ERA & OSCA ODA PRODUCING WELLS SUMMARY

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Memo to:

Morten Løkken, Spirit Energy

Memo No: 11B9P8I4-4/ HABT_rev01 From: Harald Bjarne Tvedt

Date: 2018-10-23

Prep. By:

QA:

Harald Bjarne Tvedt & Helene Østbøll

Odd Willy Brude

ERA & OSCA ODA PRODUCING WELLS SUMMARY

The guideline for oil spill response (NOROG, 2013) emphasizes that tactical response shall reflect the potential for environmental risk, linked to an operation, in this case producing oil wells. For the planned operations, given the rates and durations applied, the environmental risk is negligible for the VECs studied (pelagic and coastal seabirds, marine mammals and shoreline habitats) as part of Spirit Energy’s installation acceptance criteria.

For the oil drift rate/duration matrix, the concentration of total hydrocarbon components exceeds 50 ppb in a smaller area in the immediate vicinity of the modelled release location and does not affect the regional sand eel habitats.

Single simulations show that a potential overlap with sand eel habitats is influenced by the weather conditions. The highest modelled concentration of sedimented THC registered in the "overlap area" is in the 3-10 g/m² category. A single simulation represents a defined period and the output from the modelling work should be assessed carefully.

Mechanical oil recovery is more efficient during the summer period compared to winter, which is due to the weather conditions and thereby the availability of Surface oil. Another tendency is reduced recovery efficiency for response systems employed later. This is due to less oil being available for recovery.

1 INTRODUCTION

The work is primarily carried out by applying tools developed for the Butch/Oda oil field in 2015/2016 (DNV GL, 2015a, 2016). Environmental risk (ERA) is calculated using Operational Environmental Risk (OPERAto) which has been updated as part of the study.

Since previous version of OPERAto was established, the oil drift model OSCAR has been updated, and version 8.0.1 is therefore used for the modelling instead of version 6.2.

Updated resource data (coastal seabirds, SEAPOP 2017) and Best Practise for OSCAR modelling (NOROG, 2016) are applied.

The Best Practise procedure includes standardized parameters:

 Current and wind data (2002-2011)

 Current: daily mean data, 4 x 4 km resolution, SWIM archive (NMI)

 Wind: 3-hour-interval, 10 x 10 km resolution, NORA10 (NMI/ Norsk Dypvannsprogram)

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The amount of oil was distributed over an increased number of particles, compared to in the past, from 2 500 to 3 000 – 10 000 (depending on rate).

Oil Spill Contingency (OSCA) evaluations are based on OSCAto, developed for the Oda oil field in 2015/2016 (DNV GL, 2016). The tool was developed using a variety of response configurations for various rates.

Key input differences between an environmental risk and oil spill contingency analysis are the presence of incident frequency in risk calculation as well as a rate-/duration matrix approach in ERA while OSCA plans for an incident to happen and is carried out applying 1 rate and 1 duration. The output could be low environmental risk with a high oil spill response requirement. An evaluation at end of study, to ensure that the oil spill contingency level reflects the environmental risk is therefore vital. The alignment of these two parameters are addressed in the Oil Spill Contingency guideline (NOROG, 2013).

2 METHODOLOGY

As described above, the output in the study is from the Oda field specific tools (OPERAto and OSCAto) developed by DNV GL in 2015/2016. The maps (figures) are prepared using ArcGIS version 10.3.1.

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3 INPUT DATA

Blowout rate

The blowout rates applied in the study are gathered from the Oda field blowout study (Add Energy, 2015) combined with output from the 2017 blowout study for Oda development wells (Acona) (Table 3-1).

The reasoning behind the approach is as follow:

Most of full opening scenarios is defined as outside casing (Lloyd’s 2018), a scenario not included in standard blowout scenario modelling. The restricted annulus scenario is applied as representative for this scenario (Acona, 2017). The rate from a topside drilling blowout study is considered conservative for a subsea release; however, used in current study with Lloyd’s 2018 distribution scheme, the rate

represents the 90-percentile level and thereby valid for the oil spill contingency analysis.

Table 3-1 Rates (m³/d) and related probability for blowout scenarios applied in environmental risk and oil spill response calculations for Oda producing field.

Flow path Rate (m³/d)

Probability (fraction)^a)

Accumulated probability (%)

Env. Risk Oil spill response

Inside prod. tubing (restricted) (Add Energy, 2015)

5 900 0.502 50 50

Annulus (Acona, 2017)

6527

0.082 58

42 Outer annulus

(Acona, 2017) 0.082 66

Outside casing (same as annulus)

(Acona, 2017)

0.252 92 X

Inside prod. tubing (open) (Add Energy, 2015)

9 100 0.082 100 8

a) Lloyd’s uses 2 digits after 0. To summarize to 1, the last 0. 01 has been divided equally among spill scenarios.

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Leakage rates

As Oda is based on subsea templates with tie-back to Ula, the current study has calculated potential environmental risk contribution linked to the pipeline transportation system. As an integrated part of the study, OLGA modelling was applied to define leakage scenarios/volumes (Appendix A). Generated output is presented in Table 3-2. Full bore scenarios are included in the environmental risk analysis.

Table 3-2 Various leak scenarios at Oda subsea template. Accumulated amounts are in Sm³, duration in hours (hrs) (Appendix A).

Scenario

Accumulated leak oil volume flow (Sm³)

Oda subsea template Oselvar SSIV

Small

15-minute detection time¹⁾

38

(at t=5 hrs after start of the leak)

347

Small 1-hour detection

time¹⁾

65

360

Medium

15-minute detection time

227

261

Medium 1-hour detection

time

388

(at t=3.75 hrs after start of the leak)

437

Full bore 15-minute detection

time

259

279

Full bore 15-minute detection

time

433

456

1) For the small leak at the Oselvar SSIV accumulated leak oil volume is considerably larger than at the Oda subsea template. The Oda pipeline is lying on a downward gradient, with the highest point being the Oda template (65-meter water depth) and the lowest point the Oselvar SSIV (70-meter water depth). During the small leak at the Oselvar SSIV, the slow depressurization of the pipeline and the oil accumulating in the bottom means that oil is pushed out by the gas, as opposed to the small leak at the Oda template, where it is mainly the gas lying on top of the oil which is released during depressurization.

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Duration

Assessed time to drill a relief well is 62 days (Add Energy, 2015). Based on the longest duration, DNV GL distributed the oil spill duration into 5 segments (Table 3-3). Distribution is gathered from Lloyd’s (2018).

The whole matrix is applied in OPERAto. The weighted duration (11 days) is applied for the oil spill contingency analysis (NOROG, 2013).

Table 3-3 Blowout duration distribution for a subsea blowout during the producing phase at Oda oil field (PL 405) (Add Energy, 2015, Lloyd’s, 2018).

Release location Duration (days)

2 5 15 35 62

Subsea 50.6 % 18.7 % 17.6 % 6.1 % 7.0 %

The durations for leakage scenarios are presented in Table 3-2.

Topside/subsea probability distribution

The oil producing operation is based on a subsea template, therefore the probability for a seabed blowout is 100 %.

Activity overview

An overview of activities and frequencies for potential blowouts in the first year of operation, at the Oda field, are presented in Table 3-4. The frequencies are generic, based on SINTEF’s Offshore Blowout database (Lloyd’s 2018). Oil field specific barriers are described in Spirit Energy’s “Oda Barrier Management strategy” document (Spirit Energy, 2017), however, as no Well Risk Assessment was carried out prior to calculations the generic values were applied. The probability for a leak along the 14- km transportation pipeline, from Oda subsea template to Ula platform is presented in Table 3-5. In addition, a frequency for a spill at the Oselvar SSIV is included. The frequency is based on the field specific concept risk analysis study (FMC Technologies, 2016), where all valve failures were provided with same frequency.

Table 3-4 Activities and frequencies for a potential oil blowout during the producing phase at Oda oil field (Lloyd’s, 2018).

Activity Number of activities (producing year)

Frequency (per well year)

Total

Producing wells (normal oil well)

2 2.4 x 10^-5 4.8 x 10^-5

Water injection well

1 9.9 x 10^-6 9.9 x 10^-6

Total 5.8 x 10^-5

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Table 3-5 Frequency for oil spill during production at Oda oil field (FMC Technologies, 2016).

Activity Length (km) Frequency

(per km/year)

Total (year)

Pipeline leakage 14 5.0 x 10^-4 7.0 x 10^-3

Valve (used to represent SSIV)

2.1 x 10^-4

Acceptance criteria

Spirit Energy has defined acceptance criteria for environmental risk as part of their management system.

For the scheduled operations, Spirit Energy’s installation specific acceptance criteria for environmental risk are used (Table 3-6). The acceptance criteria state the limit for what Spirit Energy has defined as acceptable risk for the company’s activities (probability for a given consequence). These criteria are formulated as a measure of environmental damage to natural resources, expressed by duration and degree of seriousness.

Spirit Energy uses the same acceptance criteria in all regions across the Norwegian Continental Shelf.

Environmental risk analysis captures differences in environmental vulnerability on a regional level based on the presence and vulnerability of environmental resources in each area and through calculation of restitution time for potentially affected resources. This means that the calculated environmental risk is higher for areas where a larger share of a vulnerable population or habitat is affected.

The acceptance criteria express Spirit Energy’s attitude to keep nature as far as possible untouched by the company’s activities. The criteria state maximum tolerated incident frequency which can cause harm to the environment.

Table 3-6 The installation specific acceptance criteria for acute pollution according to Spirit Energy (CEUNOR-HSEQ-PRO-0012 Risk Management).

Severity of environmental

damage

Duration of damage (Recovery/ restitution

time)

Production specific acceptance criteria per

installation (per year of operation)

Minor <1 year <1.0 × 10^-2

Moderate 1-3 years <2.5 × 10^-3

Considerable 3-10 years <1.0 × 10^-3

Serious >10 years <2.5 × 10^-4

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Oil type

Ula crude oil is the reference oil applied in OPERAto and OSCAto for Oda field.

Valuable Ecological Component (VEC)

The resource data in OPERAto are updated for this study. The data covers the North Sea with the most recent coastal seabird data (SEAPOP, 2017). For pelagic seabird, marine mammals and shoreline, the data sources are the same as in the original study (DNV GL, 2015b).

The response system configurations prepared for the original OSCAto modelling is presented in Table 3-7.

As OSCAto is applied for current study, the information is assessed as valid.

Table 3-7 Overview of NOFO systems and response times used in the modelling phase of OSCAto (DNV GL, 2016).

* Spirit Energy agreement with operator of oil spill resources - response time (3h).

** Oil Spill Response systems number 19 and 20 is taken in to get efficiency data. This oil spill resources might be hired from OSRL resource pool or other suppliers.

NO. Location OR-vessel

Distance (km)

Response time (h)

Location towing

vessel

Distance (km)

Response time (h)

Total response

time (h)

1* Ula 5 3 Stril

Mariner* - 3 3

2 Ekofisk 78 10 RS

Haugesund 291 10 10

3 Sleipner/ Volve 170 11 RS

Kleppestø 390 13 13

4 Balder 249 17 RS Måløy 557 18 18

5 Troll 2 405 18 NOFO pool - 24 24

6 Troll 1 426 19 NOFO pool - 24 24

7 Tampen 471 21 NOFO pool - 24 24

8 Stavanger 1 263 22 NOFO pool - 24 24

9 Gjøa 483 24 NOFO pool - 24 24

10 Mongstad 1 433 28 NOFO pool - 24 28

11 Haltenbanken 932 38 NOFO pool - 24 38

12 Kristiansund 1 724 39 NOFO pool - 24 39

13 Stavanger 2 263 42 NOFO pool - 24 42

14 Mongstad 2 433 48 NOFO pool - 24 48

15 Kristiansund 2 724 59 NOFO pool - 24 59

16 Sandnessjøen 1 122 65 NOFO pool - 24 65

17 Hammerfest 1 1 806 81 NOFO pool - 24 81

18 Hammerfest 2 1 806 101 NOFO pool - 24 101

19** International - 101 NOFO pool - 24 120

20** International - 101 NOFO pool - 24 120

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OSCAto is developed by applying various mechanical recovery configurations, for a set of predefined rates, using Ula oil and 1 oil spill duration (15 days). The setup is presented in Table 3-8.

Table 3-8 Mechanical recovery configurations used in OSCAto for Oda (DNV GL, 2016). A system is NOFO OR vessel and tug vessel. Barrier 1 and 2 are the offshore barriers in a contingency strategy.

Response configuration

Number of vessels in

barrier 1

Number of vessels in

barrier 2

Comments

0_0 0 0 Modelling of spill without contingency, to compare

with contingency modelling cases.

3_0 3 0 Normal mechanical setup with 3 systems in

barrier 1 and 0 systems in barrier 2.

Single simulations

To study the potential for sedimentation single simulations have been carried out for reference scenario (no response measures). Following start dates were used for the examples:

 Summer: April 15^th, 2016

 Winter: January 15^th, 2016

The scenarios are set-up with weighted spill duration (11days) and rate of 6 527 Sm³/d. The results are presented for end of simulation (day 31).

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4 RESULTS

The results are presented as follow: 1) oil drift, 2) environmental risk assessment and 3) oil spill contingency analysis.

Oil drift

Influence area, Total Hydrocarbon Concentration (THC) in water column and probability for stranding for a subsea oil release are presented seasonally in Figure 4-1 to Figure 4-3.

The results indicate that an influence area is potentially larger during the summer months (June-August) compared to the rest of the year. The reason for this is the weather conditions, providing less energy, and thereby limit weathering processes taking place on the water surface. The influence area, given a blowout at the Oda field, varies to some extent on a seasonal level. The most pronounced difference is the drift pattern along the shoreline, with summer having the potential for affecting most coastal grid cells (Figure 4-1). The probability for oil hitting shore is, independent of season, within the lowest oil hit probability category (5-10 %).

For THC, the maximum level was in the category 50-100 ppb, calculated near the release site. The potentially area, exceeding 50 ppb (58 ppb is set as threshold level for fish), does not overlap with the regional habitat areas for sand eel, independent of season (Figure 4-2).

The probability for stranding is limited and except for one grid cell in summer within the lowest hit probability category (5-10 %). A seasonal comparison indicates that summer is the season with

potentially a larger area of the shoreline being affected (Figure 4-3). This is due to variations in seasonal weather pattern.

Stranding

The output using the rate and duration matrix shows seasonal variance, with summer season being the period with potentially the largest amount of oil emulsion to shore. The 95-percentile data is presented seasonally in Table 4-1. Given an 80 % fraction of water in Ula oil emulsion (SINTEF, 1999), the oil part during summer season amounts to 316 tonnes.

The shortest drift time at 95-percentile level is 19 days at the shortest (autumn).

The results for 95-percentile stranded oil emulsion and drift time to shore are independent (i.e. not necessarily from the same simulation).

Table 4-1 Seasonal stranding of oil emulsion (ton) and shortest drift time to shore (days) at 95- percentil given a subsea blowout at Oda oil field. All simulations are included in the calculations.

Percentile

Stranded oil emulsion (ton) Drift time (days)

Spring Summer Autumn Winter Spring Summer Autumn Winter

95

104 1582 345 185 30 22 19 20

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Figure 4-1 Seasonal probability for ≥5 % hits of >1-ton oil in 10×10 km grid cells given a subsea blowout from a producing well at Oda oil field. The hit probability is based on all rates and durations and their individual probability.

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Figure 4-2 Seasonal THC concentrations in the water column (10 x 10 km grid cells) given a seabed blowout from a producing well at Oda oil field. The output is based on all rates and durations and their individual probability and with ≥5 % hits within a single grid cell. The outlined areas are habitats for sand eel.

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Figure 4-3 Seasonal probability for stranding (≥5 % hits of >1-ton oil) in 10×10 km shoreline grid cells given a subsea blowout from a producing well at Oda oil field. The hit probability is based on all rates and durations and their individual probability.

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Environmental Risk

The output from environmental risk calculations, for a subsea blowout scenario during producing phase at Oda oil field, is presented in Table 4-2. The results show negligible risk, as part of Spirit Energy’s acceptance criteria. The seasonal maximum damage frequency, total for all consequence categories, is for pelagic seabirds during winter. The maximum frequency is in the order of 10^-6 (Figure 4-4).

Table 4-2 Annual risk contribution from subsea blowout during producing phase, as part of Spirit Energy’s installation specific acceptance criteria. The consequence categories refer to recovery time for a population/ habitat. Output is generated in OPERAto.

Resource group Minor

<1 year Moderate

1-3 years Considerable

3-10 years Serious

>10 years

Pelagic seabirds 0.1 % 0.2 % 0.0 % 0.0 %

Coastal seabirds (+

marine mammals)

0.0 % 0.1 % 0.1 % 0.1 %

Coastal habitats 0.0 % 0.0 % 0.0 % 0.0 %

Figure 4-4 Seasonal environmental damage frequency for a subsea oil spill at Oda during producing phase for pelagic seabirds (left), coastal seabirds and marine mammals combined (centre) and coastal habitat (right). The consequence categories are Minor (<1 year), Moderate (1-3 years), Considerable (3- 10 years) and Serious (>10 years). Output generated in OPERAto.

Potential risk contribution from the water injection well, as part of Spirit Energy’s acceptance criteria, is negligible (<0.1 %), independent of environmental resource and consequence category.

Based on the potential spill volumes and durations modelled for leaks along the transport pipeline (tie- back) to Ula platform (Appendix A), the output shows no environmental risk contributions for any of the scenarios.

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Oil Spill Contingency

The output in this section is generated using the OSCAto tool developed for the Oda (Butch) field in 2015/2016.

The mass balance at end of simulation, given a subsea oil release, indicates more Recovered oil during summer compared to winter season (Figure 4-5) and (Table 4-3 - Table 4-4). This is primarily due to seasonal variations in weather pattern, which affects the availability of recoverable Surface oil. The OSCAto calculations indicate a gradual reduction in effectiveness for the oil spill response configurations implemented later in the response scheme. This is due to a reduced amount of oil being available for mechanical recovery for additional recovery systems. The Out of grid (Sedimented) oil fraction is higher during winter season compared to summer, while Dispersed and Evaporated oil is more pronounced during the summer period. The trend is observed independent of response configuration.

The fraction of Stranded oil, independent of period and oil spill response level, is zero at end of

simulation. This is supported by the stranding output in OSCAto, which at 95-percentile level show that for the given 90-percentile rate used in the study (6527 m³/d), there was no stranding at end of

simulation. This is valid for both summer and winter and independent of response level. It is emphasized that the results are output from the single rate and duration combination applied in the oil spill

contingency analysis, and not from the matrix applied in the oil drift and ERA part of the study.

A substantial drop in Surface oil fraction is observed in the period following the release (Figure 4-6).The reduction is more significant during summer season due to a higher Surface oil fraction during the spill period, compared to winter season.

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Figure 4-5 Mass balance given various mechanical recovery configurations for a subsea oil release at Oda, summer (top) and winter (bottom). The results are combined for open water barriers (1+2) where 0_0 denotes reference scenario without oil spill response. Output generated in OSCAto.

0 % 10 % 20 % 30 % 40 % 50 % 60 % 70 % 80 % 90 % 100 %

0_0 3_0 4_2 6_3 8_4 10_5 12_6 14_6

Configuration setup

Mass balance, including mechanical recovery, at the end of simulation for selected discharge rate and recovery alternatives

Out of grid Evaporated Stranded Surface Dispersed Dissolved Degraded Recovered

0 % 10 % 20 % 30 % 40 % 50 % 60 % 70 % 80 % 90 % 100 %

0_0 3_0 4_2 6_3 8_4 10_5 12_6 14_6

Configuration setup

Mass balance, including mechanical recovery, at the end of simulation for selected discharge rate and recovery alternatives

Out of grid Evaporated Stranded Surface Dispersed Dissolved Degraded Recovered

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Table 4-3 Mechanical recovery for various oil spill contingency configurations during summer season.

Output generated in OSCAto.

Mechanical recovery [% of

released oil]

Recovery per configuration

Configuration [% recovery] [t/d]

0_0 0.0 0.0 -

3_0 7.3 7.3 404

4_2 11.3 4.0 248

6_3 15.2 3.9 235

8_4 18.4 3.2 208

10_5 20.7 2.3 154

12_6 22.8 2.1 126

14_6 23.2 0.5 53

Table 4-4 Mechanical recovery for various oil spill contingency configurations during winter season.

Output generated in OSCAto.

Mechanical recovery [% of

released oil]

Recovery per configuration

Configuration [% recovery] [t/d]

0_0 0.0 0.0 -

3_0 3.1 3.1 169

4_2 5.2 2.0 111

6_3 7.3 2.1 114

8_4 8.9 1.7 91

10_5 10.6 1.6 88

12_6 11.9 1.3 73

14_6 12.4 0.5 25

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Figure 4-6 Mass balance over time for a subsea release without implementation of oil spill contingency measures for summer (top) and winter (bottom). Note that the x-axis is non-linear, with 11 days being the release end and 31 days the end of simulation.

4.4.1 Dispersant application

Chemical dispersion has in a previous study showed limited effect as oil spill response strategy for Ula crude oil scenarios (DNV GL, 2015b). The results are likely due to a relative short “dispersion window”

(green) (Table 4-5) (SINTEF, 1997). Given a subsea release location, the effect is likely even less.

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Table 4-5 Time-window for use of chemical dispersants on Ula crude oil emulsion during winter (5 °C) and summer season (15 °C) given different wind conditions. Green colour indicates dispersible, yellow indicates reduced dispersibility and red indicates poorly dispersibility.

Season

Time window for use of chemical dispersion

Hours 1 2 3 6 9 12 24 48 72 96 120

Days 0.04 0.08 0.13 0.25 0.38 0.50 1.00 2.00 3.00 4.00 5.00

Winter (5 °C)

Wind 2 m/s 5 m/s 10 m/s 15 m/s

Summer (15 °C)

Wind 2 m/s 5 m/s 10 m/s 15 m/s

4.4.2 Sedimentation

The results representing winter and summer season are presented in Figure 4-7 and Figure 4-8. The 1^st figure presents sediment/deposition (g/m²) in combination with mass balance and wind speed and direction at end of simulation, while the 2^nd figure displays areas with sediment concentration (>0.9 g/m²) and regional sand eel habitats. The concentration is accumulated at end of simulation.

The single simulations show variations with regards to potentially affected area as well as concentration level; with a more widespread distribution and higher sediment concentration near release location for the winter (January) scenario compared to the summer (April) scenario (Figure 4-7). The potential overlap with sand eel habitats is influenced by the weather conditions, e.g. southwest in the April scenario vs. more west in the January setup. The modelled output indicates that in the areas with a potential for overlap, the highest concentration of sedimented THC is registered in the 3-10 g/m²

category. It should be emphasized that a single simulation provides information for a defined period and the output from the modelling work should be viewed carefully.

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Figure 4-7 Sedimentation at end of single simulation for scenario without response measures implemented (0_0) during winter (top) and summer (bottom). The figure show sediment deposition (g/m²), mass balance, wind speed (m/s) and wind direction at end of simulation (day 31).

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Figure 4-8 Sedimentation at end of single simulation for scenario without response measures implemented (0_0) during winter (top) and summer (bottom). The figure show sediment deposition (g/m²), mass balance, wind speed (m/s) and wind direction at end of simulation (day 31).

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4.4.3 Environmental risk and oil spill preparedness

A subsea blowout during producing phase at the Oda oil field is assessed to have a negligible

environmental risk, maximum 0.2 % (in category Moderate, 1-3 years’ restitution time) as part of Spirit Energy’s acceptance criteria for installation (Section 3.6). This calculation is carried out without

implementation of oil spill contingency systems. Based on the limited output for the reference scenario, it is unlikely that implementation of oil spill response systems will further reduce the risk level for the VECs applied in a standard environmental risk analysis.

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5 DISCUSSION

The guideline for oil spill response (NOROG, 2013) emphasizes that tactical response shall reflect the environmental risk level, linked to an operation, in this case producing oil wells. For the planned operations, given the rates and durations applied, the environmental risk is negligible for the VECs studied (pelagic and coastal seabirds, marine mammals and shoreline habitats). Based on the

assumptions used in oil spill response planning for calculating 95-percentil strand mass and shortest drift time to shore, the output was zero prior to implementation of response systems. In standard oil drift, using a rate/duration matrix, shortest drift time to shore at 95-percentil was minimum 19 days.

For the oil drift rate/duration matrix, the concentration of total hydrocarbon components exceeds 50 ppb in a very small area in the immediate vicinity of the modelled release location and does not affect the regional sand eel habitats.

Single simulations show that a potential overlap with sand eel habitats is influenced by the weather conditions. The highest concentration of sedimented THC registered in the "overlap area" is in 3-10 g/m² category. A single simulation represents a defined period and the output from the modelling work should be assessed carefully.

Mechanical oil recovery is more efficient during the summer period compared to winter, which is due to the weather conditions and thereby the availability of recoverable Surface oil. Another tendency is reduced recovery efficiency for each additional response systems. This is due to less oil being available for recovery.

The location makes it easy for NOFO-OR systems to access the field in case of an oil spill. This is illustrated in Table 4-7, with numerous systems available within 24 hours.

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6 REFERENCES

Acona, 2017. Blowout rate evaluations for the 8-1/2” pilot from 13-3/8” casing – transient reservoir response evaluations. Oda development wells (PL405). Rev 0 – 28^th September 2017.

Add Energy, 2015. Blowout Simulations Butch Production Well. Rev 1, December 9, 2015.

DNV GL, 2016. OSCAto (Oil Spill Contingency Analysis tool). DNVGL_OSCAto_Butch_rev00_v2-02. DNV GL no. 1QQQJTK-10, rev01. Date 2016-01-06.

DNV GL, 2015a. OPERAto (Operational Environmental Analysis tool).

DNVGL_OPERAto_Butch_rev00_Final.xlsm. DNV GL no. 1QQQJTK-9, rev00. Date 2015-08-21. Revised 01, date 14.09.2018.

DNV GL, 2015b. Environmental risk and oil spill contingency analyses for development drilling at Butch field (PL 405), Report number: 2015-0772, Rev, 00.

FMC Technologies, 2016. Report, feed study, subsea production system, concept risk analysis, Centrica Butch feed. Doc. No: RPT60132683, rev A, p. 28.

Lloyd’s, 2018. Blowout and well release frequencies based on SINTEF offshore blowout database 2017, Report no: 19101001-8/2018/R3, Rev: Final, Date 20 April 2018.

NOROG, 2016. Oljedriftsmodellering for standard miljørisikoanalyser ved bruk av OSCAR – beste praksis. Utarbeidet av Acona, Akvaplan-Niva & DNV GL, Power Point Presentation 14.03.2016.

NOROG, 2013. Veiledning for miljørettede beredskapsanalyser, datert 16.08.2013.

Spirit Energy, 2017. Oda Barrier Management Strategy. NOR0004, Oda, rev C, 21.12.2017.

Seapop, 2017. Rådata innhentet for konsentrasjoner av kystnære sjøfuglarter fra Norsk Institutt for Naturforskning ved Geir Systad. Nasjonale og regionale datasett.

SINTEF, 1999. Oppdatert forvitringsstudie for Ula råolje relatert til effektivitet av Foxtail Skimmer, SINTEF Kjemi, Rapportnr, STF66 F99076.

SINTEF, 1997. Forvitringsegenskaper til Ula Råolje. SINTEF Kjemi. Rapportnr. STF66 F98001. 1997-12- 30.

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Appendix A

Leak simulations Oda

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Memo to: Memo No: 11B9P8I4-6/ HABT_REV02

Morten Løkken, Spirit Energy From: Harald Bjarne Tvedt

Date: 2018-09-27

Copied to:

Gard Tore Pedersen, Spirit Energy

Prep. by:

QA by:

Jan Fredrik Helgaker Charles Renaud-Bezot

LEAK SIMULATIONS ODA 1 INTRODUCTION

This document summarizes the results of a leak study on the Oda Production Flowline. Production fluids are transported from the Oda subsea template to the Ula platform through a 14 km 10" production pipeline. The multiphase flow software tool OLGA was used to model the different leak scenarios.

2 INPUT DATA

2.1 10" Production Pipeline

An overview of the Oda field is shown in Figure 1-1. The Oda subsea template is located at a water depth of approximately 65 meters. The 10" production flowline will be tied into the existing Oselvar SSIV (water depth 70 m), enabling the Oda production to be routed through the existing Oselvar spools and production riser to Ula inlet facilities. Seabed difference from Oda template (water depth 65 m) to Oselvar SSIV water depth 70 m) is assumed to be linear. Production pipeline dimensions are given in Table 2-1 and external coating data in Table 2-2. The total heat transfer coefficient of U = 5 W/m²K is set for the pipeline. Ambient seabed temperature is 5 °C.

The internal volume of the Oda production pipeline from Oda template to SSIV is approximately 640 m³.

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Page 2 of 11

Table 2-1 Production pipeline dimensions /2/.

Description Material OD (mm) Selected WT (mm)

Zone 2 Zone 1

10" Production pipeline Carbon Steel 273.1 17.5 15.9

Table 2-2 External coating data /2/.

Descriptions Unit 10" PR

Coating Description - 3LPP

Pipe Steel OD mm 273.1

First layer, FBE Thickness mm 0.3

Density kg/m³ 1300

Second layer, Cohesive PP

Thickness mm 0.3

Density kg/m³ 900

Third layer, PP Thickness mm 27

Density kg/m³ 900

Total Thickness mm 27.6

Density kg/m³ 904.3

2.2 Production data

Production data for 2019, used in study, is presented in Table 2-3.

Table 2-3 Production data Oda pipeline /4/.

Parameter Value

Maximum oil rate 5564 Sm³/sd

Maximum gas rate 465 kSm³/sd

Maximum produced water rate 4000 Sm³/sd

Produced Oil rate 2019 5564 Sm³/sd

Produced gas rate 2019 465 kSm³/sd

Produced water rate 2019 0 Sm³/sd

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Parameter Value

Pressure downstream subsea choke during normal production 60 bara Wellhead temperature during normal operation 100 °C

2.3 Fluid characteristics

Fluid characteristics of the Oda production fluid is given in Table 2-4.

Table 2-4 Oda fluid composition /1/.

Component Mol% Mole Weight [g/mol] Density [g/cm³]

Nitrogen N2 1.614

Carbon Dioxide CO2 0.843

Hydrogen Sulfide H2S 0

Methane C1 23.128

Ethane C2 7.115

Propane C3 7.882

i-Butane iC4 1.640

n-Butane nC4 4.936

i-Pentane iC5 1.991

n-Pentane nC5 2.827

Hexanes C6 3.657

Heptanes C7 5.325 86.2 0.664

Octanes C8 5.440 96 0.738

Nonanes C9 3.759 107 0.781

Decanes Plus C10+ 29.843 271 0.867

2.4 Leak scenarios

Three different leak scenarios at two different locations are studied. Pipeline hole sizes are small (20 mm), medium (80 mm) and large (full bore rupture). One location is at the Oselvar SSIV (KP 14) and the other close to the Oda subsea template (KP 0.5).

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2.5 Assumptions

The following assumptions are applied for the leak modelling:

• There is no backflow from the Ula platform.

• When a leak is detected, well template valve, SSIV and topside ESD valve at Ula are all closed.

• Leak detection systems installed on Oda is claimed to be able to detect all leaks (small, medium, large) within one hour /3/. In the following, two scenarios are considered for all hole sizes. A detection and closing time of 15 minutes and a detection and closing time of 1 hour. For the medium and large leak, 15 minutes is likely a realistic detection time due to the fast reduction in pipeline pressure which should be detectable. For the small leak, a 1-hour detection time is likely the most realistic.

3 RESULTS

Results for small, medium and full bore rupture leak at all locations are included below. The pressure and temperature in the Oda production pipeline for the conditions given in Table 2-3 is shown in Figure 3-1.

Figure 3-1 Pressure and temperature Oda pipeline during normal operation.

The accumulated leak oil volume at standard conditions is given in Figure 3-1, while leak profiles for oil at standard conditions are given in Figure 3-2 - Figure 3-13. For the leak scenario at Oselvar SSIV, the accumulate leak oil volume at standard conditions is largest for the small leak compared to medium and full bore rupture. The reason for this is the slow depressurization of the pipeline with the ambient, with oil accumulating in the bottom of the Oda pipeline (SSIV located 5 below Oda template). The pressurized gas pushes the oil out of the pipeline. For the small leak located at the Oda template the accumulated leak oil volume rate is considerably smaller, as it is mainly the gas located at the top of the pipeline which is released during depressurization.

60 65 70 75 80 85 90 95 100 105

20 25 30 35 40 45 50 55 60 65

0 2 4 6 8 10 12 14

Temperature (deg C)

Pressure (bara)

KP [km]

Pressure and Temperature Oda Pipeline

Pressure Temperature

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Table 3-1 Accumulated leak oil volume at standard conditions.

Scenario Accumulated leak oil volume flow (Sm³) Oda subsea template Oselvar SSIV Small – 15-minute detection

time¹⁾

38 Sm³

347 Sm³

Small – 1-hour detection time¹⁾ 65 Sm³

360 Sm³

Medium – 15-minute detection time

227 Sm³

261 Sm³

Medium – 1-hour detection time 388 Sm³

437 Sm³

Full bore – 15-minute detection time

259 Sm³

279 Sm³

Full bore – 1-hour detection time 433 Sm³

456 Sm³

1) For the small leak at the Oselvar SSIV is accumulated leak oil volume is considerably larger than at the Oda subsea template. The Oda pipeline is lying on a downward gradient, with the highest point being the Oda template (65 meter water depth) and the lowest point the Oselvar SSIV (70 meter water depth). During the small leak at the Oselvar SSIV, the slow depressurization of the pipeline and the oil accumulating in the bottom means that oil is pushed out by the gas, as opposed to the small leak at the Oda template, where it is mainly the gas lying on top of the oil which is released during depressurization.

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Figure 3-2 Leak oil volume flow (Sm³/d) for small leak at Oda subsea template 15-minute detection time. Leak occurs at time t=1 hour.

Figure 3-3 Leak oil volume flow (Sm³/d) for small leak at Oda subsea template 1-hour detection time. Leak occurs at time t=1 hour.

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Figure 3-4 Leak oil volume flow (Sm³/d) for medium leak at Oda subsea template 15-minute detection time. Leak occurs at time t=1 hour.

Figure 3-5 Leak oil volume flow (Sm³/d) for medium leak at Oda subsea template 1-hour detection time. Leak occurs at time t=1 hour.

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Figure 3-6 Leak oil volume flow (Sm³/d) for full bore rupture at Oda subsea template 15- minute detection time. Leak occurs at time t=1 hour.

Figure 3-7 Leak oil volume flow (Sm³/d) for full bore rupture at Oda subsea template 1-hour detection time. Leak occurs at time t=1 hour.

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Figure 3-8 Leak oil volume flow (Sm³/d) for small leak at Oselvar SSIV 15-minute detection time. Leak occurs at time t=1 hour.

Figure 3-9 Leak oil volume flow (Sm³/d) for small leak at Oselvar SSIV 1-hour detection time.

Leak occurs at time t=1 hour.

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Figure 3-10 Leak oil volume flow (Sm³/d) for medium leak at Oselvar SSIV 15-minute detection time. Leak occurs at time t=1 hour.

Figure 3-11 Leak oil volume flow (Sm³/d) for medium leak at Oselvar SSIV 1-hour detection time. Leak occurs at time t=1 hour.

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Figure 3-12 Leak oil volume flow (Sm³/d) for full bore rupture at Oselvar SSIV 15-minute detection time. Leak occurs at time t=1 hour.

Figure 3-13 Leak oil volume flow (Sm³/d) for full bore rupture at Oselvar SSIV 1-hour detection time. Leak occurs at time t=1 hour.

4 REFERENCES

/1/ “Blowout Simulations, Butch Production Well”, Add Energy Report 2015

/2/ PL405 Oda Field Development, PDO Appendix 4 Facility Support Document, Document ID CE04- CEN-A-RA-00-00005, 2016

/3/ Ode Leak Detection Decision Memo, Document ID CE04-CEN-Z-RA-18-00001, 2016

/4/ Oda Subsea Tie-Back to Ula, Oda Basis of Design, Document ID CEU-PRJ-NOR0004-BOD-0010,