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Article

First-Order Estimation of In-Place Gas Resources at the Nyegga Gas Hydrate Prospect, Norwegian Sea

by
Kim Senger
1,2,*,
Stefan Bünz
1 and
Jürgen Mienert
1
1
Department of Geology, University of Tromsø, Dramsveien 201, N-9037 Tromsø, Norway
2
Center for Integrated Petroleum Research, Uni Research, Allégaten 41, N-5020 Bergen, Norway
*
Author to whom correspondence should be addressed.
Energies 2010, 3(12), 2001-2026; https://doi.org/10.3390/en3122001
Submission received: 26 October 2010 / Revised: 7 December 2010 / Accepted: 20 December 2010 / Published: 22 December 2010
(This article belongs to the Special Issue Natural Gas Hydrate)
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Versions Notes

Abstract

:
Gas hydrates have lately received increased attention as a potential future energy source, which is not surprising given their global and widespread occurrence. This article presents an integrated study of the Nyegga site offshore mid-Norway, where a gas hydrate prospect is defined on the basis of a multitude of geophysical models and one shallow geotechnical borehole. This prospect appears to hold around 625 GSm 3 (GSm 3 = 10 9 standard cubic metres) of gas. The uncertainty related to the input parameters is dealt with through a stochastic calculation, giving a spread of in-place volumes of 183 GSm 3 (P90) to 1431 GSm 3 (P10). The resource density for Nyegga is found to be comparable to published resource assessments of other global hydrate provinces.

1. Introduction: Gas Hydrate as an Energy Resource

Gas hydrates are solid compounds of guest gas molecules set in a rigid cage of host water molecules, occurring at specific pressure-temperature (P-T) conditions beneath the world’s oceans and below the permafrost [1,2].
Originally a mere scientific curiosity, gas hydrates have attracted much attention since being reported in hydrocarbon pipelines as early as 1934 [3]. Flow assurance remains a problem in the global oil and gas industry to the present day [4,5], with deep-water production and ever longer tie-back distances calling for sophisticated hydrate flow management. Furthermore, gas hydrate dissociation in sediments along continental margins has been linked to potential for large-scale slope failures [6], reduced integrity of man-made seafloor structures due to hydrate-associated slope instability [7] and atmospheric release of methane linking into the wider issue of climate change [8,9,10].
However, in the past decade gas hydrates are also increasingly considered as a potential energy source. The global energy market is in disharmony, with falling oil production unable to supply the increasing global demand in the long term [11], financial crisis notwithstanding. Production of natural gas is already replacing oil as the dominant hydrocarbon produced in regions close to infrastructure and markets, as on the Norwegian Continental Shelf (NCS). Natural gas, with its lower per unit energy CO 2 emissions than any other fossil fuel, is set to provide a large part of the supply necessary to satisfy a predicted 50–60% global energy demand increase in the period 2008–2030 [12]. Unconventional gas resources, such as tight sands, shale gas or coal bed methane, may ease some of the load off conventional gas resources, provided that their production remains environmentally, technically and commercially acceptable. In addition, gas hydrates can also be considered as an unconventional gas resource [13].
The production of gas hydrates has, to date, utilized slightly modified conventional oil & gas production technologies. For the guest gas to be produced, the solid ice cage must be broken down by displacing the hydrate out of its P-T stability zone. This is achieved by depressurisation, thermal stimulation or chemical inhibition, or a combination thereof. Both numerical studies, including the use of hydrate-specific reservoir simulators [14,15,16], and field experience from the Siberian gas field Messoyakha [5,17,18], the North Slope Borough [19] and the Mallik test site [20,21], point to depressurization being the most cost-effective and efficient method. In this scenario, the free gas zone trapped beneath the impermeable hydrate layer is produced, lowering the pressure, and thus allowing the overlying hydrate to dissociate and contribute to the gas flow. However, every prospect is different and the applied production strategy will, as for conventional gas deposits, depend on the geological setting and the hydrate reservoir properties [22].
Gas hydrates are a global and abundant resource. Recent conservative estimates of global hydrate-bound methane, while significantly reduced from the enormous estimates published in the 1980s and 1990s [23], suggest hydrate-derived methane to be an important carbon reservoir [1,2]. While most of these resources occur in low-saturation marine sediments, as illustrated by the resource pyramid of Boswell et al. [24], the potential societal gain of hydrates cannot be ignored. A recent review of the Alaskan gas hydrate resources, as an example, indicates up to 2 400 GSm 3 (GSm 3 = 10 9 standard cubic metres; 85 trillion cubic feet; equivalent to 15 095 million barrels of oil equivalents) of technically recoverable gas [25]. Furthermore, production of gas from some hydrate deposits is possible with only minor modifications of conventional technologies [26]. Most importantly, it has already been tested during short-term scientific production tests at Mallik, a multinational study site in the Canadian Mackenzie Delta [20,21,27,28]. Extensive marine expeditions undertaken as part of ambitious national “hydrate as a resource” programs offshore India [29], Japan [30] and Korea [31], as well as a Joint Industry Project in the Gulf of Mexico [32,33] and numerous ODP/IODP cruises [34,35], provide a substantial database for examining various global hydrate provinces in terms of reservoir characterization and prospect definition.
Here we present such a study for the Nyegga prospect, a gas hydrate prospect located in predominantly unlicensed acreage on the northern flank of the Storegga slide, offshore mid-Norway.

2. Geologic Setting: The Nyegga Gas Hydrate System

Our study area, referred to as Nyegga in literature, lies on the Vøring Plateau some 135 km north of Ormen Lange, Norway’s second largest gas field (Figure 1). The nearest conventional field, Kristin, is located approximately 80 km to the north-east. Lying alongside the prolific gas province of the Norwegian Sea is important for several reasons. Firstly, deep thermogenic gas may contribute as a local source to some of the hydrate deposits, as observed in parts of the Gulf of Mexico [36]. Secondly, the existing infrastructure suits itself to cost-effective tie-back solutions should hydrate deposits be developed in the future. Last but not least, the amount of data available for the study of hydrates, in part thanks to the thorough work that went into the Ormen Lange development [37], makes a good foundation for a quantification study.
The Nyegga area has been shaped by a combination of lasting tectonically-driven processes and more recent glacial activity. Multiple rifting episodes resulted in the opening of the Norwegian-Greenland Sea around 55 million years ago, leading to the development of the Møre and Vøring sedimentary basins [39,40]. The Late Eocene strike-slip compressive regime resulted in the development of north-south trending anticlinal features [41], of which the Ormen Lange dome is one. Within the last 3 million years, extensive deposition of glacially derived materials of the Naust Formation dominated the area, resulting in a sediment package well over 1000 m thick in places [42]. Its depositional regime is highly dependent on the climatic variations associated with glacial and interglacial times and the position of the ice sheet in relation to the shelf break [43].
The study area lies within the Norwegian-Greenland Sea, in which oceanic circulation is governed by the northward-flowing waters of the North Atlantic Current (NAC). Studies of benthic microfossil assemblages during ODP Leg 104 have confirmed that the modern-day oceanic conveyor system was established already during the mid-Miocene [44]. The NAC, essentially the continuation of the North Atlantic Drift, transports warm saline waters into the Nordic Seas. Upon entering the Norwegian-Greenland Sea through the Faroe-Shetland inflow, the NAC is partially branched as the south-easterly flowing Norwegian Channel Inflow. In addition, the Norwegian Coastal Current (3–18 ∘ C, Klitgaard-Kristensen et al. [45]) flows along the Norwegian coast, being strongly controlled by seasonal variation. A large publicly available data set [46] allows the examination of 1070 Conductivity-Temperature-Depth (CTD) casts within the study area. The data clearly show the largest variation within the uppermost 200 m of the water column. At depths exceeding approximately 750 m, temperatures are stable at approximately - 1 ∘ C. Between 250 m and 750 m there is a large variation in oceanic temperatures of up to 8 ∘ C.
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Figure 1. Location of the Nyegga study area, offshore mid-Norway. The study area rests on the north flank of the Storegga slide, approximately 135 km north of the Ormen Lange gas field. The main Nyegga gas hydrate prospect, based on the interpretation of the bottom simulating reflection (BSR), is emphasized in yellow. A detailed map illustrating the extent of the gas hydrate zone, as well as the key data used is provided in Figure 4. Figure modified from Weibull et al. [38].
Figure 1. Location of the Nyegga study area, offshore mid-Norway. The study area rests on the north flank of the Storegga slide, approximately 135 km north of the Ormen Lange gas field. The main Nyegga gas hydrate prospect, based on the interpretation of the bottom simulating reflection (BSR), is emphasized in yellow. A detailed map illustrating the extent of the gas hydrate zone, as well as the key data used is provided in Figure 4. Figure modified from Weibull et al. [38].
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Gas hydrates have originally been inferred from the Nyegga area on the basis of bottom-simulating reflections (BSRs) [47,48,49] as well as seabed topography and biology [50,51]. Physical sampling of shallow gas hydrates was first reported in 2006 [52], though the Nyegga gas hydrates have long been studied “geophysically” [53,54,55]. It is notable that a shallow geotechnical borehole, 6404/5 GB1, penetrated the BSR during a drilling campaign in 1997. While the vertical seismic profiling (VSP) suggest the presence of hydrates, no physical samples were recovered at this time, probably due to a lack in suitable pressure-coring equipment. While gas hydrate saturations have been estimated in places through the use of various inversions of ocean bottom seismic (OBS) and high-resolution 3D seismic data [56,57,58], no one has, to the best of our knowledge, previously attempted to calculate the total amount of methane encaged within the Nyegga gas hydrate province.
Quantifying gas hydrate deposits, at Nyegga or otherwise, is important for three main reasons:
  • Modeling potential release of the potent greenhouse gas methane into the ocean following a shift in P-T conditions;
  • Risk assessment for conventional exploration boreholes targeting hydrocarbons beneath zones of notoriously unstable gas hydrate;
  • Providing an estimate of the scale and potential of the hydrate deposit as a future energy resource.
This study focuses on Point 3, yet the methods and results presented could easily be modified to suit other objectives. It must be noted that this study’s objective was to define a range of probable in-place (GIIP) volumes, and further work remains on evaluating whether the hydrate deposits can technically be recovered.

3. Methods

3.1. Modeling the Hydrate Stability Zone

In order to constrain the Nyegga gas hydrate system in two dimensions, a thermobaric model was established to calculate the extent of the hydrate stability zone (HSZ, Figure 2, [59]). The HSZ is defined on the basis of the hydrate phase boundary, the geothermal gradient and the oceanic thermal gradient. A matrix of cases was established to examine the relative impact of altering the various input parameters. Finally, the modeled base of the HSZ was compared with the BSR observed on seismic data (Figure 3). A good fit confirms that the BSR is likely to be a hydrate-related reflection.

3.2. Prospect Evaluation

Our methodology closely follows that of traditional prospect evaluation of conventional hydrocarbon prospects. To begin with, an integrated database of seismic, borehole and oceanographic data was established (Figure 4). The Nyegga prospect is modeled as a 3-segment unit (Figure 5), consisting of a solid gas hydrate zone, a gaseous free gas zone and a combination chimney zone.
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Figure 2. Input parameters used to define the thermobaric hydrate stability zone (HSZ) model. (a) Hydrate phase boundary; (b) Geothermal gradients; (c) Oceanic thermal gradients; (d) The complete system plotted on the pressure-temperature diagram. The model is kept on the same scale to allow for comparison of the effect of the various parameters. Pressure is given in decibars (db).
Figure 2. Input parameters used to define the thermobaric hydrate stability zone (HSZ) model. (a) Hydrate phase boundary; (b) Geothermal gradients; (c) Oceanic thermal gradients; (d) The complete system plotted on the pressure-temperature diagram. The model is kept on the same scale to allow for comparison of the effect of the various parameters. Pressure is given in decibars (db).
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Figure 3. Modeled HSZ extent (red areas = hydrate can form) compared to the bottom-simulating reflection (stippled yellow line) as observed on 2D line JMF97-215. This particular model is based on a pure methane system with saline pore water, a high geothermal gradient and an average oceanic thermal gradient.
Figure 3. Modeled HSZ extent (red areas = hydrate can form) compared to the bottom-simulating reflection (stippled yellow line) as observed on 2D line JMF97-215. This particular model is based on a pure methane system with saline pore water, a high geothermal gradient and an average oceanic thermal gradient.
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Figure 4. Location map showing the data, including seismic, borehole and oceanographic data, used to generate the 3D model. Please note that the stippled yellow lines indicate 2D seismic data used to tie the key 2D seismic data set, JMF97 (pink solid lines), to the wells. Also note that the study area only contains the largest BSR extent, while other prospects where BSRs are identified provide an upside potential.
Figure 4. Location map showing the data, including seismic, borehole and oceanographic data, used to generate the 3D model. Please note that the stippled yellow lines indicate 2D seismic data used to tie the key 2D seismic data set, JMF97 (pink solid lines), to the wells. Also note that the study area only contains the largest BSR extent, while other prospects where BSRs are identified provide an upside potential.
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Figure 5. A cartoon sketch of the Nyegga prospect definition based on seismic line NH9651-202, showing its three main segments; (1) The gas hydrate zone, 10–120 m thick; (2) The free gas zone, 20–80 m thick; (3) The chimney zone, on average 200 m wide. The bottom-simulating reflection (BSR) is highlighted with arrows. The BSR is most marked within permeable intervals where the free gas to gas hydrate transition causes a strong and sharp amplitude change. The geotechnical borehole, 6404/5 GB1, has been used to constrain porosity. The polygonal fault system within the underlying Kai Formation provides pathways for fluid and gaseous flow [54]. Figure modified from Bünz and Mienert [57].
Figure 5. A cartoon sketch of the Nyegga prospect definition based on seismic line NH9651-202, showing its three main segments; (1) The gas hydrate zone, 10–120 m thick; (2) The free gas zone, 20–80 m thick; (3) The chimney zone, on average 200 m wide. The bottom-simulating reflection (BSR) is highlighted with arrows. The BSR is most marked within permeable intervals where the free gas to gas hydrate transition causes a strong and sharp amplitude change. The geotechnical borehole, 6404/5 GB1, has been used to constrain porosity. The polygonal fault system within the underlying Kai Formation provides pathways for fluid and gaseous flow [54]. Figure modified from Bünz and Mienert [57].
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While both the gas hydrate and the free gas zones are spatially defined by the BSR, the chimney zone is based on an integrated study of Weibull [60]. Weibull used both multibeam echosounder data and the GH2001 high-resolution seismic survey to generate a well-documented geostatistical overview of gas-related features across part of the Nyegga prospect. While the physical content of acoustic chimneys is an ongoing debate [61], potential for higher saturation hydrate accumulations exists in such pipes due to focused fluid flux and they have thus been included as a separate segment in our volumetric calculation.
A standard volumetric calculation (Equation (1), Figure 6) was implemented in two industry-standard tools, Petrel and GeoX. To account for the uncertainty with respect to data sampling across the Nyegga prospect, a wide range of probable reservoir parameters was used as input (Table 1).
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Figure 6. A sketch illustrating the Nyegga volumetric calculation. The three-dimensional reservoir extent is calculated based on the areal extent of the bottom-simulating reflection (BSR) and the thickness of the hydrate and free gas zones, based on ocean bottom seismometer (OBS) experiments. For the chimney zone, the gross rock volume (GRV) is directly defined by the study of Weibull [60]. Net-to-gross (NTG), porosity and gas hydrate saturation is applied to give a hydrocarbon pore volume (HCPV). Upon application of an expansion factor, B G , a gas initially in place (GIIP) volume is calculated. Only a fraction of the GIIP is technically producible, depending on the recovery factor, to give the final recoverable gas. Please note that GIIP equates in-place volumes.
Figure 6. A sketch illustrating the Nyegga volumetric calculation. The three-dimensional reservoir extent is calculated based on the areal extent of the bottom-simulating reflection (BSR) and the thickness of the hydrate and free gas zones, based on ocean bottom seismometer (OBS) experiments. For the chimney zone, the gross rock volume (GRV) is directly defined by the study of Weibull [60]. Net-to-gross (NTG), porosity and gas hydrate saturation is applied to give a hydrocarbon pore volume (HCPV). Upon application of an expansion factor, B G , a gas initially in place (GIIP) volume is calculated. Only a fraction of the GIIP is technically producible, depending on the recovery factor, to give the final recoverable gas. Please note that GIIP equates in-place volumes.
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The total in-place gas, Q g a s , is defined by:
[ ! h ] Q g a s = B R V × ϕ × N / G × ( 1 - S W ) × 1 B G
where:
  • B R V = Bulk rock volume, m 3 ;
  • ϕ = porosity, given as fraction of 1;
  • N / G = Net to gross ratio of sand, given as fraction of 1;
  • S W = Water saturation, given as fraction of 1;
  • B G = Compressibility of gas, defined by volume at reservoir/volume at STP.

3.3. Reservoir Parameters

Input parameters were defined by distributions, spanning in both directions from a base case representing the most likely case (Table 1 and Figure 7).
Table
Table 1. Range of reservoir parameters used in defining the in-place volumes of hydrate-bound methane. Each reservoir parameter is defined by a distribution between a range of possible values used in the stochastic calculation. The mode case will, by definition, have the highest impact in the volumetric calculation and thus represents the most favoured case. Note that StrBeta = Stretched Beta distribution.
Table 1. Range of reservoir parameters used in defining the in-place volumes of hydrate-bound methane. Each reservoir parameter is defined by a distribution between a range of possible values used in the stochastic calculation. The mode case will, by definition, have the highest impact in the volumetric calculation and thus represents the most favoured case. Note that StrBeta = Stretched Beta distribution.
Gas hydrate zoneReference/Comments
Parameter [units]TypeMinBaseMax
Area of Closure [km2]StrBeta107022543120Mid case: BSR outline without "tricky" zones, Low case: "Sweet spot" BSR outline, High case: BSR outline
Column Height [m]StrBeta1050120Based on Bünz et al 2005, Westbrook et al 2008 and Faverola et al 2009.
Net/Gross Ratio [decimal]Normal0.0010.51Based on Hustoft et al 2007 & Bouriak et al 2003.
Porosity [decimal]Normal0.490.550.61Based on geotechnical borehole 6404/5 GB1.
Gas Saturation [decimal]StrBeta0.0250.0710.21Based on Bünz et al 2005, Westbrook et al 2008 and Faverola et al 2009.
Gas Expans. Factor (1/Bg) [Sm3/m3]Constant164164164Based on Sloan & Koh 2008.
Free gas zone
Parameter [units]TypeMinBaseMax
Area of Closure [km2]StrBeta107022543120Mid case: BSR outline without "tricky" zones, Low case: "Sweet spot" BSR outline, High case: BSR outline
Column Height [m]StrBeta204080Based on Bünz et al 2005, Westbrook et al 2008 and Faverola et al 2009.
Net/Gross Ratio [decimal]Normal0.0010.51Based on Hustoft et al 2007 & Bouriak et al 2003.
Porosity [decimal]Normal0.490.550.61Based on geotechnical borehole 6404/5 GB1.
Gas Saturation [decimal]StrBeta0.0020.0070.19Based on Bünz et al 2005, Westbrook et al 2008 and Faverola et al 2009.
Gas Expans. Factor (1/Bg) [Sm3/m3]Normal100120140Assumed to be 1/pressure, with a reservoir depth of 1200m.
Chimney zone
Parameter [units]TypeMinBaseMax
Gross Rock Volume [km2-m]Normal3452928615120Weibull (2008) for direct estimate for low case, extrapolated across the Nyegga prospect in the high case.
Net/Gross Ratio [decimal]Normal0.0010.51Uncertainty with respect to suitable host rock, assumed to be 50:50 chance.
Porosity [decimal]Normal0.350.550.75Mean value from geotech borehole, wider range to account for carbonate formation and fracture-induced porosity.
Gas Saturation [decimal]Normal0.050.20.35Increased to reflect hydrate potential. Max case based on Stoian et al (2008) example from offshore Korea.
Gas Expans. Factor (1/Bg) [Sm3/m3]Constant164164164Based on Sloan & Koh 2008.
The large uncertainty in the reservoir parameters is accounted for by using stochastic models with a range of parameters. Stochastic models, based on the Monte Carlo method, were set up to handle the parameter ranges described above. Its 5000 realizations calculated a probabilistic range based on a random element constrained within the range of input parameters assigned previously. This approach is deemed the most optimal for dealing with the high degree of uncertainty involved in this first-order estimation.
Statistically the base case equates to the mode, while both the P50 and mean cases may be offset due to the skewed distributions used. Percentiles, such as P1, P50 and P99, relate to probabilities of a reservoir parameter being present with the respective quality. Reservoir parameters are given using the “minimum-base-maximum” value convention. As an example, the 10–50–120 distribution for the thickness of the hydrate zone gives a 99% probability of a hydrate zone at least 10 m thick being present, yet only a 1% chance that a 120 m thick zone is present in any of the 5000 realizations calculated. The shape of the distribution, either Normal or Stretched Beta, then defines which thickness is most likely to be chosen in the calculation (Figure 7).
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Figure 7. A graphical representation of the distributions of the various reservoir parameters for Nyegga’s three segments. The graphs illustrate the relative probability of a particular value to be chosen for the stochastic volumetric calculation. The peak of the curve, corresponding to the mode, stands a higher chance of being selected than the outlying points near the P99 and P1 end points. Skewed distributions are used particularly for the gas hydrate saturation parameter in order to account for both the relatively large upside potential while keeping a conservative P99 and base case. Please note that the y-axis is a measure of the probability of the respective reservoir parameter value being chosen in any particular stochastic calculation run. Please note the different x-axis scales for each diagram. For clarity, distribution ranges are tabulated in Table 1.
Figure 7. A graphical representation of the distributions of the various reservoir parameters for Nyegga’s three segments. The graphs illustrate the relative probability of a particular value to be chosen for the stochastic volumetric calculation. The peak of the curve, corresponding to the mode, stands a higher chance of being selected than the outlying points near the P99 and P1 end points. Skewed distributions are used particularly for the gas hydrate saturation parameter in order to account for both the relatively large upside potential while keeping a conservative P99 and base case. Please note that the y-axis is a measure of the probability of the respective reservoir parameter value being chosen in any particular stochastic calculation run. Please note the different x-axis scales for each diagram. For clarity, distribution ranges are tabulated in Table 1.
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Seismic interpretation, primarily on the JMF97 2D survey, provided the initial spatial constraint by outlining the extent of the BSR. Estimates of the thicknesses (column height, see Figure 8 and Table 2) of both the gas hydrate and free gas zone were based on OBS studies [56,57,58], as were the gas hydrate and free gas saturations. For the chimney zone, a GRV was calculated based on the chimney study of Weibull [60] extrapolated across the Nyegga prospect. “Traditional” reservoir parameters such as porosity are based on the geotechnical borehole 6404/5 GB1.

3.3.1. Area of Closure

Spatially, the reservoir is restricted to the BSR-defined lateral extent of the Nyegga prospect. The low case is defined by the interpretation of the central part of the BSR, the so-called “BSR Sweet Spot”. For the high case, previous BSR interpretations were used [62]. The base case is based on the same interpretation, but disregards the zones of uncertain BSR interpretations to the north and south-east.
An upside potential exists in other areas where BSRs have been identified. Seven other areas with BSRs have been mapped in the immediate area around the main Nyegga prospect [62], with a combined area of 658 km 2 . These areas, as well as other hydrate-prone zones on the Norwegian continental shelf, have not been included in the volumetric calculation but represent a considerable upside potential.

3.3.2. Column Height

The thicknesses and gas hydrate saturation of the hydrate system itself, both the solid hydrate-layer and the underlying free gas, is primarily defined by the OBS experiments of Bünz et al. [56], Westbrook et al. [58] and Faverola et al. [63].
Utilising P-wave velocities derived from the OBS experiments as interval velocities, it is possible to derive a time-depth relationship at the OBS stations.
This allows the OBS-derived P-wave velocities to be plotted directly onto the seismic profiles (Figure 9), serving both as a quality-control and for visualising the continuity of the various zones of anomalous velocities. Furthermore, a time-depth relationship allows the plotting of time-domain interpreted horizons onto the OBS depth-domain “well section” (Figure 8).
Table
Table 2. Summary of the column height and saturation values derived from the 6404/5 GB1 borehole as well as the OBS sites of Bünz et al. [56, Westbrook et al. [58] and Faverola et al. [63].
Table 2. Summary of the column height and saturation values derived from the 6404/5 GB1 borehole as well as the OBS sites of Bünz et al. [56, Westbrook et al. [58] and Faverola et al. [63].
StationWater depth (m)Depth to BSR (mbsl)Hydrate zoneFree gas thicknessHydrate saturationFree gas saturationCommentsReference
6404/5 GB196012202515 to >40??Free gas zone poorly imaged by borehole ending 50m below the BSR6404/5 GB1 borehole
OBS 758 1052max 12018m12-20% Two additional gas layers at 1128 (30m thick) and 1415 (35m thick)Westbrook et al 2008
JM516965124547 6-12%0.7-14%Low hydrate estimate = hydrate in frame, high-estimate = hydrate as pore fill. Low gas estimate = homogeneous distribution, high gas estimate = patchy distribution.Bünz et al 2005
JM51794512255646-9011-21%0.9-19%
JM52392112014250-854-8%0.9-18%
JM52491911993260-682.5-5%0.7-14%
1Z7089567037 0.55-15%
3H7409987129 0.5-14%
4Z706no BSR Gas trapped beneath GDF, 0.3-8%Faverola et al 2009
5Z733no BSR Gas trapped beneath GDF, 0.2-5.5%
6H765no BSR No LVZ1 seen on OBS data
GeoX input 10 - 50 -12020 - 40 - 802.5 - 7.1 - 210.2 - 0.7 - 19
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Figure 8. Summary of ocean-bottom seismic (OBS) data of Bünz et al. [56], Westbrook et al. [58] and Faverola et al. [63] compared to the 6404/5 GB1 measured P-wave velocity. The bottom simulating reflection (BSR) well top is defined on the basis of the onset of the low velocity anomaly on the OBS data, and is notably absent at stations 4Z, 5Z and 6H. The remaining tops are defined by the intersection of the interpreted horizons with the “well path” of the OBS stations. Note that GDF = glacigenic debris flow.
Figure 8. Summary of ocean-bottom seismic (OBS) data of Bünz et al. [56], Westbrook et al. [58] and Faverola et al. [63] compared to the 6404/5 GB1 measured P-wave velocity. The bottom simulating reflection (BSR) well top is defined on the basis of the onset of the low velocity anomaly on the OBS data, and is notably absent at stations 4Z, 5Z and 6H. The remaining tops are defined by the intersection of the interpreted horizons with the “well path” of the OBS stations. Note that GDF = glacigenic debris flow.
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Figure 9. OBS-derived P-wave velocities as displayed on a composite seismic line. The illustration also provides an overview of the interpreted horizons. Note particularly the cross-cutting nature of the bottom simulating reflection (BSR). Furthermore, the P-wave velocity at OBS station 6H indicates no free gas layer at the expected BSR layer, leading to the reduction of the BSR-extent of Bünz et al. [62] in the volume calculation. Well tops are based on the OBS data. OBS data from Bünz et al. [56], Westbrook et al. [58] and Faverola et al. [63].
Figure 9. OBS-derived P-wave velocities as displayed on a composite seismic line. The illustration also provides an overview of the interpreted horizons. Note particularly the cross-cutting nature of the bottom simulating reflection (BSR). Furthermore, the P-wave velocity at OBS station 6H indicates no free gas layer at the expected BSR layer, leading to the reduction of the BSR-extent of Bünz et al. [62] in the volume calculation. Well tops are based on the OBS data. OBS data from Bünz et al. [56], Westbrook et al. [58] and Faverola et al. [63].
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3.3.3. Porosity

Porosity was measured at the nearby geotechnical borehole 6404/5-GB1 (Figure 10), and is restricted to a narrow distribution of 0.49–0.55–0.61.
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Figure 10. Wireline and measured data from the 6404/GB5 geotechnical borehole. Unfortunately, poor data quality makes the wireline data of limited use. The porosity measurements (5th track), however, are useful and provide constraints for the reservoir. Vertical seismic profiling (VSP), shown in the 6th track, appears to indicate a slightly higher velocity in a 30 m interval above the BSR, a zone that has been interpreted as the solid gas hydrate zone. Porosity and unit weight were measured twice, once offshore and once onshore. Plotting them on the same track does not reveal major differences in the trends. Data is provided by Statoil, and is the property of the Norwegian Deepwater Programme [64,65]. Wireline logs are digitalised by hand and inaccuracies need to be considered.
Figure 10. Wireline and measured data from the 6404/GB5 geotechnical borehole. Unfortunately, poor data quality makes the wireline data of limited use. The porosity measurements (5th track), however, are useful and provide constraints for the reservoir. Vertical seismic profiling (VSP), shown in the 6th track, appears to indicate a slightly higher velocity in a 30 m interval above the BSR, a zone that has been interpreted as the solid gas hydrate zone. Porosity and unit weight were measured twice, once offshore and once onshore. Plotting them on the same track does not reveal major differences in the trends. Data is provided by Statoil, and is the property of the Norwegian Deepwater Programme [64,65]. Wireline logs are digitalised by hand and inaccuracies need to be considered.
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For the chimney zone, porosity is assigned a broader range centered upon the same base case, namely 0.35–0.55–0.75. This range is designed to account for the possibility of increased authigenic carbonate formation lowering the porosity, particularly in the uppermost chimney zones. On the other hand, increased fracture porosity could be generated by increased fluid flux.

3.3.4. Net to Gross

Hustoft et al. [55] illustrate a series of porous and permeable zones suitable for hydrate formation. A quick estimate suggest that this “reservoir” accounts for approximately 50% of the area of interest. A wide NTG range of 0–1 is thus used to account for the large uncertainty due to limited ground truth.

3.3.5. Gas Expansion Factor

Gas compressibility is defined by the relative amount of hydrate-bound gas compared to the same gas at standard P-T conditions. The base case assumes full cage occupancy, with 164 units of methane held within one unit of hydrate [2]. A constant value of 164 is thus used for the gas hydrate zone.
For the free gas zone, compressibility is assumed to be 1/pressure. Given that the prospect lies only a few hundred meters beneath the seafloor at approximately 1200 m depth, and assuming hydrostatic pressure, a gas expansion factor range of 100–120–140 was used.

3.3.6. Gas Hydrate Saturation

3.3.6.1. Hydrate and Free Gas Zone

As summarized by Table 2, both the gas hydrate saturation and the free gas saturation at the Nyegga prospect are low, on the order of 1–2% of the pore space. This is similar to other Class 4 hydrate reservoirs, as the <1% saturation reported from the Cascadia margin by Milkov et al. [66]. At Cascadia, Riedel et al. [35] outline four essentially independent methods for estimating the hydrate saturation, yet still come up with a large uncertainty of <5% to >25% of gas hydrate saturation. Similar saturations have been obtained through a multi-channel seismic analysis at the Korean Ulleung Basin, where Stoian [67] calculated a 1–4% gas hydrate saturation.
Even for well studied hydrate deposits where ground truth is available, gas hydrate saturations vary widely. As an example, [32] outline Gulf of Mexico gas hydrate saturations of 1.5–6%, 1–12% and >20% depending on which method for calculation is used [68,69,70].
At the Nyegga prospect, depending on the model of hydrate formation used, a heterogeneous gas hydrate saturation of up to 10–20% was calculated by Bünz et al. [56]. Gas hydrate saturation of up to 12% were predicted using a frame-only model, while gas hydrate saturation of up to 20% were predicted for the frame-and-pore model [58].
With this uncertainty in mind, a broad yet conservative gas hydrate saturation range from 0.025 (P99) to 0.071 (mode) to 0.21 (P1) for the hydrate zone was used. A free gas saturation from 0.002 (P99) to 0.007 (mode) to 0.19 (P1) is assigned for the free gas zone.
High values of 0.21 and 0.18 are deemed to represent possible “sweet spots” where high and focused fluid flux forms higher saturation hydrate deposits.

3.3.6.2. Chimney Structures

Chimney structures are expected to contain higher saturations of gas hydrates than the hydrate zone, due to the focused fluid flux thought to form them. Chimney structures typically lie below complex pockmarks [38]. Furthermore, such complex pockmarks are the only locations where solid gas hydrates have been inferred at shallow depth [51] and subsequently sampled with gravity corers [52,71]. The pockmark-chimney interaction is further outlined by Hustoft et al. [72].
It follows that the Nyegga chimney structures have been assigned a more optimistic hydrate saturation range of 0.05–0.2–0.35. To account for the uncertainty in whether the chimneys actually contain hydrate, as raised by Paull et al. [61], cases were calculated without the chimney component. The chimney zone hydrate is thus considered an upside of the Nyegga prospect.

4. Results

Volumes of in-place gas, even in the most pessimistic P90 case, amount to 151–183 GSm 3 , depending on whether the chimney zone is included or not. Out of the three segments, the gas hydrate zone contains the majority of resources (69% of the total mean case), followed by the free gas zone (19%) and the chimney zone (12%, Table 3).
Table
Table 3. Results of in-place volumes of hydrate-bound methane at Nyegga. Intermediate volumes are given for comparison. To calculate the deterministic volume, only the base case reservoir parameters were used. In contrast, wide distributions were used to generate the stochastic spread.
Table 3. Results of in-place volumes of hydrate-bound methane at Nyegga. Intermediate volumes are given for comparison. To calculate the deterministic volume, only the base case reservoir parameters were used. In contrast, wide distributions were used to generate the stochastic spread.
DeterministicStochastic
Gas hydrate zoneunit MeanP90P50P10
Gross rock volumeGSm3112.7122.157.3115.3195.9
Net rock volumeGSm356.460.921.054.3109.3
HC pore volumeGSm32.23.00.82.45.9
Gas initially in place (GIIP)GSm3361.2489.8133.5398.7967.5
Free gas zone
Gross rock volumeGSm390.295.357.791.6138.9
Net rock volumeGSm345.147.419.443.780.4
HC pore volumeGSm30.21.10.10.72.7
Gas initially in place (GIIP)GSm320.8134.717.489.4313.6
Chimney zone
Gross rock volumeGSm39.39.36.49.312.1
Net rock volumeGSm34.64.72.24.57.5
HC pore volumeGSm30.50.50.20.50.9
Gas initially in place (GIIP)GSm383.885.432.577.2149.8
Nyegga without chimneys
Gas initially in place (GIIP)GSm3382.0624.5150.9488.11281.1
tcf13.522.15.317.245.2
Nyegga total (all 3 segments)
Gas initially in place (GIIP)GSm3465.8709.9183.4565.31430.9
tcf16.425.16.520.050.5
Please note GSm3 = 109 standard cubic metres, tcf = 1012 standard cubic feet
As the volumes already indicated, the gas hydrate and free gas zones seem to be the most important constituents of the prospect. This is also obvious from the variance diagram (Figure 11), where the parameters assigned to the aforementioned zones dominate. The variance is quite simply a measure of statistical dispersion, and illustrates the parameters with the largest spread that contribute the most to the final result.
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Figure 11. A variance diagram showing the relative importance of the various reservoir parameters on the result. Note the dominance of the uncertainty related to the gas hydrate zone, particularly gas hydrate saturation, the column height of the gas hydrate zone and the net to gross ratio.
Figure 11. A variance diagram showing the relative importance of the various reservoir parameters on the result. Note the dominance of the uncertainty related to the gas hydrate zone, particularly gas hydrate saturation, the column height of the gas hydrate zone and the net to gross ratio.
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5. Discussion

Regional hydrate assessments have been conducted in a wide range of settings. In the marine environment, most of these were based on the delineation of the bottom simulating reflection (BSR) and subsequent extrapolation of poorly constrained reservoir parameters across the area. To ease comparison between very different hydrate provinces, a resource density was calculated based on the reported in-place resources and the areal extent of the BSR (Table 4, Figure 12). The range of those, from 0.005 GSm 3 /km 2 to 2.129 GSm 3 /km 2 , represents both the uncertainty range with estimating hydrate-bound volumes and the geological differences between these provinces. On the one side, 0.005 GSm 3 /km 2 resembles the average methane hydrate resource density extrapolated across the whole Earth landmass. On the other side, 2.129 GSm 3 /km 2 is a reasonable resource density seen in Norwegian conventional gas fields.
The Nyegga prospect, with a range of 0.08 GSm 3 /km 2 to 0.64 GSm 3 /km 2 , plots in between these two end-members. In terms of its areal extent, it is a fraction of the other hydrate provinces, most closely related to the West Svalbard margin investigated by Hustoft et al. [73]. Its mean resource density (0.32 GSm 3 /km 2 ) is comparable to both the West Svalbard site (0.35 GSm 3 /km 2 , Hustoft et al. [73]) and the Nankai Trough (0.23 GSm 3 /km 2 , Ichikawa and Yonezawa [30]). Nyegga’s low case, 0.08 GSm 3 /km 2 , nonetheless resembles the resource density calculated for the whole ocean (0.06 GSm 3 /km 2 , MacDonald [74]). Compared to geologically similar provinces, distinguished by large areas of low saturations, Nyegga seems to have a slightly higher resource density than the regional Gulf of Mexico site, yet a lower resource density than both the Blake Ridge and New Zealand’s Fiordland and Hikurangi provinces.
Comparing the recent investigations of the marine Gulf of Mexico (1.33 GSm 3 /km 2 in the mean case) system by the Minerals Management Service [33] to the assessment of the Alaskan North Slope (0.02 GSm 3 /km 2 in the mean case) by the USGS [25] highlights the general difference of the permafrost deposits compared to the marine provinces. Nonetheless, production tests are being undertaken on permafrost hydrate, where easier logistics and a well developed infrastructure make such projects economically feasible. The relatively low resource density at the Alaskan North Slope permafrost province, highlights the inadequacy of using the resource density as the sole indicator of future development. While the overall resource density appears to be low on the Alaskan North Slope, its sweet-spot deposits, onshore location and proximity to conventional petroleum infrastructure is likely to make the North Slope an early candidate for commercial production.
In absolute value, the GIIP numbers of approximately 625 to 715 GSm 3 , depending on whether the chimney segment is included, are higher than the originally in-place resource of the conventional Ormen Lange gas field (439 GSm 3 NPD [75]). However, when compared to the area it covers the Nyegga prospect has a considerably lower in-place resource density (0.32 GSm 3 /km 2 , Table 4) compared to the mega-field Troll (3.4 GSm 3 /km 2 ), the high-pressure, high-temperature field Kristin (1.24 GSm 3 /km 2 ) and Ormen Lange (1.3 GSm 3 /km 2 , NPD [76]). The only discovery on the Norwegian continental shelf with a comparable energy per unit area density is Peon, whose 35 GSm 3 in-place resources are spread over 80 km 2 (0.44 GSm 3 /km 2 ) [76,77].
Table
Table 4. Comparison of the resource density at the Nyegga prospect and other hydrate and conventional deposits worldwide. Note that permafrost hydrate provinces are denoted with italics. Data from this study, Collett et al. [25], Collett [26], Ichikawa and Yonezawa [30], Frye [33], Hustoft et al. [73], MacDonald [74], Milkov and Sassen [78], Pecher et al. [79], Laberg et al. [80], Hovland et al. [81], Milkov and Sassen [82], Lodolo et al. [83], Fohrmann [84], Gorman [85] and NPD [76]. For ease of comparison, the data presented here is also plotted in Figure 12.
Table 4. Comparison of the resource density at the Nyegga prospect and other hydrate and conventional deposits worldwide. Note that permafrost hydrate provinces are denoted with italics. Data from this study, Collett et al. [25], Collett [26], Ichikawa and Yonezawa [30], Frye [33], Hustoft et al. [73], MacDonald [74], Milkov and Sassen [78], Pecher et al. [79], Laberg et al. [80], Hovland et al. [81], Milkov and Sassen [82], Lodolo et al. [83], Fohrmann [84], Gorman [85] and NPD [76]. For ease of comparison, the data presented here is also plotted in Figure 12.
ProvinceAreaIn-place resourcesResource density (GSm3/km2)Reference
(km2)(GSm3 g.e.)
minmeanmaxminavemax
 
Hydrate prospects/ provincesNyegga (all three zones)2 2541837101 4310.0810.3150.635This study
Nyegga (hydrate and free gas)2 2541516251 2810.0670.2770.568This study
Barents Sea270.190 0.3800.007 0.014Laberg et al 1998
West Svalbard3 000 1 035 0.345 Hustoft 2009
Gulf of Mexico regional22 5002 000 3 0000.089 0.133Milkov and Sassen 2001
Gulf of Mexico "sweet spots"23 0008 000 11 0000.348 0.478Milkov and Sassen 2001
Gulf of Mexico457 933314 000607 000975 0000.6861.3262.129Frye 2008
Niger Delta568 951 1.674 Hovland 1997
Hikurangi and Fjordland margins, NZ50 000 20 000 0.400 Pecher et al 2004
Fiordland margin "sweet spots"352 48 0.136 Fohrmann 2009, Gorman 2008
Nankai Trough32 000 7 40060 000 0.2311.875Ichikawa and Yonezawa 2002
Blake Ridge26 000 28 000 1.077 Milkov and Sassen 2002
Håkon Mosby Mud Volcano1.8 0.300 0.167 Milkov and Sassen 2002
South Shetland Margin, Antarctica1 362 2 360 1.733 Lodolo et al 2002
near-well Mallik, Mackenzie Delta0.250.137 0.1680.548 0.672Huang et al 2009
Alaskan North Slope144 7647152 4064 4690.0050.0170.031Collett et al 2008
Milne Point, northern Alaska0.35 to 6.9individual prospects from 0.16 to 5.260.3100.6571.352Inks et al 2009
 
Conventional gas fieldsOrmen Lange345 439 1.272 NPD 2010
Kristin84 104 1.238 NPD 2010
Troll700 2 350 3.357 NPD 2010
Peon80 35 0.438 NPD 2010
 
GlobeOcean361 132 000 21 000 000 0.058 MacDonald 1990
Land148 940 000 740 000 0.005 MacDonald 1990
Total510 072 000 20 000 000 0.039 Collett 2002
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Figure 12. Graphical comparison of the resource density at the Nyegga prospect and other hydrate and conventional deposits worldwide. The diamonds indicate the average resource density, while the minimum and maximum resource densities are represented by triangles and circles, respectively. Data source identical to Table 4. Please note the logarithmic x-axis.
Figure 12. Graphical comparison of the resource density at the Nyegga prospect and other hydrate and conventional deposits worldwide. The diamonds indicate the average resource density, while the minimum and maximum resource densities are represented by triangles and circles, respectively. Data source identical to Table 4. Please note the logarithmic x-axis.
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In summary, the resource density at Nyegga is comparable to other hydrate provinces. Furthermore, the large spread of calculated resources at both Nyegga and other hydrate provinces illustrates the large uncertainty involved in quantifying gas hydrate deposits. Nonetheless, stochastic modelling as employed in this study is critical to constrain the range of probable in-place volumes at any given prospect.

6. Conclusions

  • A gas hydrate prospect is defined in the Norwegian Sea.
  • The gas hydrate resource, 710 GSm 3 in the mean case, appears to be significant for a prospect on the Norwegian Continental Margin.
  • Large uncertainty in calculated in-place volumes exists, primarily due to the lateral variations in reservoir parameters (3D reservoir extent and gas hydrate saturation being the most important).
  • Using the employed reservoir parameters, it appears that the gas hydrate and free gas zones contribute most to the total in-place resources. Chimneys, assuming that they are at least partially hydrate-filled, contribute to localized high saturation hydrate accumulations.
  • The resource density of the Nyegga prospect, 0.32 GSm 3 /km 2 , is generally in line with that calculated for other hydrate provinces, though the large spread of the estimates emphasizes the large uncertainties involved.
  • Apart from their economic value, the hydrate-held methane could, under changing P-T conditions, potentially be released into the ocean and/or the atmosphere. Further work is required to test this hypothesis.
  • Further work is required to determine the producibility of this resource. A hydrate-specific simulator could, for example, assist in quantifying potential recovery factors.
  • It is questionable whether the Nyegga resource will ever be commercially produced, given its low saturation and large lateral extent. At the very least, a hydrate-specific reservoir simulator needs to be employed in a feasibility study.

Acknowledgements

This study was conducted as part of an MSc at the University of Tromsø. Bayerngas Norge AS, the SEABED consortium, Statoil and Fugro Geos provided parts of the data used. Bayerngas Norge AS is further acknowledged with generous financial, technical and moral support that made this study possible during Kim Senger’s employment period. Geoknowledge AS provided access to the GeoX software. Finally, the authors would like to thank four anonymous reviewers for their constructive comments that have improved this manuscript.

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MDPI and ACS Style

Senger, K.; Bünz, S.; Mienert, J. First-Order Estimation of In-Place Gas Resources at the Nyegga Gas Hydrate Prospect, Norwegian Sea. Energies 2010, 3, 2001-2026. https://doi.org/10.3390/en3122001

AMA Style

Senger K, Bünz S, Mienert J. First-Order Estimation of In-Place Gas Resources at the Nyegga Gas Hydrate Prospect, Norwegian Sea. Energies. 2010; 3(12):2001-2026. https://doi.org/10.3390/en3122001

Chicago/Turabian Style

Senger, Kim, Stefan Bünz, and Jürgen Mienert. 2010. "First-Order Estimation of In-Place Gas Resources at the Nyegga Gas Hydrate Prospect, Norwegian Sea" Energies 3, no. 12: 2001-2026. https://doi.org/10.3390/en3122001

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