Evidence for Widespread, Low Saturation Gas Hydrate in The

Home , Barents Sea

Evidence for Widespread, Low Saturation Gas Hydrate in the

Barents and Norwegian Seas

Thesis

Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in

the Graduate School of The Ohio State University

Ryan Conover Heber

Graduate Program in Earth Sciences

The Ohio State University

2020

Thesis Committee

Dr. Ann Cook, Advisor

Dr. Elizabeth Griffith

Dr. Derek Sawyer

Copyrighted by

Ryan Conover Heber

2020

iii

Abstract

The distribution of marine natural gas hydrate in European offshore areas is not well constrained, yet, accurately characterizing hydrate accumulations is of particular interest due to potential climate and carbon cycle interactions. Using petroleum industry well logs to identify gas hydrate occurrence in the Barents and Norwegian Seas is a regionally novel approach. This study finds that in industry wells under at least 350 meters of water,

13 out of 18 wells in the Barents Sea and 36 out of 46 wells in the Norwegian Sea have potential hydrate accumulations, given resistivity increases (0.5-5 Ωm) above background values within the gas hydrate stability zone. Although the hydrate saturation is likely low, the presence of hydrate was found in a significant portion of wells, implying low concentrations of hydrate may occur over both areas. In the Norwegian Sea, geostatistical results show clustering of gas hydrate along the head scarp of the Storegga Slide where gas hydrate has been previously identified and inferred in seismic data. In the Barents

Sea, the resistivity increases of greatest magnitude occur in the Bjørnøya Trough, where thermobaric conditions allow for the thickest gas hydrate stability zone (~400 mbsf) across the Barents Sea shelf.

Dedication

For edges.

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Acknowledgments

I would like to thank my advisor Dr. Ann Cook and her postdoctoral student Dr. Alexey

Portnov for their input and encouragement. This research was funded by NSF Award number #1752882.

Vita

2017 ...... B.S. Earth Sciences, The Ohio State University

Fields of Study

Major Field: Earth Sciences

Table of Contents

Abstract ...... ii

Dedication ...... iii

Acknowledgements ...... iv

Vita ...... v

List of Tables ...... vii

List of Figures ...... viii

Introduction ...... 1

Methods ...... 8

Results ...... 13

Discussion ...... 25

Conclusion ...... 30

References ...... 31

List of Tables

Table 1. Resistivity Increase Classification Criteria ...... 12

Table 2. Gas Compositions of Barents and Norwegian Sea Wells ...... 14-15

Table 3. Barents and Norwegian Sea Well Ranks ...... 17

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List of Figures

Figure 1. Study Area and Dataset ...... 3

Figure 2. Bathymetry and Industry Wells. a. Norwegian Sea. b. Barents Sea ...... 7

Figure 3. a. Gas Hydrate Stability Curves. a. Well 7120/2-1. b. Well 6305/1-11 ...... 16

Figure 4. Resistivity Strength Well Ranks ...... 18

Figure 5. Norwegian Sea Log Plot. 6706/11-1 ...... 20

Figure 6. Barents Sea Log Plots. a. 7321/8-1. b. 7321/7-1 ...... 21

Figure 7. Norwegian Sea Log Plots. a. 6305/5-3. b. 6506/6-1. c. 6608/10-3 ...... 22

Figure 8. Interpolated Resistivity Increase Strength. a. Norwegian Sea. b. Barents Sea .. 24

viii

Introduction

Natural gas hydrate is an ice-like clathrate of water and natural gas (Sloan and Koh,

2007) existing in marine sediments, permafrost regions and under ice sheets (Collett,

2002; Collett et al., 2011; Portnov et al., 2016). Despite their worldwide distribution and interest from academia and industry (Shipley et al., 1979; Kvenvolden et al., 1993;

Makogon, 2010), there still remain questions regarding the role of gas hydrates in past and present climate change (Wadham et al., 2008; Ruppel and Kessler, 2016), their geo- hazard potential ((McIver, 1982; Frye, 2008; McConnell et al., 2012) and energy capacity

(Boswell and Collett, 2011; Johnson, 2011).

In contrast to the United States, Japan, China, Korea, and India, European countries have received less national investment into natural gas hydrate research, specifically in drilling, coring and well logging of subseafloor gas hydrate systems (Minshull et al.,

2019). In Norway, for example, most sub seafloor studies on gas hydrate involve only seismic data and modeling (Andreassen et al., 1990; Mienert et al., 1998;

Vadakkepuliyambatta et al., 2013; Vadakkepuliyambatta et al., 2015). Traditionally, the presence of hydrate is suggested in seismic data by bottom simulating reflections (BSR) that generally run parallel to the seafloor with opposite polarity (Shipley et al., 1979;

Hyndman et al., 1992). Although BSRs are potential indicators of gas hydrate accumulations, there are a fair number of locations where gas hydrate was found without a BSR, as well as locations with a BSR that do not have evidence of hydrate (Wood and

Ruppel, 2000; Tsuji et al., 2009; Majumdar et al., 2016). Unlike seismic data, downhole well logs can better confirm the presence of gas hydrate in specific depth intervals and provide information regarding the sediment or rock type, in situ characteristics of hydrate, and hydrate saturation (Collet and Ladd, 2000; Goldberg et al. 2009; Cook et al.,

2010).

Although most gas hydrate research targets are accumulations with high gas hydrate concentrations greater than 60%, the lower-concentration hydrate systems are still an important research target given their combined magnitude on a global scale. Boswell and

Collett (2011) detail the range of gas in place global volume estimates for global gas hydrates over the past 50 years, however, these estimates are wide ranging (3.1 x 1015 m3

(McIver et al., 1981) to ~3 x 1018 m3 (Trofimuk et al., 1973) and not well constrained.

The gas in place volumetric estimate for global low saturation systems is given to be roughly 3 x 1015 m3 (Boswell and Collett, 2011).

I focus the study on European high-latitude offshore regions where hydrate has greater potential for dissociation due to climate-driven ocean temperature rise (Ferré et al.,

2012). I employ a novel technique for analyzing hydrates in the region, utilizing geophysical industry well logs from the Barents and Norwegian Seas that are publicly available through the Norwegian Petroleum Directorate (Figure 1). A similar procedure was used by Majumdar et al. (2017) in the U.S. Gulf of Mexico. Wells offshore Norway were selected based on the distribution of the gas hydrate stability zone (GHSZ) modeled at each well location and the availability of well log data within that zone. Gas hydrate is an electrical insulator; therefore, wells were analyzed for increases in electrical resistivity above a calculated or estimated background as gas hydrate-bearing intervals. By looking

2 at wells not specifically drilled for the study of gas hydrates, these new results develop a new picture of gas hydrates in the subsurface which may have implications for anthropogenic climate change in the Barents and Norwegian Sea.

Figure 1. Area of study showing the Barents and Norwegian Sea and locations of industry wells used in this study in red.

Geologic Setting

The Barents Sea is located at a crossroad of the warm Gulf Stream and cold polar waters, making it a vulnerable Arctic climate transition zone (Hansen and Østerhus, 2000; Ezat et al., 2014). The area has been shaped by a complex geologic history involving tectonic uplift and subsidence and glacial erosion (Larsen et al., 1989; Doré and Jensen, 1996;

Patton et al., 2016; Lasabuda et al., 2018). Such processes have promoted sub seafloor fluid flow and gas seepage in the water column, leaving extensive pockmark fields and craters on the seafloor (Solheim and Elverhøi, 1985; Chand et al., 2012; Mazzini et al.,

2016; Portnov et al., 2016; Andreassen et al., 2017; Serov et al., 2017). Fluid migration is controlled by faults and fractures which act as pathways for natural gas and hydrocarbons

(Ostanin et al., 2013; Vadakkepuliyambatta et al., 2013).

Many uncertainties persist in the Barents Sea regarding gas hydrate saturation, distribution, and volume (Minshull et al., 2019). Gas hydrate has been inferred in the

Barents Sea, by the presence of BSRs interpreted from multi-channel seismic data

(Vadakkepuliyambatta et al., 2017). The BSRs typically occur in Jurassic age lithified sediments or in glacial sediments ranging in age from Pleistocene to Holocene

(Andreassen et al., 1990), and can range from 225 to 345 meters below seafloor (mbsf)

(Laberg et al., 1998; Rajan et al., 2013). Gas hydrates have been identified and sampled in the Barents Sea at seafloor seeps as well as nonpermafrost-related pingos (Hong et al.,

2017; Hong et al., 2018; Waage et al., 2019). Vadakkepuliyambatta et al. (2017) modeled pure methane hydrate stability in the Barents Sea and only found a subseabed GHSZ thickness up to 150 m in the deepest water depths of the Bjørnøya Trough region where water depths are greater than 400 m. However, in the presence of higher order

4 hydrocarbons such as ethane or propane, the base of the GHSZ thickens up to 450 mbsf in the same Bjørnøya Trough region, in this case, 3% ethane and 1% propane with a geothermal gradient of 22.8 °C/km (Chand etal., 2008). The depths of the BSRs in the region (e.g., 220 mbsf at 400 water depth; Laberg et al., 1998) support the assumption that gas mixes are not pure methane. Gas hydrates in the Barents Sea show little promise of economic value given their likely occurrence at low saturations in either fractures of lithified Jurassic formations, or Pleistocene to Holocene glacial sediments (Andreassen et al., 1990; Vadakkepuliyambatta et al., 2017). However, the amount of gas hydrate may be important for understanding the gas hydrate-climate positive feedback system, as hydrate dissociation may induce methane releases to the atmosphere (de Garidel-Thoron et al., 2004).

The Norwegian Sea has a well-defined continental slope covered by a thick sediment section of up to 800 m (Johnson and Heezen, 1967). Basin formation was the result of several rifting events in the Late Paleocene to Early Eocene, inducing thermal subsidence

(Skogseid and Eldholm, 1995). Compressional forces during the Late Eocene to Mid

Miocene produced dome structures, of which, some are known to accommodate hydrocarbon reservoirs (Doré and Lundin, 1996; Brekke, 2000). Seafloor evidence for gas hydrate is present at water depths between 550 to 1300 m (Bünz et al., 2003).

Submarine pingos (mounded or domed structures of accumulated hydrate) have been observed in the Norwegian Sea, indicating the presence of shallow gas hydrate and active fluid leakage to the seafloor (Hovland and Svensen, 2006; Jose et al., 2008; Mazzini et al., 2016). Senger et al. (2010) estimates Norwegian Sea sediments hold an estimated

68,125 m3 of both hydrate and free gas, however, economic prospects are still low given they mainly occur in diffuse systems.

In the southern part of the Norwegian Sea, the world’s largest known mass wasting event, the Storegga Slide, is visible on the seafloor bathymetry (Bryn et al., 2005) (Figure 2).

The slide moved close to 5600 km3 of sediment and slide deposits are 450 m thick in some locations (Bugge, 1987). The slide took place approximately 8.2 ka (Haflidason et al., 2001). Gas hydrate decomposition may have been a precursor based a well-defined

BSR observed on the northeast side of the slide scar (Bugge, 1983; Mienert et al., 1998;

Mienert et al., 2003) at depths of 250 to 350 mbsf (Bünz et al., 2003; Mienert et al.,

2005). Along with BSRs, seafloor pockmarks and seismic evidence of vertical fluid migration can be observed at the Storrega Slide and point to presence of gas hydrate

(Hustoft et al., 2007). Moreover, hydrate samples were obtained from a pockmark field along the northeastern corner of the Storegga Slide (Ivanov et al., 2007), and hydrate saturations from this area have been estimated to range from 2-15% based on ocean bottom seismometer data (Minshull et al., 2019).

Figure 2. a. Bathymetry and industry well logs in the Norwegian Sea with the profile of the Storegga Slide visible in the southwest corner of the map. b. Bathymetry and industry well logs in the Barents Sea with the profile of the Bjørnøya Trough visible in the central portion of the map.

Methods

Gas Hydrate Stability

In marine environments, the GHSZ is controlled by pressure, temperature, gas content, and pore water salinity (Dickens and Quinby-Hunt, 1997; Xu and Ruppel, 1999). By incorporating these variables into the phase boundary model for hydrates, the bottom of the gas hydrate stability zone (BGHSZ) can be identified and more accurately characterize hydrate systems and their extent. The BGHSZ was calculated for each well in Figure 1 using the Colorado School of Mines Hydrate (CSMHYD) Program, an open source software available through the Colorado School of Mines (Sloan and Koh, 2007).

The software models the thermodynamic stability of hydrates by calculating pressure at a given temperature, gas composition, and salinity. The resulting pressure is converted to depth in order to draw a temperature-depth curve for hydrate stability. For each well, bottom water temperature (BWT) was acquired from CTD (thermal conductivity, temperature, depth) data from the world ocean database (Boyer et al., 2013). Additional well specific inputs such as water depth, bottom hole temperature (BHT), and gas composition were acquired from public well reports on the Norwegian Petroleum

Directorate website. Hydrate stability was calculated twice for each well, once assuming a pure methane gas composition and a second time using gas sample composition measurements unique to that well (Table 2). If no gas composition data was available for a well, a plausible composition of 90% methane, 7% ethane, and 3% propane was used

8 for hydrate stability modeling in both the Barents and Norwegian Sea, based on work from Ostanin et al. (2013).

Geothermal gradients in the Barents Sea can range from 25-65° C/km, changing quickly due to proximity to the mid-ocean ridge or heat-conductive salt diapers (Bugge et al.,

2002; Vanneste et al., 2015). Local conditions such as BWT and BHT are responsible for a highly variable GHSZ thickness (Chand et al., 2008), therefore geothermal gradient and gas hydrate stability are modeled based on local temperature variables available at each well rather than using regional heat flow models.

The geothermal gradient was calculated using temperature and depth differentials at the seafloor and bottomhole. However, bottomhole temperature generally underestimates true formation temperature since it represents a measurement of the drilling fluid, which is typically cooler than the formation (Deming, 1989). Corrections are available (e.g., Peters and Nelson, 2012), but require a minimum of three logging runs that record time and temperature, which was not available in the existing dataset. Therefore, calculated geothermal gradients are likely lower than true gradients and if so, the BGHSZ is somewhat overestimated and deeper than the actual BGHSZ. By modeling the conditions under which hydrate can form at each individual well, regional variabilities in lithology and heat flux are controlled for, thereby providing a better estimation of the local GHSZ.

Gas Hydrate Identification

Since gas hydrate dissociation can occur due to the thermobaric conditions in shallow water depths between 250 to 350 m (Vadakkepuliyambatta et al., 2017), only industry wells under at least 350 m water depth from the Barents Sea and the Norwegian Sea

(Figure 2) were downloaded from the Norwegian Petroleum Directorate public database

(NPD FactPages, 2016). Digital well log data was acquired through The Centre for

Arctic Gas Hydrate, Environment, and Climate at the Arctic University of Norway. The logging data was not of equal quality from well to well. Missing data and erroneous signals were observed in the shallow sections of many wells. Any well deemed to have insufficient data quality was removed from the dataset, leaving a total of 18 wells in the

Barents Sea and 46 wells in the Norwegian Sea.

Gas hydrates are electrical insulators and can be identified by increases in resistivity on well logs (Pearson et al., 1983; Goldberg et al., 2009; Waite et al., 2009). Along with resistivity, hydrate can also be identified by increases in P-wave velocity because gas hydrate increases the elastic moduli of the bulk sediment system. P-wave velocity increases, however, generally only occur with moderate to high saturation reservoirs (Sh>

0.4) (Yun et al., 2005), because lower saturations do not alter the elastic moduli. There is also a small decrease in bulk density due to the difference between the density of brine rich pore water (~1.02 g/cc) and gas hydrate (~0.92 g/cc), however, this change can be difficult to identify, even at high gas hydrate saturations (Sh> 0.6) (Goldberg et al., 2009). Therefore, because resistivity is the most sensitive to hydrate at any saturation, the industry well logs are primarily analyzed for increases in resistivity above background.

Background resistivity, Ro, is estimated in two ways: 1) visually from a water saturated portion of the resistivity log (often identified by low resistivity, conductive interval), or

2) by using the porosity (!) , m the cementation factor, Rw the resistivity water in the pore, and a the tortuosity factor (Archie, 1942):

# = &'( Equation 1 $ )* 10

Although resistivity measurements were available in every well, only ten wells had additional data for analysis within the zone of interest. Meaning, in 54 wells, only gamma ray and resistivity measurements were present within the GHSZ, and thus background resistivity was estimated visually (#1 above). This method contains inherent error since

Ro can vary due to variation in lithology, but in the absence of logs such as bulk density or neutron porosity it provides the best possible method to identify hydrate presence.

If either bulk density or neutron porosity is available, Equation 1 was used with a =1 and

Rw = 0.3 Ωm (Winsauer, 1952). The cementation exponent, m, has some physical meaning when a = 1, and tends to depend on grain size distribution and falls somewhere between 1.4 and 2.5 for sandstones, therefore the commonly applied value of m = 2 is used for this analysis (Jackson, 1978; Glover et al, 1997). It should be noted that cementation factor can vary continuously throughout the borehole due to changes in subfacies, however, these changes are typically minimal (Ehrlich et al., 1991).

Resistivity increases above Ro are characterized according to Majumdar et al. (2017)

(Table 1) where “A” is the rank representing a significant hydrate accumulation with a notable increase in resistivity, which is defined as a 5 Ωm or more increase in resistivity above background for at least 10 m. Resistivity increases and thickness are lower for “B” and “C” wells (Table 1). The “D” rank represents the lowest increase in resistivity, 0.5 to

2 Ωm increase above background resistivity for less than 10 m. Finally, wells marked

“None” show no increase in resistivity above background. The ordinal rankings are numerically transformed for spatial analysis so that A=4, B=3, C=2, D=1 and None=0.

Table 1. Resistivity increase classification criteria adapted from Majumdar et al. (2017) with numerical transformation.

Classification Criteria Ordinal rank Numerical transformation 5 Ωm or more increase in resistivity above A 4 background for at least 10 m 2 Ωm to 5 Ωm increase in resistivity above background for at least 10 m, or more than 5 Ωm B 3 increase above background resistivity but less than 10 m 0.5 Ωm to 2 Ωm increase in resistivity above C 2 background for at least 10 m 0.5 Ωm to 2 Ωm increase above background D 1 resistivity for less than 10 m No resistivity increase None 0

Spatial Analysis

A geostatistical kriging model is deployed using ArcGIS Pro to interpolate hydrate occurrence estimates for both the Barents and Norwegian Seas. Kriging models use a semivariogram (the degree of spatial dependence) to interpolate spatial intensity of a given variable, in this case, resistivity increase rank (Burgess and Webster, 1980). The model uses an empirical transformation which is appropriate to secure a distribution closer to normal, and an exponential semivariogram which provides a faster rate of decay for spatial dependence. The interpolative radius is set at 60 km.

Results

Gas Hydrate Stability

Gas composition had a significant influence on the BGHSZ. Only 4 of 18 wells in the

Barents Sea were able to house stable hydrate under a pure methane gas composition scenario. In the deeper Norwegian Sea, 21 of 46 wells had a stable GHSZ under a pure methane scenario (Table 2). The introduction of a mixed gas system (whether from sample gas composition data or from an assumed likely composition) increased the thickness of the GHSZ anywhere from 20 to 260 m depending on the specific mix of gas

(Table 2) (Figure 3). (Other well specific physical conditions such as geothermal gradient and water depth also had an impact on BGHSZ). Therefore, wells that would otherwise be unsuitable for the accumulation of pure methane hydrate, were shown to have a GHSZ if higher order hydrocarbons were present in sample gas composition data or if modeled using an assumed likely mixed gas composition. In the Barents Sea, the mixed gas GHSZ thickness ranges from 160 to 450 m while in the Norwegian Sea the thickness ranges from 200 to 640 m. When available, gas sample composition data (Table 2) is used to model BGHSZ and inform gas hydrate identification in the industry well logs. However, if no gas sample composition data was available, the BGHSZ was modeled using the likely gas mix of 90% methane, 7% ethane, and 3% propane from Ostanin et al. (2013).

Table 2. Gas composition data from industry wells in the Barents and Norwegian Seas as well as their accompanying bottom of gas hydrate stability (BGHSZ) for either a pure methane gas composition or a mixed gas calculated using either gas sample data or a likely gas composition from Ostanin et al. (2013) (shaded). BGHSZ is measured in meters from the rig floor and therefore includes Kelly bushing.

Sea Well Methane Ethane Propane Pure Methane Gas Mix (%) (%) (%) BGHSZ BGHSZ Norwegian 6201(11-1) 90 7 3 Not Stable 614 Norwegian 6201(11-2) 90 7 3 Not Stable 586 Norwegian 6302(6-1) 89 0.17 0.2 1711 1841 Norwegian 6305(1-1) 90 7 3 1219.5 1379.5 Norwegian 6305(4-1) 90 7 3 1351 1482 Norwegian 6305(5-1) 95.03 3.74 0.48 1288.5 1308.5 Norwegian 6305(5-3 S) 90 7 3 942 1132 Norwegian 6403(10-1) 90 7 3 1987 2087 Norwegian 6403(6-1) 95.7 0.83 0.22 1981 2001 Norwegian 6404(11-1) 90 7 3 1905 2015 Norwegian 6405(10-1) 83.8 0 0 1248 1268 Norwegian 6405(7-1) 85.6 0.23 0 1536 1556 Norwegian 6406(1-2) 90 7 3 Not Stable 603 Norwegian 6406(2-3) 90 7 3 Not Stable 602 Norwegian 6504(5-1 S) 90 7 3 1560 1670 Norwegian 6505(10-1) 96 2.5 1.2 1064 1194 Norwegian 6506(11-6) 90 7 3 Not Stable 606 Norwegian 6506(11-7) 90 7 3 Not Stable 586 Norwegian 6506(6-1) 89.8 0.57 0.45 Not Stable 644 Norwegian 6506(9-1) 90 7 3 Not Stable 616 Norwegian 6507(3-3) 92.8 2.6 4 Not Stable 591 Norwegian 6507(6-1) 90 7 3 Not Stable 759 Norwegian 6507(6-3) 90 7 3 Not Stable 630 Norwegian 6507(7-1) 90 7 3 Not Stable 577 Norwegian 6507(7-10) 90 7 3 Not Stable 622 Norwegian 6507(7-6) 90 7 3 Not Stable 550 Norwegian 6508(5-1) 90 7 3 Not Stable 771 Norwegian 6603(12-1) 90 7 3 1666 1746 Norwegian 6605(1-1) 90 7 3 1487 1597 Norwegian 6605(8-1) 90 7 3 1158 1308

Norwegian 6605(8-2) 90 7 3 1138 1288 Norwegian 6607(2-1) 90 7 3 1280 1450 Norwegian 6607(5-1) 90 7 3 Not Stable 668 Norwegian 6607(5-2) 90 7 3 Not Stable 837 Norwegian 6608(10-1) 90 7 3 Not Stable 655 Norwegian 6608(10-3) 90 7 3 Not Stable 582 Norwegian 6608(10-4) 90 7 3 Not Stable 592 Norwegian 6608(10-6) 90 7 3 Not Stable 578 Norwegian 6608(10-7) 90 7 3 Not Stable 577 Norwegian 6608(10-8) 90 7 3 Not Stable 586 Norwegian 6608(10-9) 87 6.7 5.1 Not Stable 597 Norwegian 6610(2-1 S) 90 7 3 Not Stable 626 Norwegian 6704(12-1) 90 7 3 1672 1772 Norwegian 6706(11-1) 99.73 0 0 1678 1678 Norwegian 6706(12-1) 90 7 3 1762 1902 Norwegian 6706(6-1) 96.7 2.9 0.4 1728 1758 Barents 7120(2-1) 90 7 3 Not Stable 837 Barents 7122(6-1) 96.71 null null Not Stable 541.3 Barents 7122(6-2) 72.69 null null Not Stable 730.7 Barents 7122(7-1) 90 7 3 Not Stable 811 Barents 7122(7-2) 90 7 3 Not Stable 807 Barents 7122(7-4 S) 77.69 null null Not Stable 581 Barents 7122(7-5) 90 7 3 Not Stable 800 Barents 7123(4-1 A) 90 7 3 Not Stable 693 Barents 7128(4-1) 93.46 null null Not Stable 575.1 Barents 7219(8-1 S) 66.78 15.96 17.26 Not Stable 779 Barents 7219(9-1) 97.05 null null Not Stable 515.8 Barents 7222(11-1) 90 7 3 Not Stable 656 Barents 7222(6-1 S) 90 7 3 Not Stable 694 Barents 7228(2-1 S) 96.46 null null Not Stable 536.4 Barents 7321(7-1) 90 7 3 615 875 Barents 7321(8-1) 68.45 null null 568 788.5 Barents 7321(9-1) 69.63 null null 579 798.5 Barents 7324(10-1) 97.74 null null 488 585.3

Figure 3. a. Gas hydrate stability curves for Barents Sea Well 7120/2-1. Pure methane hydrate would be unstable, however given a gas mix of 90% methane, 7% ethane, and 3% propane, the well can house stable hydrate. b. Gas hydrate stability curves for Norwegian Sea well 6305/1-1. Pure methane and a gas mix of 90% methane, 7% ethane, and 3% propane both produce stable hydrate. 16

Gas Hydrate Identification

A total of 13 out of 18 wells in the Barents Sea and 36 out of 46 hydrate wells in the

Norwegian Sea showed evidence for gas hydrate within the GHSZ (based on stability curves modeled with either gas sample composition data (when available) or a likely mixed gas composition (Table 2). A total of 4 out of 18 wells in the Barents Sea and 17 out of 46 hydrate wells in the Norwegian Sea showed evidence for gas hydrate within the

GHSZ (based on stability cures modeled with a pure methane gas composition) The increase in resistivity was ranked according to Majumdar et al. (2017) (Table 3 and

Figure 4). Only four wells in the Barents and Norwegian Seas achieved an “A” or “B” rank. The majority of potential hydrate wells had lower resistivity increases between 0.5 and 2 Ωm.

Table 3. Number of wells in the Barents and Norwegian Seas that fall into each resistivity increase ranked classification.

Rank Barents Sea wells Norwegian Sea wells

A 0 1

B 3 0

C 6 21

D 4 14

None 5 10

Total 18 46

Figure 4. Map showing industry wells ranked based on resistivity increase classification. Well log examples included in this manuscript are circled and labeled.

Well 6706/11-1 in the Norwegian Sea (figure 5), was identified as the only “A” ranked well in dataset. From 1340 to 1420 meters below rig floor (mbrf), resistivity increases extend above background by 3 to 7 Ωm. Moreover, based on curve separation observed in this interval between micro, medium, and deep resistivities, gas hydrate is likely occurring within near vertical fractures (Cook et al., 2010). Deeper in the well, however, intervals showing resistivity increases above background are attributed to borehole washout rather than the presence of gas hydrate due to anomalously high values of porosity. Gas sample data shows a composition of nearly 100% methane in well 6706/11- 18

1. Without the presence of higher order hydrocarbons, the GHSZ is relatively thin compared to stability zones modeled with the Ostanin et al. (2013) gas mix in similar thermobaric environments.

In the Barents Sea, the resistivity increases above background had a higher variance with a comparable number of wells falling into each rank (except “A” which had no wells). In the Norwegian Sea, variance was lower with resistivity characterized by thicker intervals of small increases above background leading to twenty-one ‘C’ and fourteen “D” ranked wells.

Figure 6a is an example of a “B” ranked log from the Barents Sea illustrating a prolonged resistivity increase above a background calculated using the neutron porosity log and

Equation 1. The shaded areas denote potential hydrate accumulations. The largest increase above background occurs from 585 to 598 mbrf at the top of the figure and likely has the highest hydrate saturation in the hole. Decreases in porosity align with increases in background resistivity and are likely do not contain hydrate. Figure 7 contains three examples of ‘C’ ranked wells from the Norwegian Sea, all of which show increases in resistivity for over 10 m above an estimated background resistivity. Figure

6b is a ‘D’ ranked log from the Barents Sea, and shows small resistivity spikes between

700-740 mbrf above a visually estimated background resistivity.

Figure 5. Well 6706-11-1 in the Norwegian Sea with resistivity increases ranked A. The bottom of the gas hydrate stability zone (BGHSZ) is based on gas mix data from Table 2. Resistivity increase above background are shaded in red. Sections of washout are shaded in grey and not identified as gas hydrate.

Figure 6. a. Well 7321/8-1 in the Barents Sea with resistivity increases ranked B. b Well 7321/7-1 in the Barents Sea with resistivity increases ranked D. The bottom of the gas hydrate stability zone (BGHSZ) is based on gas mix data from Table 2. Resistivity increase above background are shaded in red.

Figure 7. a. Well 6305/5-3 in the Norwegian Sea with resistivity increases ranked C. b. Well 6506/6-1 in the Norwegian Sea with resistivity increases ranked C. c. Well 6608/10- 3 in the Norwegian Sea with resistivity increases ranked C. The bottom of the gas hydrate stability zone (BGHSZ) is based on gas mix data from Table 2. Resistivity increase above background are shaded in red.

Spatial Analysis

In the Barents Sea the surface interpolated using the resistivity increase classification by the kriging model shows that the most significant resistivity increases occur in the

Bjørnøya Trough, where thermobaric conditions allow for the thickest gas hydrate

22 stability zone (Figure 7b) and where most of the known BSRs are clustered (Bugge 1983;

Mienert et al. 1998; Mienert et al. 2003; Chand et al., 2011; Vadakkepuliyambatta et al.,

2017). In the Norwegian Sea, the resistivity increases clusters along the Storegga Slide head scarp where gas hydrate has been previously inferred from BSRs and fluid escape features (Figure 7a) (Hustoft et al., 2007). However, in both seas, the characterization of resistivity within the GHSZ can change quickly across space, as a “No Hydrate” is observed within 20 km of the “A” ranked well in the Norwegian Sea. An exponential semivariogram is appropriate in this case. The differences in variance can be inferred from the spread of data breaks outputted by the model with the Barents Sea model interpolated values between 0.6 and 2.73 and the Norwegian Sea model spread between

1.04 and 2.01 (Figure 7).

Figure 8. Interpolated model (60 km radius) illustrating resistivity increase strength within the GHSZ in the a. Norwegian Sea and b. Barents Sea as well as the geographic extent of know bottom simulating reflections (BSR)

Discussion

Gas Hydrate in the Barents and Norwegian Seas

When thinking about data sources for gas hydrate research, industry well log data is advantageous in that wells are typically drilled targeting hydrocarbons which could act as a potential gas sources for hydrates. In fact, in the industry dataset, it was common that hydrocarbon shows were observed in formations below the GHSZ. Moreover, the dataset has the added benefit of being available to the public. Public industry well logs, therefore, provide a cost-efficient opportunity to analyze hydrate accumulations. Particularly in the

Norwegian high-latitude regions of the Barents and Norwegian Seas in which petrophysical measurements are not as widely used for hydrate research as they are in other locations like the Gulf of Mexico (Majumdar et al., 2017, Collett et al., 2012, Cook et al., 2008 Boswell et al., 2009). As a regionally underutilized data source for gas hydrate analysis, industry well logs provide a different perspective that ultimately supports previous studies such as Bugge et al. (1983), Mienert et al. (1998), and Mienert et al. (2003).

In both seas, the majority of well logs had resistivity increases above background indicative of gas hydrate accumulations. This contrasts with results from Majumdar et al.

2017 which found only 116 of 788 wells in the Gulf of Mexico had resistivity increases above background. But with most Barents and Norwegian Sea increases within 0.5 and 2

Ωm (“C” and “D” ranks), potential hydrate wells appear to be lower saturation. However, given the percentage of “low saturation” wells constituted a majority in each sea, the 25 cumulative effect may have significant impacts on hydrate volume estimates. Scientific study of gas hydrate typically focuses on the large and high saturation reservoirs.

Therefore, diffuse low concentration hydrate is underrepresented in datasets and potentially in global hydrate volume estimates. Such estimates are important in determining the gas hydrate contribution to global carbon cycling.

Moreover, spatial analyses indicate that although there are environments more suitable to hydrate occurrence like in the Bjørnøya Trough in the Barents Sea and the Storegga Slide in the Norwegian Sea, the potential to accumulate hydrate exists across large swaths of each margin and hydrate is observed across each sea over wide areas. These spatial analyses may be further tied to seismic data or numerical models.

A larger spread of resistivity increase ranks is observed in the Barents Sea. While in the

Norwegian Sea, ranks are mainly either C or D. The difference in variance between the

Barents and Norwegian Seas may be explained by the difference in regional geology. The

Barents Sea, with its unique glacial history and thin sediment section, represents a more spatially dynamic geologic setting than that of the Norwegian Sea which has a more defined continental slope with gradually increasing depths greater than a kilometer and a thicker sediment section. The GHSZ of the Barents Sea is mostly present in the Jurassic aged lithified siltstones and sandstones of the Adventdalen Group or in glacial sediments with grain sizes that include cobble and boulder (NPD FactPages, 2016), while the GHSZ of the Norwegian Sea is mostly present in the Miocene to recent marine sediments of the

Norland Group ranging from clay to silt to sand (NPD FactPages, 2016). Since marine sediments generally have higher porosity than that of lithified rocks, and a more

26 consistent porosity than that of glacial sediments, the Norwegian Sea appears to have more favorable and consistent conditions for gas hydrate accumulation.

Confidence

Increases in resistivity are not only caused by the presence of gas hydrate. For brine saturated sediment or rock, sediment compaction and/or cementation will lead to lower porosity and higher resistivity. Porosity measurements were not always available in the zone of interest, making the impact of compaction and/or cementation difficult to determine. When either bulk density or neutron porosity data was available within the

GHSZ (a total of ten wells), porosity and background resistivity were calculated. With these additional measurements, confidence in resistivity increases denoting a gas hydrate accumulation was improved. Without bulk density or neutron porosity, background resistivity was estimated visually. This method could only accommodate similar changes in background and therefore any changes in resistivity due to changes in porosity were impossible to resolve. The only exception to this rule is geologic formations specifically interpreted on the well logs. For example, the Kviting Formation, a calcareous sandstone with interbedded mudstones (NPD FactPages, 2016), is characterized by an approximately 30 m increase in resistivity (likely due to cementation) visible across four logs in the Barents Sea (7222/6-1,7222/6-2,7222/7-1,7222/7-2); this formation and resistivity signature was not included as a gas hydrate signal.

Resistivity increases could also be due to the presence of free gas not bound in hydrate clathrates. However, for wells included in the analysis, well reports indicate that no shallow gas was observed during drilling (NPD FactPages, 2016).

Moreover, the well ranks are not proxies for gas hydrate saturation, but rather denote evidence for the presence of gas hydrate based on the relative strength of resistivity increases above background within the GHSZ. In fact, saturation calculations using

Archie’s equation are only valid for clean sand intervals (Archie, 1942). Since the study areas have typical lithologies of either marine mud or silt sediments in the case of the

Norwegian Sea and Jurassic age lithified shales and siltstones in the Barents Sea (NPD

FactPages, 2016), any saturation calculations would not be particularly insightful.

The industry data set is limited is both its distribution and density. The wells were drilled targeting hydrocarbons, and therefore, gaps in data coverage persist across both the

Norwegian and Barents Sea, due to clustering of wells within potential petroleum plays

(for example, the Tornerose discovery in the Barents Sea contains 3 wells in the dataset and the Ormen Lange discovery in the Norwegian Sea also contains 3 wells in the dataset

(NPD FactPages, 2016)), interpolation between distant data points is difficult. Therefore, the interpolation radius is limited to 60 km. This is particularly true in the eastern part of the Barents Sea where two wells, geographically separate from the main distribution and from each other, are making interpolation calculations based only on their individual values. This leaves a gap in the interpolated surface and causes the signal to be relatively meaningless at any distance from the wells in question. Moreover, the density of wells is more of an issue in the Barents Sea with only 18 data points to the Norwegian Sea’s 46.

The relative sparsity contributes to a decrease in confidence regarding the Barents Sea’s interpolative resistivity increase calculations. The Norwegian Sea calculations, however, with 2.5 times the wells and few spatial gaps in data, are more robust. The geostatistical interpolative model correlates with known BSR locations (Bünz et al., 2003; Mienert et

28 al., 2005; Chand et al., 2011; Vadakkepuliyambatta et al., 2017) particularly in the

Norwegian Sea along the head scarp of the Storegga Slide, where hydrate has been found

(Figure 7).

This method can be easily repeated in additional study areas that have available public well log data in order to characterize low saturation hydrate systems globally in a cost- effective manner.

Conclusions

Publicly available industry well logs are a rich source of natural gas hydrate information.

Although traditionally underutilized in European offshore areas like the Barents and

Norwegian Seas, a majority of wells showed evidence of low saturation hydrate accumulation within an independently determined GHSZ modeled at each well site.

Based on spatial modeling of the resistivity increase’s strength, the areas most favorable to hydrate accumulation are the head scarp of the Storegga Slide (Norwegian Sea) and the

Bjørnøya Trough (Barents Sea). This approach is a viable option for exploring low saturation hydrate systems worldwide.

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