset up a variable heat flow model from Late Paleozoic to Cenozoic,which provides the basis for the thermal history calibration.Therefore, the heat flow was assigned taking into account threeelevated heat flow values in correlation with the present-daymagnitude, associated with the rifting phases (140 and 65 Ma)and the regional subsidence (250 Ma) that occurred in the BarentsSea, and a fourth heat flow increase related to neotectonics andcompressional deformation (Fjeldskaar et al., 2000) (Fig. 6a),following the approach of Cavanagh et al. (2006).

The background heat flow value corresponds to the present-dayheat flow reported in the literature for this area (Sundvor et al.,2000). Published heat flow maps (Sundvor et al., 2000; Sundvorand Eldholm, 1992) reveal that the average landward value on themarginal escarpments is 57 mW/m2. A few measurements east ofthe Senja Fracture Zone are not statistically significant, but include

several values below 50 mW/m2 (Sundvor et al., 2000). Shallowdrill hole measurements yield values from 54 to 74 mW/m2

(Sundvor et al., 2000; Eldholm et al., 1999). Cavanagh et al. (2006)tested a heat flow in the range of 50e80 mW/m2 in their 2D modelaround Snøhvit field. Their maturity model indicated that valuesbetween 60 and 65 mW/m2 are required at maximum burial tomatch vitrinite reflectance data.

As discussed above a variable heat flow history was defined andassigned to themodel using heat flowmapswith values between 58and 75 mW/m2 in order to reproduce the thermal history trendpresented in Figure 6a (black line). Initially, the heat flow valueswere homogenously distributed throughout the basin (Fig. 6c).However, since calibrationwith well temperature data could not beachieved in the central parts of the basin, it was necessary todecrease the heat flow values for those areas by a magnitude of5 mW/m2, as shown in Figure 6b (black line) and d. Using this newheat flow distribution we achieved a good calibration of the model(discussion of model calibration is presented later in Section 4.1). Intotal seven heat flows maps were created with a similar heat flowpattern distribution, but with different values, andwere assigned todifferent ages in order to reproduce the paleo heatflow trend shownin Figure 6a, b. From Middle Jurassic to Early Barremian, a domedeveloped in the central partof theHammerfest Basin, parallel to thebasin axis. This process was controlled by the dominant east-west-trending fault system in the central part of the basin axis(Linjordet and Grung-Olsen, 1992; Gabrielsen et al., 1990). Thisstructure certainly could have affected the paleo-thermal heat flowdistribution in the basin, andmay have been the responsible for theheat flow variation necessary for our model calibration. We carriedout a sensitivityanalysis considering threepossibleheatflowhistoryscenarios: low, medium and high (heat flow 1, 2 and 3 in Fig. 6a, b),with the average background values being 50, 58, and 66 mW/m2,respectively; and45, 53, and61mW/m2 in the central part (Fig. 6a, b,d). The results of this sensitivity study are reported in Section 4.2.

3.1.4. Sediment water interface temperature (SWIT)The upper-boundary condition of heat transfer in sedimentary

basins is given by the temperatures either at the sub-aerial surface

Figure 5. Lateral facies variation of the Stø Formation unit. The two plots at the bottom correspond to the porosity (bottom left) and permeability (bottom right) behaviour throughtime for the two main facies in two different locations of the basin (ellipses outline positions of the respective data).


or at the sedimentewater interface, and is affected by the waterdepth, the paleogeographic position, and oceanic currents. In ourmodel, the pre-glacial (from Late Paleozoic to Pleistocene) SWITvalues are between 25 and 10 �C (Fig. IIa, auxiliary material), whichwere assigned based on the timeelatitude diagram proposed byWygrala (1989).

The upper-boundary thermal condition during the Pleistoceneglacialeinterglacial periods is represented by a temperature trend(Fig. IIb, auxiliary material). The interglacial SWIT was assumed tobe around 3 �C, since temperatures around this magnitude havebeen proposed for these stages (Archer et al., 2004; Siegert et al.,2001) and also when this value was assumed, a good interpola-tion of the temperature in the sediment-ice contact is achieved inthe model for the glacial periods. Regarding the glacial periods theupper-thermal boundary is represented by the temperature at theinterface between the sub-aerial ice-sheet and the atmosphere.Mean annual surface temperatures from numerical ice-sheet

modelling range between �16 and �35 �C for ice thickness be-tween 750 and 1000 m (Siegert and Marsiat, 2001). For our modelwe fixed these values as �15 �C for ice thickness around 500 m(Fig. IIb, auxiliary material) and �45 �C for ice thickness ofw1750 m (Fig. IIb, auxiliary material), obtaining temperatures be-tween 0 and �1 �C at the interface ice-sediment. These tempera-tures at the ice-base are calculated by the software based on the icethickness and its thermal properties as well as on the heat flow.Present-day SWIT is around 6 �C, this is based on benthic forami-niferal composite oxygen isotope records (Mienert et al., 2005;Archer et al., 2004) and the annual temperature for the south-western part of the Barents Sea (National Oceanographic DataCenter, 2011; Henrich and Baumann, 1994; Loeng, 1991).

3.1.5. Uplift and erosional eventsThe main uplift and erosion of the Barents Sea can be related to

two important regional events: I) the structural development

Figure 6. Heat flow definition. a) General heat flow trends as a function of geologic time (dots in the black curve) applied in the modelling. The three curves correspond to the threeheat flow scenarios considered for the sensitivity analysis, with a maximum e heat flow 3 e , medium e heat flow 2 e and minimum e heat flow 1 e trends. b) Same heat flowtrends as in (a), but with lower values, necessary to calibrate the model in the central parts of the basin. c) Example of initial heat flow maps definition (assuming no lateralvariations). d) Final regional distribution of heat flow map trends, with lower trends in the central parts of the basin.


linked to the rifting, break-up, and subsequent opening of theNorwegian-Greenland Sea during the OligoceneeMiocene, and II)the glacial activity during the Late Cenozoic (PlioceneePleistocene)(Cavanagh et al., 2006; Dimakis et al., 1998; Riis, 1996; Knutsenet al., 1993; Richardsen et al., 1993; Nyland et al., 1992; Riis andFjeldskaar, 1992; Vorren et al., 1991; Berglund et al., 1986). Ac-cording to apatite fission track analysis (AFTA) the OligoceneeMiocene uplift and erosion phase followed the maximum burialof the basin (around 30 Ma) and apparently had a greater magni-tude e by about 500 m e than the PlioceneePleistocene phase(Nyland et al., 1992). However, Cavanagh et al. (2006) proposed theQuaternary glacial erosion as the most important of the Cenozoicexhumations, since its inclusion into their model allowed the bestthermal calibration. Also biostratigraphic datings on the sedimentsof thewedge on the Senja Ridge indicate that a strong erosion eventwas due to glaciations (Nyland et al., 1992).

In the southwestern Barents Sea, the estimated values of thetotal Cenozoic erosion derived from different methods such asvitrinite reflectance estimation, AFTA, sandstones diagenesis, andmass balance calculations range from 500 to 3000 m, increasingfrom west to east and to the north and northwest. In the Ham-merfest Basin the erosion reaches magnitudes between 1000 and1500 m (Henriksen et al., 2011a; Ohm et al., 2008; Reemst et al.,1994; Nyland et al., 1992; Riis, 1992; Berglund et al., 1986). In ourmodel we divided the total Cenozoic erosion into the two erosionalevents previously described: The OligoceneeMiocene erosionphase due to tectonic uplift (from 30 to 15 Ma); and the PlioceneePleistocene phase due to glaciations (between 2.50 and 0.01 Ma).

Since published erosion maps (Henriksen et al., 2011a; Ohm et al.,2008; Dimakis et al., 1998; Nyland et al., 1992; Riis, 1992; Riis andFjeldskaar, 1992) describe the total eroded thickness during theCenozoic, we had to subdivide total erosion into two episodes ofinterest: OligoceneeMiocene and PlioceneePleistocene. We used asimilar erosional pattern for the two phases, but with a 2:1magnitude relationship (Fig. 7) which provided the best calibrationto measured vitrinite reflectance and temperature data. Sensitivityof the model to the erosion magnitudes was evaluated throughhigh, medium and low erosion scenarios; erosion a, b and c,respectively in Figure 7. The highest and lowest values for eachscenario are: 1500e300 m, 1200e150 m, and 900e0 m.

3.1.6. Ice sheet modelling during glaciations and deglaciationsSeveral periods of ice-sheet growth and retreat occurred during

the Late Cenozoic. A deterioration of the climate in the northernhemisphere started at around 2.50 Ma, which resulted in regionalglaciations (Jansen and Sjoholm, 1991; Vorren et al., 1991). For theperiod between 2.50 and w1.00 Ma ice volumes changed pre-dominantly in 41,000 year cycles, while from w1.00 Ma to 0.01 Ma100,000 year cycles were predominant (Kukla and Cílek, 1996;Solheim et al., 1996). During this last period (w1.00e0.01 Ma)larger glacial cycles occurred with the development of thicker ice-sheets and an advance to the south of the Barents Sea (towards theHammerfest Basin) and to the shelf edges (Knies et al., 2009). Forthis reasonwe considered andmodelled the ice-sheet developmentin the Hammerfest Basin only between 1.10 and 0.01 Ma. Theglacialeinterglacial periods between 1.10 and 0.12 Mawere defined

Figure 8. Definition of the ice thickness evolution. a) Ice thickness. Three ice-sheetthicknesses were considered in order to evaluate the sensitivity of the model output.For the Weichselian period (between 0.12 and 0.01 Ma) no thickness variation wasconsidered since this period has been well constrained and several models give anestimate of the thickness (details in Section 3.1.6). b) Glaciation history through fivemegacycles including isostatic response. The MC1 also includes the Weichselian period


following the oxygen-isotope stages, and considering a subdivisionin five megacycles (MC5 to MC1, Fig. 8) as described by Kukla andCílek (1996), with an acceptable ice periodicity based on theMilankovitch theory. Considering that the Earth’s climate systemhas a dominant 100,000 year cycle (Henrich and Baumann, 1994;Broecker and Denton, 1990) an ice megacycle length of roughly100,000 years was assumed (Fig. 8, Table 2). For each megacyclefour phases of equal time length were defined: a phase of icegrowth, a phase of ice stability, a phase of ice retreat and an ice-freephase (interglacial period). Therefore, two important parametersnecessary to model glaciation processes have been defined: dura-tion of the glaciation and extent of the ice cover. A third importantparameter is the ice thickness for which there are no real con-straints for the period prior to 0.12 million years. Hence, we eval-uated three scenarios of ice thickness to address the sensitivity ofthe system to this parameter; ice thickness of 1000, 1250 and1500 m; 1, 2 and 3, respectively in Figure 8, the latter being in thesamemagnitude as the value reported for the last glacial maximum(Svendsen et al., 2004; Siegert et al., 2001).We did not consider ice-sheet topography variations in our model, because regional icethickness maps report minor thickness variability over the studyarea, at least for theWeichselian period (Siegert et al., 2001; Siegertand Marsiat, 2001; Siegert et al., 1999).

For the Weichselian glaciation, between 0.12 and 0.01 Ma, theduration, extent and ice thickness of each glacial cycle have beenwell defined in several studies (Clark and Mix, 2002; Siegert et al.,2001; Siegert andMarsiat, 2001; Siegert et al., 1999; Svendsen et al.,1999; Lambeck, 1995; Elverhøi et al., 1993). We used the reportedvalues as input for the model (Table 2) and defined four glaciation-phases with an increasing-intensity (Fig. 8, Table 2), from Early toLateWeichselian, as proposed by Siegert et al. (2001). Themodelledice-sheet was defined as a zero-porosity and effectively incom-pressible and impermeable lithology; with the density of frozenwater (the physical properties used are shown in Table 1).

(Table 2).

4. Results

4.1. Calibration

We built a total of 9 models on which carried out sensitivityanalyses for the heat flow and erosion, described in the previousSections 3.1.3 and 3.1.5. As discussed by Cavanagh et al. (2006) thepresent day temperature field of the Hammerfest basin is in ther-mal disequilibrium due to the rapid glacial erosion, such that pre-sent temperatures are comparatively high. Due to this effect correcttemperature calibration of the models requires inclusion of theerosion history. Hence, the scenario that allows the best calibrationto the T data corresponds to a background heat flow between 53and 58 mW/m2 (heat flow 2 in Fig. 9a, c) and erosion between300 m (200 Oligo-Miocene : 100 Plio-Pleistocene) and 1500 m(1000 Oligo-Miocene : 500 Plio-Pleistocene), i.e. erosion scenario“a” (Fig. 9b, d). The results obtained when the different erosionscenarios were evaluated did not show a large variation for thetemperature calibration as seen in Figure 9b; however it is possibleto say that the best calibration is observed for the major erosion,this means erosion “a”. Regarding calibration to the VR data, it isimportant to mention that the results show the particular distri-bution or variation observed in VR calibration. Specifically this re-fers to the fact that when a variation in the heat flow scenario is

Figure 7. Erosion maps created and loaded into the modelling software for the two eroPleistocene (associated to the glaciations). The same erosion trend was used for both events,phase). Three erosion scenarios were also tested in the sensitivity analysis, corresponding to aThree iso-erosion lines are shown for each scenario.

performed a rotation of the VR trend is observed. On the otherhand, when a variation on the erosion scenario is performed atranslation of the VR is observed. This effect is probably not easy tovisualize due to the big dispersion on the well data (black dots onFig. 9c, d) and also to the fact that erosion magnitudes are differentaround the basin and lower towards the central-western part of thebasin (Fig. 7). However, the VR calibration results also suggest thesame conclusion observed for the temperature calibration. Onother words, the scenarios that better calibrate the model corre-spond to the medium heat flow scenario or heat flow 2 and to theerosion a. We also varied the relative erosion magnitudes in theOligoceneeMiocene and PlioceneePleistocene from 2:1 to 1:2. Theerosional pattern and the erosion magnitudes were maintained asshown in Figure 7. The results of this sensitivity study did not showa large range of variation between both scenarios (Fig. III, auxiliarymaterial) confirming that vitrinite reflectance is not sensitive to thetiming of erosion.

4.2. Sensitivity analysis

Through the sensitivity analysis conducted we determined thevariability of the model output in terms of petroleum (oil þ gas)mass variations with respect to the variation in the input

sion events considered in our models: OligoceneeMiocene (tectonic) and Plioceneebut with different magnitudes (2/3 of total erosion corresponding to the Oligo-Miocenemaximum (erosion a), medium (erosion b) and minimum (erosion c) erosion intensity.

Table 2Ice sheet periodicity used as input for the 3D basin model. The thickness for each glaciation is shown, together with the different events considered in each megacycle and theduration. MC ¼ Megacycle.

Name Ice MC Thickness (m) Age growth (Ma) Duration (Ma) Age stable (Ma) Duration (Ma) Ice decay (Ma) Duration (Ma) Interglacial (Ma) Duration (Ma)

Ice I MC5 1500 1.10e1.05 0.05 1.05e1.00 0.05 1.00e0.95 0.05 0.95e0.90 0.05Ice II MC4 1500 0.90e0.85 0.05 0.85e0.80 0.05 0.80e0.75 0.05 0.75e0.70 0.05Ice III MC3 1500 0.70e0.65 0.05 0.65e0.60 0.05 0.60e0.55 0.05 0.55e0.50 0.05Ice IV MC2 1500 0.50e0.42 0.08 0.42e0.34 0.08 0.34e0.26 0.08 0.26e0.18 0.08Ice V MC1 1500 0.18e0.16 0.02 0.16e0.15 0.01 0.15e0.13 0.02 0.13e0.12 0.01Ice VIa MC1 480 0.12e0.11 0.01 e e 0.11e0.10 0.01 e e

Ice VIb MC1 750 0.10e0.09 0.01 e e 0.09e0.08 0.01 e e

Ice VIc MC1 550 0.08e0.07 0.01 0.07e0.02 0.05 0.02e0.01 0.01 0.01 to present-day e

Ice VId MC1 1250 0.07e0.06 0.01 e e 0.06e0.05 0.01 e e

Ice VIe MC1 1750 0.03e0.02 0.01 e e 0.02e0.01 0.01 0.01 to present-day e


parameters mentioned in Sections 3.1.3, 3.1.5, and 3.1.6 (heat flow,erosion and ice thickness, respectively). Since the kinetics imple-mented in our model consist of 14 components, all the masses re-ported for oil correspond to the sum of the liquid hydrocarbons(hexane, C7eC15, C16eC25, C26eC35, C36eC45, C46eC55 and C55þ) andthe masses for gas correspond to the sum of the gaseous hydro-carbons (methane, ethane, propane, i-butane, n-butane, i-pentaneand n-pentane). The model results, with respect to the masses ofpetroleum generated, are more sensitive to the heat flow historyand the erosion scenarios used. Assuming the same erosion sce-nario e erosion a e and varying the heat flow history according tothe three scenarios previously described, we conclude that themasses generated vary as follows: 139 � 24 Gt of petroleum(oil þ gas); 74 � 3 Gt for the total amount of oil and 65 � 22 Gt forthe gaseous hydrocarbons (Table 3). It is clear that the masses beingmost affected by this parameter correspond to those of the gaseoushydrocarbons. The variations in relation with the masses of thepetroleum expelled (see below for details) are more or less in thesame range, being: 61 � 32 Gt for the total amount of petroleumexpelled, 28� 14 Gt for the total oil expelled, and 33� 19 Gt for thetotal amount of gas expelled (Table 3). If we consider the possibleeffect on themasses accumulated in the reservoirs, we observe thatthe variation is not considerable, ranging between 0.59 � 0.01 and0.30 � 0.02 Gt (Table 3).

Assuming the same heat flow scenario e heat flow 2 e andlooking at the variation of the results in response to the threeerosion scenarios considered, we observed that the variability ofpetroleum masses is less sensitive to erosion magnitudes, resultingin a variability of the masses generated as follow: 131 � 12 Gt forthe total amount of petroleum (oil þ gas), 72 � 4 Gt for the oilgenerated, 58 � 7 Gt for the gaseous hydrocarbons (Table 4).Variation in the amount of the petroleum expelled is more or less inthe same magnitude, i.e.: 51 � 11 Gt, 25 � 5 Gt, 26 � 6 Gt, for thetotal amount of petroleum, the total amount of oil and the totalamount of gas expelled, respectively (Table 4). Once again the re-sults with respect to the masses accumulated in the reservoirsshow a smaller deviation and are more accurate; the variability is0.65 � 0.07 Gt for petroleum, 0.36 � 0.07 Gt for oil and 0.29 � 0.01for gas (Table 4). Therefore, the masses generated are more sensi-tive to heat flow variations than to the variations in erosion mag-nitudes, since the first is a parameter that directly influences thethermal history of the basin, and thus the temperature and thermalmaturation of the source rocks. With respect to thermogenic gaslosses from the reservoirs, the model is more sensitive to erosionwhere a deviation of 0.17 � 0.09 Gt has been calculated (Table 4).These results support our interpretation pointing out to the factthat structural tilting and the changes in the temperature andpressure conditions in the reservoir resulting from uplift anderosion dominantly control the leakage dynamics from theaccumulations.

Since the glaciation processes took place towards the end of thegeological history of the basin after maximum burial, the sensitivityanalysis with respect to ice thickness (Section 3.1.6) showed thatthere is no influence on the amounts of petroleum generated, noraccumulated. The simulations with three different ice-sheetthicknesses (1500, 1250 and 1000 m) show a variability of theamount of petroleum accumulated in the Stø Formation of0.601 � 0.002 (0.299 � 0.001 Gt for oil 0.301 � 0.002 for gas;Table 5). On the other hand, the variability of the amount of gas lostfrom the reservoirs was calculated to be 0.247 � 0.003 Gt.

Based on the expelled and accumulated volumes determined(Tables 3 and 4) an accumulation efficiency of roughly 1.2% can becalculated for the Hammerfest basin (using the mean expelled andaccumulated values from Table 4). This accumulation efficiency isrelatively low as compared to values listed by Magoon and Valin(1994), they are, however, comparable to values listed for theMandal-Ekofisk petroleum system of the Central Graben, Norwe-gian North Sea (Magoon and Valin, 1994). Accordingly we assumethat the values calculated based on our modelling efforts arerealistic.

The following discussion of results is based on the model withthe largest erosione erosion ae and ice thicknesse 1500me , andwith the medium heat flow e heat flow scenario 2 e , which pro-vided the most consistent regional calibration.

4.3. Source rock maturation, petroleum generation and expulsion

Figure 10aeb shows the modelled burial and maturation historyfor each source rock derived from a pseudo-well located in thenorthwestern margin of the basin, where the three source rocksreached the highest maturity level (Fig. 11). Assuming the onset ofoil windowmaturity at Roz 0.50% (Tissot andWelte, 1984, p. 543),generation of oil in the Kobbe Formation would have started in theLate Triassic (w215 Ma), in the Snadd Formation in Early Creta-ceous (w125 Ma), and in the Hekkingen Formation in Late Creta-ceous (w95 Ma) time.

Predicted present-day transformation ratio (TR), defined as theratio which reflects the fraction of petroleum (oilþ gas) potential ofthe kerogen realized (Tissot and Welte, 1984, p. 218), indicates thatthe Hekkingen Formation has reached the oil window at thewestern and northwestern margins of the basin. This is manifestedin the pseudo-well plot shown in Figure 10b, by VR ofw0.65% and aTR around 25%. In the central, southern and eastern parts of thebasin this source rock is predicted to be thermally immature(Fig. 11a), supporting earlier interpretations (Ohm et al., 2008;Doré, 1995). The potential Triassic source rocks have reachedcomplete kerogen transformation in almost the entire basin, withthe Kobbe Formation being the one reaching the highest maturity(Fig. 11b, c). This indicates that at least part of the gaseous hydro-carbon accumulations present in the basin may have been sourced

Figure 9. Calibration results. a) & b) Examples of model calibration to temperature in relation to the three heat flow and erosion scenarios (description in Sections 3.1.3 and 3.1.5). c)& d) Examples of model calibration to vitrinite reflectance also in relation to the variation of the heat flow and erosion scenarios. Shadowed areas correspond to the best calibrationzone. The plots are from a circular area around the wells shown in a) and b). The wells are the same for c) and d).


Table 3Comparison of the volumetrics results for the three models with different heat flow scenarios (Details in Section 3.1.3). For this comparison it was keep it the same erosionpattern (erosion a) and the same ice thickness (1500 m defined for MC5, MC4, MC3, MC2 and the first glaciation of MC1). Gt¼ Gigatonnes, SD¼ Standard deviation. The valuesshown in brackets correspond to the detailed masses of each source rock, i.e. Kobbe Formation þ Snadd Formation þ Hekkingen Formation masses. The value outside thebrackets corresponds to the sum of these three masses.

Masses generated (Gt)

Petroleum generated Oil generated Gas generated

Heat flow 1 (58 þ 47 þ 9) 114 (33 þ 31 þ 7) 71 (25 þ 16 þ 2) 43Heat flow 2 (64 þ 63 þ 16) 143 (28 þ 37 þ 12) 77 (36 þ 26 þ 4) 66Heat flow 3 (66 þ 71 þ 25) 161 (23 þ 35 þ 8) 75 (43 þ 35 þ 8) 86Mean 139 74 65SD 24 3 22

Masses expelled (Gt)

Petroleum expelled Oil expelled Gas expelled

Heat flow 1 (17.0 þ 10.8 þ 0.8) 28.6 (7.2 þ 6.8 þ 0.5) 14.5 (9.8 þ 4.0 þ 0.3) 14.0Heat flow 2 (35 þ 24 þ 3) 62 (14 þ 14 þ 2) 30 (20 þ 11 þ 1) 32Heat flow 3 (47 þ 40 þ 6) 93 (17 þ 21 þ 3) 41 (30 þ 19 þ 3) 52Mean 61 28 33SD 32 14 19

Masses accumulated in reservoir (Gt)

Petroleum in Stø Fm. Oil accum. in Stø Fm. Gas accum. in Stø Fm.

Heat flow 1 0.59 0.27 0.32Heat flow 2 0.60 0.30 0.30Heat flow 3 0.58 0.30 0.28Mean 0.59 0.29 0.30SD 0.01 0.02 0.02

Table 4Comparison of the volumetrics results for the three models with different erosionscenarios (Details in Section 3.1.5). For this comparison it was keep it the same heatflow history (heat flow 2) and the same ice thickness (1500 m defined for MC5, MC4,MC3, MC2 and the first glaciation of MC1). Gt ¼ Gigatonnes, SD ¼ Standarddeviation.

Masses generated (Gt)

Petroleumgenerated

Oil generated Gas generated

Erosion a 143 77 66Erosion b 130 72 58Erosion c 119 68 51Mean 131 72 58SD 12 4 7

Masses expelled (Gt)

Petroleumexpelled

Oil expelled Gas expelled

Erosion a 62 30 32Erosion b 49 24 25Erosion c 41 20 21Mean 51 25 26SD 11 5 6


Petroleumin Stø Fm.

Oil accum. in Stø Fm. Gas accum.in Stø Fm.

Erosion a 0.60 0.30 0.30Erosion b 0.62 0.34 0.28Erosion c 0.72 0.43 0.29Mean 0.65 0.36 0.29SD 0.07 0.07 0.01

Gas lost from Stø Fm. Gas outflow (model top)

Erosion a 0.24 0.3Erosion b 0.21 0.3Erosion c 0.07 0.1Mean 0.17 0.2SD 0.09 0.1


from these Triassic source rocks. Additionally, Dieckmann et al.(1998) established that secondary cracking of oil to gas is ex-pected to start after the temperature boundary of 170 �C is reachedand/or exceeded. The three source rocks considered in our model,mainly the Triassic Kobbe Formation, have exceeded this boundaryin the western and northwestern margin by the time when hy-drocarbons started to accumulate in reservoir (Paleocene). Thissupports the presence of significant sources for thermogenic gas inthe basin. Figure 11f shows, in fact, a decrease of oil masses from theKobbe Formation after 100 Ma, which indicates the occurrence ofsecondary cracking of residual oil and generation of gaseoushydrocarbons.

Our 3D model allows a first order mass/volume estimation ofthe petroleum generated through geologic time in the Hammerfest

Table 5Comparison of the volumetrics results for the three models with different icethickness for the MC5, MC4, MC3, MC2 and the first glaciation of MC1 (Details inSection 3.1.6). For this comparison it was keep it the same heat flow history (heatflow 2) and the same erosional pattern (erosion a). Gt ¼ Gigatonnes, SD ¼ Standarddeviation.


Petroleumin Stø Fm.

Oil accum.in Stø Fm.

Gas accum.in Stø Fm.

Ice 1 (1000 m) 0.600 0.301 0.299Ice 2 (1250 m) 0.603 0.300 0.303Ice 3 (1500 m) 0.599 0.298 0.302Mean 0.601 0.299 0.301SD 0.002 0.001 0.002

Gas lostfrom Stø Fm.

Gas outflow(model top)

Ice 1 (1000 m) 0.250 0.300Ice 2 (1250 m) 0.245 0.288Ice 3 (1500 m) 0.244 0.289Mean 0.247 0.292SD 0.003 0.007

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Basin as it considers the main Triassic and Jurassic source rocksvolumetrically. The predicted total amount of petroleum (oil þ gas)generated by the three source rocks is around 142 Gt (Fig. 10c), ofwhich approximately 66 Gt corresponds to gas and 76 Gt to oil.Figure 11d, e, f shows the detailed amount of oil and gas generatedby each source rock. The densities of oil and gas as separate phasesat subsurface conditions are calculated in PetroMod based on thecompositional predictions of the kinetic models and the respectivephysical properties. Volumes are then calculated based on the in-situ density of the individual phases. An estimation of the totalvolumes of oil and gas generated by the Hekkingen, Snadd andKobbe Formations, based on the model results are around140 billion m3 and 300 billion m3, respectively.

In the modelling software used petroleum expulsion isconsidered as a function of the critical oil (Soc) and gas saturation(Sgc) once the adsorptive capacity of the kerogen is exceeded. Thepetroleum saturation defines the fraction of pore space which isused for flow (England et al., 1987), thus the critical oil and gassaturations are threshold values that distinguish between initialsaturations, which must be overcome to allow flow, and residualsaturations, which are immobile. The critical oil saturation isimportant because it defines the threshold value that must beovercome in order to initiate the movement of oil and expulsionfrom the source rock. Critical gas saturations are usually assumedto be negligible, allowing every gas bubble to be mobile(Hantschel and Kauerauf, 2009). In the application of PhaseKi-netic models of petroleum generation we consider that under thepressure and temperature conditions the fluids generated aremonophasic (di Primio et al., 1998). Accordingly an adsorptionmodel is used which does not differentiate between oil and gasphases, similarly the saturation threshold applies to a singlephase (oil) which we ensured by setting oil and gas saturationthresholds to the same value for the source rock lithology (5% forshale and 0.1% for siltstones). According to Hantschel andKauerauf (2009) critical oil saturations in shales range from 0.5to 50% and are much higher than in sandstones, for which thevalues range between 0.1 and 10% (PetroMod uses the same Soc ofsandstones for siltstones). Hydrocarbon migration was simulatedusing the hybrid method, previously described in Section 3 (de-tails in Hantschel and Kauerauf, 2009; Schlumberger, 2009;Hantschel et al., 2000).

The predicted timing for initial petroleum expulsion from theTriassic Kobbe Formation is around 120 Ma (implying that migra-tion took place since Early Cretaceous time) and the estimated totalamount of petroleum expelled corresponds to w62 Gt (30 Gt of oiland 32 Gt of gas). The expulsion efficiency is defined as the per-centage of expelled petroleum in relation to total generatedbitumen of a particular source rock unit. The expulsion efficienciescan also be determined for total petroleum phases or fractions aswell as for individual compounds (Mann et al., 1997). For thismodel, expulsion efficiencies were determined for the total petro-leum and for the separate oil and gas phases, using the masses ofpetroleum (oil þ gas), oil and gas generated and expelled (Table 3).The different compounds taken into account for each phase havebeen specified in Section 4.2. The monophasic petroleum expulsionefficiencies for the Hekkingen, Snadd and Kobbe formationscorrespond to w19% (3 Gt expelled/16 Gt generated), w40% (24 Gtexpelled/63 Gt generated) and w55% (35 Gt expelled/64 Gtgenerated), respectively. We estimated the expulsion efficienciesfor the two separated phases, i.e. oil and gas. The oil expulsion ef-ficiencies correspond to approximately 17%, 38% and 50% and thegas expulsion efficiencies are approximately 25%, 42% and 55%(Hekkingen, Snadd and Kobbe formations, respectively). Variableoil and gas expulsion efficiencies are due to the inclusion of gasgenerated by secondary cracking in the calculations.

Figure 11. a, b, c) Modelled maturity maps at present-day for the Hekkingen, Snadd and Kobbe formations. Note that the highest maturities have been reached in the western and northwestern margin of the basin. d, e, f) Total mass inGt of oil (green line) and gas (red line) generated by the three source rocks through time.

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In the next sections we present estimations on the fate of thethermogenic gas in the basin, i.e. how much gas was actuallytrapped into the Stø Formation reservoir, how much leaked fromthis reservoir and how much of the leaked gas reached the modelsurface.

4.4. Hydrocarbon accumulations (main reservoir-Stø Formation)

Hydrocarbons are predicted to start filling this reservoir (StøFormation) from 80 Ma onward (Fig. 12a). At approximately 55 Mawhen one of the main filling pulses into the Stø Formation tookplace, the main sealing unitse Fuglen and Hekkingen formationsewere already deposited and to a large degree consolidated. This isindicated by porosity values below 15%, specifically w11.6% for theFuglen Formation and 7.5% for the Hekkingen Formation (Fig. 12d).Simultaneously, the predicted permeability during that period is inthe order of 10�6 to 10�7 mD (Fig. 12d), values supported by pub-lished data (Linjordet and Grung-Olsen, 1992), which suggests thateffective sealing and the trapping of oil and gas was possible. Thisnotion is also supported by the predicted reservoir petroleumsaturation values, which start to increase at this time.

Modelling results show that the main loss of oil occurred afterthe Oligocene time associated to the tectonic uplift and erosion ofthe basin, when expansion of the gaseous phase took place, causingspilling out of the structures and affecting primarily the liquidphase (Fig. 12a). We observed that themain filling of the Goliat fieldin the southeastern margin of the basin occurred as well after

Figure 12. a) Accumulation history for oil (green line) and gas (red line) in the main reservthe area marked in a) by a black rectangle) for the glacial period, i.e. between 1.10 and 0.01maximum burial and the beginning of the uplift and erosion. d) Porosity (solid line) and permand Hekkingen formations. (For interpretation of the references to colour in this figure leg

30 Ma (Fig. 12c), indicating that a portion of the petroleum in thisfield was probably sourced from the north after spilling out of thestructure, and indicating at the same time the possible long-distance migration. On the other hand, the main loss of gaseoushydrocarbons occurred during the Pleistocene time associated tothe glaciations which developed in the Barents Sea. The modelpredicts that at present-day the amount of gas accumulated in theStø Formation slightly exceeds the amount of oil (Fig. 12a, b), i.e.0.302 Gt of gas and 0.298 Gt of oil. The modelling results reproducethe natural petroleum accumulations and phases quite well(Fig. 13a) at present-day in the main known fields, such as Snøhvit,Snøhvit-Askeladden, Snøhvit-Albatross and Goliat (NorwegianPetroleum Directorate, 2010b, a). For the first three fields the ac-cumulations consist mainly of gas, with Snøhvit and Snøhvit-Al-batross having oil legs. The Snøhvit-Askeladden field wasreproduced as a pure gas accumulation. Modelled gas to oil ratios(GORs) for the oil legs are between 215 and 280 Sm3/Sm3 (standardcubic metres, Fig. 13a), reported natural GORs are in the same range(Norwegian PetroleumDirectorate, 2009). Likewise, for the gaseousphases modelled GORs vary between 8500 and 22,300 Sm3/Sm3,and natural fluid measured GORs are mainly between 7400 and27,000 Sm3/Sm3. In the particular case of the Goliat field, the modelpredicts an accumulation dominated by oil, which is in agreementwith the information reported by the NPD (Norwegian PetroleumDirectorate, 2010a, 2009). GOR values in our model are around200 Sm3/Sm3, while the reported fluid GOR is around 59 Sm3/Sm3,however, it should be noted that the oils present in this field have

oir, the Stø Formation. b) Detailed view of the accumulation history (expanded view ofMa. c) Oil and gas filling history of the Goliat field. The arrow indicates the time of theeability (dotted line) history for both seal rocks of Goliat field, corresponding to Fuglen

end, the reader is referred to the web version of this article.)

Figure 13. a) Predicted petroleum accumulations (Snøhvit, Albatross, Askeladden and Goliat fields and Tornerose Discovery) in the Stø Formation at present-day. Minor untestedaccumulations predicted for this model in the area are also shown. Inlets in the figures list the gas-oil ratios reported in the Norwegian Petroleum Directorate (2013) and calculatedin the model for each field and discovery. To the right of the figure a table shows a comparison of the original recoverable oil and gas volumes reported in the Norwegian PetroleumDirectorate (2013) and compared to the volumes calculated in the model. b) Predicted hydrocarbon accumulations at 1.10 Ma, i.e. beginning of the modelled glacial period. To theright the volumes of oil and gas predicted in the model are shown.


been reported to be slightly biodegraded (Norwegian PetroleumDirectorate, 2009), which would result in the reduction of liquidGOR (Larter and di Primio, 2005).

An alternative explanation for the low GORs in Goliat, followingthe work of Karlsen and Skeie (2006), would be the loss of gaseousand light hydrocarbons on the migration pathways during longdistance migration of petroleum from the active kitchen to thefield.

The Goliat field is hosted in rollover structures, which arelocated close to the TromseFinnmark Fault Complex. This area hasbeen described as extensively faulted with the top seal beingintersected by numerous faults. This top seal is in addition thin andsilty in this part of the basin (Ohm et al., 2008). Accordingly any gasaccumulated in the Goliat field easily leaked during uplift anderosion events possibly affecting the residual oil GOR. The possiblelong distance migration of petroleum from the northern basinmargin to the Goliat field, as suggested previously, could alsoexplain the loss of gaseous and light hydrocarbons on themigrationpathways, the preferential accumulation of oil and therefore thelow GOR observed.

Based on the modelled present-day gas volume accumulated inthe Stø Formation reservoir and considering a recovery factor ofw70%, the predicted recoverable gas volume at surface conditionsis equivalent to w218 billion m3 for the Snøhvit, Albatross andAskeladd fields, w0.95 billion m3 for the Goliat field andw12.21 billion m3 for the Tornerose discovery. This matches the

reported estimates of recoverable gas in the range between 260 and300 billion Sm3 (Doré, 1995; Larsen et al., 1993) and also the re-ported estimates published in the NPD (Norwegian PetroleumDirectorate, 2013, 2010b, a)

It is worth noting that the predicted petroleum accumulations atthe onset of the glaciation period (1.10 Ma) are larger than thosepredicted at Present-day (Fig. 13b). This suggests that glaciations,and subsequent erosion, have affected the initial accumulations inthe 3D model. These model predictions actually reproduce thenatural situation, as most of the accumulations discovered in theHammerfest Basin represent underfilled traps with residual oilsaturation below the oil water contacts, indicating a previouslylarger degree of filling (Ohm et al., 2008). The loss of petroleumfrom the traps is mainly attributed to leakage or spill. In thefollowing we address this issue, focussing on the gaseous hydro-carbons, through our 3D modelling results.

4.5. Gaseous hydrocarbons loss from the modelled reservoirs

Figure 14aed shows the predicted reservoir behaviour inresponse to the periodic loading and unloading of the basin duringglacial and interglacial cycles which occurred in combination withglacial erosion. From the results, transient effects in the pore andhydrostatic pressure distributions were observed, with a slight in-crease in pore pressure above the hydrostatic pressure gradientduring maximum ice loading and glacial retreat, which generates

Figure 14. Correlation of modelled glacial history, predicted reservoir pressure con-ditions and gas masses trapped and leaked. a) Glacial history (from Fig. 8) togetherwith the depth variation of the Stø Formation. b) Oscillating reservoir (Stø Formation)pressure conditions (pore, hydrostatic and excess hydraulic pressures). c) Calculatedgas mass in the Stø Formation during the last 1.2 Ma. Note that the main events of gasdecrease occur in the transition from maximum glaciation to the interglacial period. d)Gas loss expressed as outflow at model top.


overpressure in the system (Fig. 14b). Variations of pore pressureare between w3 and 6 MPa. Such pressure oscillations affect thepetroleum accumulated in the reservoir, especially the highlycompressible gas phase (Fig. 14c). It is important to note that theresults from our model are certainly general approximations of allthe processes involved (e.g. the gas phase compression andexpansion) because modelling all the complexities associated is notpossible. Nonetheless, the main physical processes such ascompaction, pressure evolution and gas compressibility (e.g.calculation based on the gas composition using the Peng-Robinsonequation of state) are correctly treated, albeit scaled to the cell sizesused in the model.

Figure 14c depicts the accumulation history of gaseous hydro-carbons in the Stø Formation at each stage during the glacial-interglacial periods, between 1.10 and 0.01 Ma. We observed thata large and continuous loss of gas took place, with the main losspulses associated to the glacial retreat stages. The amounts of gaslost reported in our model after each megacycle are as follows:0.070 Gt (MC5), 0.031 Gt (MC4), 0.036 Gt (MC3), 0.030 Gt (MC2),and 0.080 Gt (MC1). This gives an estimation of the total amount ofgas loss of around 0.247 Gt.

Considering the possibility that a fraction of the leaked ther-mogenic gas from the reservoir could have reached the sedimentsurface, we calculated the gaseous hydrocarbons losses reported asoutflow at the top of the model for the glacialeinterglacial periods(Fig. 14d). We corroborated that the peaks of gas outflow are syn-chronous with the leakage from the reservoir. Therefore, we pro-pose that ascending gas leaked from the reservoir feeds the surfaceof the model. Also the calculated gas migration vectors during thesame glacialeinterglacial periods (Fig. 15) demonstrate that the gasmoves buoyantly towards the surface in the model.

5. Discussion

5.1. Controls on subsurface pore pressure and leakage of gas

Our simulation results allow reconstructing the pore pressureconditions in the subsurface during the glacialeinterglacial cycles.Here we focus especially on the main reservoir, the Stø Formationunit (Section 4.5).

According to Clayton and Hay (1994), Mann and Mackenzie(1990) and Osborne and Swarbrick (1997), overpressure in sedi-mentary basins can be generated by a variety of mechanisms. Thedominant mechanism being compaction disequilibrium, in whichan increase in the compressive stress results in a decrease of thesediments porosity and permeability. If the pore water is inhibitedfrom escaping (due to too low permeability) this mechanism thenresults in an increase in the pore pressure above the hydrostaticlevel. Accordingly, as it is observed in our model, a rapid burial(vertical compression) due to the loading caused by the ice-sheet(in a period of w100,000 years), would generate overpressure.

On the other hand, as discussed above, we not only observed theoccurrence of a slight overpressure during maximum loading(glacial loading), but also an increase of the hydrostatic pressuregradient. The hydrostatic pressure is the pressure exerted by acontinuous water column through the entire depth of the sedi-ments (Hambrey, 1994). During glacial loading this pressure islikely to have increased due to the increase in the water columnassociated to glacial melt water (Hambrey, 1994). In the situationmodelled we assumed that the glacier covering the HammerfestBasin was a warm glacier, that is, ice was at the pressure meltingpoint throughout, as consideration of the effects of a melt watercolumn beneath the glacier is not possible in the modelling soft-ware. The large scale erosion that took place in the area also

Figure 15. 3D model view at 0.95 Ma (end of the first glaciation) showing the Stø Formation (yellow layer), the shallowest layer at that time (brown layer) and the displacementvectors of hydrocarbons (red arrows); indicating the migration of hydrocarbons from the deep reservoir unit to the shallowest layer. (For interpretation of the references to colourin this figure legend, the reader is referred to the web version of this article.)


corroborates this assumption, as warm glaciers generate muchmore erosion than cold glaciers, in which erosion is basicallyinhibited.

Based on ice-sheet/groundwater models of the NorthwesternEurope (Saalian and Weichselian glaciations), it has been estab-lished that many polar glaciers melt basally (van Weert et al., 1997;Boulton et al., 1993). In many areas (e.g., across sedimentary ba-sins), the transmissivity of subglacial beds is enough to discharge allmelt water by groundwater flow, accordingly glacial cycles producecyclic pulses of pressure and groundwater flow through the sub-surface (Boulton et al., 1995). In the case of high melt water pro-duction, the groundwater pressure may become very high, almostequal to the overburden pressure (van Weert et al., 1997).Groundwater flow is therefore considered a vital process in con-trolling subsurface pressures (Boulton and Caban,1995). As a result,the loading and unloading associated to the growth and retreat ofthe ice-sheet affected the hydrostatic pressure (warm glacier),likely influenced sediment compaction, which in turn influencedthe pressure regime in the reservoir (as previously discussed), thefluid flow direction and the sealing capacity of cap rocks.

The leakage of gas from the Stø Formation reservoir (0.247 Gt)observed in our work is thus mainly the result of seal capillaryfailure. The capillary failure of the seal (alternatively, themaximum column height which a cap rock can hold) occurs whenthe upward directed buoyancy pressure, generated by the lowerdensity of petroleum (especially gas), plus any excess overpressurein the reservoir exceeds the capillary resistance pressure of theseal (Hantschel and Kauerauf, 2009; Clayton and Hay, 1994).Capillary failure is the normal mode of failure under hydrostatic ormoderately overpressured conditions, fracture failure generallyoccurs only in highly overpressured environments or at shallowdepths. In the modelling software, the increase of the pore and/orhydrostatic pressures (between 3 and 6 MPa) during glacialloading invariably leads to the compression of the gas phase,reducing the total petroleum column height, increasing the fluid

density and thus inhibiting capillary failure of the seal. Estimationof the actual effect of such a pressure change on a subsurface gascolumn using a natural gas composition and a PVT simulator(PVTSim V.17, Calsep-Denmark) indicates that the volume of thegas phase decreases by about 10% when an increase in porepressure of 6 MPa is assumed. At the transition from glacial tointerglacial periods the retreat of the ice-sheet and erosion tookplace, such that upon unloading of the basin at this time, as well asduring the interglacials, the gas column expands to a volumelarger than the initial, resulting in a larger hydrocarbon columnheight, the capillary failure of the cap rock and therefore hydro-carbon leakage from the reservoir. As it was previously discussed,overpressure is also present in the system, which additionally af-fects the sealing capacity of the cap rock. Gas leakage is, hence,focused in time by the physical process occurring in the basin. Allof the processes discussed above (gas compressibility, PVT effects,spilling and remigration and capillary flow and leakage) weretaken into account by the modelling software. For this modellingexercise, we did not consider any structural elements such asfaults, which can also contribute as pathways for gas leakage in thearea (Ostanin et al., 2013, 2012). As discussed in Section 3 the onlyfaults considered in this model corresponds to those of theTromseFinnmark Fault Complex, which were defined manuallyand considered as closed with respect to fluid flow from 60 Ma tothe present. This was necessary for the model to reproduce theGoliat field, located to the west of this fault complex, which it has areal structural control and the accumulations present in the fieldhave been trapped against sealing faults. We are also aware ofalternative mechanisms for petroleum leakage from the reservoirthrough the seal, such as hydraulic leakage and diffusive/moleculartransport (Karlsen and Skeie, 2006; Corcoran and Doré, 2002;Krooss and Leythaeuser, 1996), that may be active in the naturalsystem. The first relates to hydraulic fracturing, which occurswhen pore pressure exceeds the fracture gradient of the cap rock,then fractures through brittle top seals act as a conduits for the


leakage of petroleum (Corcoran and Doré, 2002). Hydraulic frac-turing is implicitly included in our simulations in dependence ofthe calculated pore pressure evolution. When pore pressures riseabove the fracture pressure, cap rock permeabilities are increasedand capillary entry pressures decreased. However, as no significantoverpressure development in the Stø Formation was modelled thiscriteria was not met in our simulations. The second mechanismcorresponds to the transport process that results from randomthermal motion of individual molecules through the cap rock(Krooss and Leythaeuser, 1996). This type of leakage is notmodelled in PetroMod and can be disregarded as a significantleakage mechanism in the Hammerfest Basin due to the low ratesof diffusive loss and the short timescale in which such losses mayhave occurred (i.e. maximum since the OligoceneeMiocene ormore likely since the Plio-Paleocene).

An abundance of faults and associated indications of gas leakagehave been described for the Snøhvit field (Ostanin et al., 2013,2012). While leakage along, or controlled by, faults is a likelymechanism, the large scale of our model as well as the lack of in-formation concerning the sealing or transmissive properties of thefaults impeded their inclusion in our simulations. Future effortsshould be directed in that sense. However, migration along faults isusually simulated assuming capillary pressure controlled percola-tion, or through permeability variations and associated reduced(transmissive) or enhanced (sealing) capillary entry pressures.Hence, we think that the main leakage mechanism, i.e. capillaryfailure, remains the same, only the exact sites where leakage occursdiffer.

Accordingly, our leakage estimates must be seen as one possiblescenario of petroleum leakage in the Hammerfest Basin. However,the fact that volumetric proportions of oil versus gas hosted in theindividual fields of the study area, their respective GORs, and thefact that underfilled structures are reproduced indicates that theleakage estimates calculated may be realistic.

6. Conclusions

Three-dimensional petroleum system modelling of the Ham-merfest Basin indicates two episodes of reservoir fluid redistri-bution, both related to erosion events: the main OligoceneeMiocene erosion resulted in a significant phase of oil redistribu-tion due to spill from the reservoirs, whilst the main loss of gasfrom the basin occurred in the recent geologic past. The latterresulted from glacial loading-unloading and erosion of the basinduring the glacial period, between 1.10 and 0.01 Ma. During theglacial cycles subsurface petroleum reservoirs were subjected tosignificant overpressure fluctuations, affecting directly the prev-alence of gas in the region and driving gas leakage to the surface.Our modelling results indicate a loss of ca. 0.247 Gt of gaseoushydrocarbons predominantly during the transitions from glacialto interglacial periods. It is important to note that the modelledarea represents only a fraction of the glacially influenced BarentsSea. In this sense, it is possible to say that similar amounts of gasmay have leaked from other areas in the Barents Sea or even inthe entire Arctic region, with a similar architecture and geologicevolution.

Acknowledgements

The authors thank Lundin Norway AS for providing the surfacemaps used in the model building. This work is a contribution to theHelmholtz Climate Initiative REKLIM (Regional Climate Change), ajoint research project of the Helmholtz Association of Germanresearch centres (HGF). Anka, Z. is head of a Helmholtz-UniversityYoung Investigator Group funded by the Helmholtz Association’s

Initiative and Networking Fund. We also thank Chris Conford andDag Karlsen for their constructive comments that helped toimprove the quality of this manuscript. An earlier version of thismanuscript benefited from the comments and suggestions ofAndrew Cavanagh.

Appendix A. Supplementary data

Supplementary data related to this article can be found at http://dx.doi.org/10.1016/j.marpetgeo.2013.04.023.

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