OCS Study MMS 2006-033

FINAL TASK 1 REPORT

VOLUME I

Alternative Oil Spill Occurrence Estimators and their 

Variability for the Chukchi Sea – Fault Tree Method

MMS Contract Number 1435-01-05-CT-39348

October, 2006

By

Bercha International Inc.

Calgary, Alberta, Canada

 U.S. Department of the Interior

 Minerals Management Service

 Alaska Outer Continental Shelf Region 

 
OCS Study MMS 2006-033

FINAL TASK 1 REPORT

VOLUME I

Alternative Oil Spill Occurrence Estimators and their 

Variability for the Chukchi Sea – Fault Tree Method

October, 2006

Principal Investigator: Dr. Frank G. Bercha, P.Eng. 

Bercha International Inc.

2926 Parkdale Boulevard N.W.

Calgary, Alberta, T2N 3S9, Canada

Email: berchaf@berchagroup.com

This study was funded by the U.S. Department of the Interior, Minerals Management Service (MMS), 

Alaska Outer Continental Shelf Region, Anchorage, under Contract No.

1435-01-05-CT-39348, as part of the MMS Alaska Environmental Studies Program.

DISCLAIMER

The opinion, findings, conclusions, or recommendations expressed in this report or product are those of 

the authors and do not necessarily reflect the views of the U.S. Department of the Interior, nor does 

mention of products constitute endorsement or recommendations for use by the Federal Government. 
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

i

ABSTRACT

Oil spill occurrence estimates were generated for several estimated future oil and gas 

development scenarios (including exploration, production, and abandonment) in the 

Chukchi Sea Outer Continental Shelf (OCS) lease sale region. Because sufficient 

historical data on offshore oil spills for this region do not exist, an oil spill occurrence 

model based on fault tree methodology was developed and applied. Using the fault trees, 

base data from the Gulf of Mexico including the variability of the data, were modified 

and augmented to represent expected Arctic offshore oil spillage frequencies. Three 

principal spill occurrence indicators, as follows, were quantified for each year of each 

scenario, as well as scenario life of field averages: 

ß Spill frequency

ß Spill frequency per barrel produced

ß Spill index, the product of spill size and spill frequency

These indicators were quantified for the following spill sizes: 

ß Small (S): 50 - 99 bbl

ß Medium (M): 100 - 999 bbl

ß Large (L): 1,000 - 9,999 bbl

ß Huge (H): >= 10,000 bbl

ß Significant (SG): >=1,000 bbl

Quantification was carried out for each future year for one principal Chukchi Sea

development scenario, with a range of development parameters, in duration up to 36

years. In addition, a comparative scenario for non-Arctic locations was formulated and

analyzed for oil spill occurrence. Generally, it was found that the non-Arctic spill 

indicators were likely to be significantly higher than those for similar scenarios in the 

Arctic. The computations were carried out using a Monte Carlo process to permit the 

inclusion of estimated uncertainties in the base and scenario data and Arctic effects. A 

wide range of details for each scenario was generated, including the following:

ß Expected time history of spill occurrences over the scenario life.

ß Spill occurrence variations by spill volumes in the above spill size ranges.

ß Spill occurrence variation by spill cause such as boat anchoring or ice 

gouging.

ß Spill occurrence contribution from each main facility type, including 

pipelines, platforms, and wells.

ß Comparison of spill occurrence predictions between Arctic and non-Arctic 

scenarios.

ß Life of field averages of spill occurrence estimators.

ß The variability in the results due to uncertainties in the inputs was expressed

as cumulative distribution functions and statistical measures.

In the final report, a detailed description of the methodology, results, and conclusions and 

recommendations is given, as well as a section on limitations of the study. 
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

ii

ACKNOWLEDGEMENTS

Grateful acknowledgement for funding and direction is made to MMS Alaska OCS 

Region. In particular, the following MMS personnel are acknowledged together with 

their roles:

ß Dr. Dick Prentki, Contracting Officer’s Technical Representative

ß Jim Craig, Resource Evaluation Section

ß Caryn Smith, Oil-Spill-Risk-Analysis Coordinator

ß Cheryl Anderson, MMS Spill Database Coordinator

ß Sharon Teger, Contracting Officer

ß Warren Horowitz, Oceanographer

ß Dennis Hinnah, Office of Field Operations

This work was carried out by Bercha International Inc. Key Bercha personnel on the 

project team were as follows:

ß Dr. Frank G. Bercha, Project Manager and Principal Engineer

ß Milan Cerovšek, Reliability Engineering Specialist

ß Edmund A. Yasinko, Offshore Pipeline Specialist

ß Wesley Abel, Offshore Engineering Specialist

ß Susan Charlton, Editorial and Word Processing Manager
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

iii

EXECUTIVE SUMMARY

A. Summary of Work Done

Oil spill occurrence estimators were generated for several estimated future oil and gas 

development scenarios (including exploration, production, and abandonment) in the 

Chukchi Sea Outer Continental Shelf (OCS) lease sale region. Because sufficient 

historical data on offshore oil spills for these regions do not exist, an oil spill occurrence 

model based on fault tree methodology was developed and applied. Using the fault trees, 

base data from the Gulf of Mexico, including their variability, were modified and 

augmented to represent expected Arctic offshore oil spillage frequencies for the Chukchi 

Sea region under study. Three principal spill occurrence indicators, as follows, were 

quantified for each year of each scenario, as well as scenario life of field averages: 

ß Spill frequency

ß Spill frequency per barrel produced

ß Spill index, the product of spill size and spill frequency

These indicators were quantified for the following spill sizes: 

ß Small (S): 50 - 99 bbl

ß Medium (M): 100 - 999 bbl

ß Large (L): 1,000 - 9,999 bbl

ß Huge (H): >=10,000 bbl

ß Signficant (SG): >=1,000 bbl

Fractional spill sizes were rounded up or down to the nearest whole number, with 

rounding up for any decimal ending in 5.

Quantification was carried out for each future year for an estimated Chukchi Sea 

exploration and development scenario, extending 36 years from 2009 to 2044 In addition, 

a comparative scenario for non-Arctic locations was formulated and analyzed for oil spill 

occurrence. Generally, it was found that the non-Arctic spill indicators were likely to be 

higher than those for a similar scenario in the Arctic. The computations were carried out 

using a Monte Carlo process to permit the inclusion of estimated uncertainties in the 

input data. A wide range of details for each scenario was generated, including the 

following:

ß Expected time history of spill occurrences over the scenario life.

ß Spill occurrence variations by spill volumes in the above spill size ranges.

ß Spill occurrence variation by spill cause such as boat anchoring or ice 

gouging.
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

iv

ß Spill occurrence contribution from each main facility type, including 

pipelines, platforms, and wells.

ß Comparison of spill occurrence predictions between Arctic and non-Arctic 

scenarios.

ß The variability in the results due to uncertainties in the input data expressed as 

cumulative distribution functions and statistical measures.

In the final report, a detailed description of the methodology, results, and conclusions and 

recommendations is given, as well as a section on limitations of the study. 

B. Conclusions

B.1 General Conclusions

Oil spill occurrence indicators were quantified for future offshore deve lopment scenarios 

in the Chukchi Sea Sale 193 area. The quantification considered variability of historical 

and future scenario data, as well as that of Arctic effects to predict oil spill occurrence 

indicators. Consideration of the variability of all input data yields both higher variability 

and a higher expected value of the spill occurrence indicators. The three types of spill 

occurrence indicators were: annual oil spill frequency, annual oil spill frequency per 

barrel produced, and annual spill index – and, additionally, the life of field averages for 

each of these three oil spill indicators were assessed.

B.2 Oil Spill Occurrence Indicators by Spill Size

How do spill indicators for the different scenarios and for their non-Arctic counterparts 

vary by spill size and source? Table 1 summarizes the Life of Field (LOF) average spill 

indicator values. Figure 1 illustrates these. The following can be observed from Table 1.

ß Spill frequency per year and per barrel-year decreases significantly with 

increasing spill size for all scenarios. 

ß The spill index increases significantly with spill size for both scenarios.

ß All non-Arctic scenario spill indicators are greater than their Arctic 

counterparts. Non-Arctic spill indicators are approximately 30% greater.
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

v

Table 1

Summary of Life of Field Average Spill Indicators by Spill Source and Size

Chukchi Sea Chukchi Sea - Non Arctic

Spill Indicators

LOF Average

Spill Frequency 

per 10

3 years

Spill Frequency 

per 10

9 bbl 

produced

Spill Index

[bbl]

Spill Frequency 

per 10

3 years

Spill Frequency 

per 10

9 bbl 

produced

Spill Index

[bbl]

Small and Medium Spills 18.750 0.675 8 26.111 0.940 11

50-999 bbl 57% 57% 2% 53% 53% 2%

8.735 0.314 58 14.808 0.533 95 Large Spills

1000-9999 bbl 26% 26% 13% 30% 30% 14%

5.578 0.201 399 8.593 0.309 574 Huge Spills

=>10000 bbl 17% 17% 86% 17% 17% 84%

14.313 0.515 458 23.401 0.842 669 Significant Spills

=>1000 bbl 43% 43% 98% 47% 47% 98%

33.063 1.190 465 49.512 1.782 680

All Spills

100% 100% 100% 100% 100% 100%

20.301 0.730 69 33.248 1.196 125

Pipeline Spills

61% 61% 15% 67% 67% 18%

7.362 0.265 9 8.668 0.312 10

Platform Spills

22% 22% 2% 18% 18% 2%

5.401 0.194 387 7.595 0.273 544

Well Spills

16% 16% 83% 15% 15% 80%

12.763 0.459 396 16.264 0.585 554

Platform and Well Spills

39% 39% 85% 33% 33% 82%

33.063 1.190 465 49.512 1.782 680

All Spills

100% 100% 100% 100% 100% 100%
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

vi

Figure 1

Life of Field Spill Indicators – By Spill Size

Life of Field Average

0

10

20

30

40

50

Spill Frequency

per 1000 years

Huge Spills

=>10000 bbl

5.578 8.593

Large Spills

1000-9999 bbl

8.735 14.808

Small and Medium Spills

50-999 bbl

18.750 26.111

Chukchi Sea Chukchi Sea - Non Arctic

Life of Field Average

0.0

0.5

1.0

1.5

2.0

Spill Frequency

 per 10^9 bbl produced

Huge Spills

=>10000 bbl

0.201 0.309

Large Spills

1000-9999 bbl

0.314 0.533

Small and Medium Spills

50-999 bbl

0.675 0.940

Chukchi Sea Chukchi Sea - Non Arctic

Life of Field Average

0

100

200

300

400

500

600

700

Spill Index [bbl]

Huge Spills

=>10000 bbl

399 574

Large Spills

1000-9999 bbl

58 95

Small and Medium Spills

50-999 bbl

8 11

Chukchi Sea Chukchi Sea - Non Arctic
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

vii

B.3 Oil Spill Occurrence Indicators by Spill Source

How do the spill indicators vary by spill source facility type for representative scenarios? 

The contributions of spill indicators by source facility have been summarized by life of 

field averages, in Table 1 and also in Figure 2, for all spill sizes. Table 1 and Figure 2

give the component contributions, in absolute value and percent, for each of the main 

facility types; namely, pipelines (P/L), platforms, and wells. The following may be noted 

from Table 1:

ß Pipelines contribute the most (61%) to the two spill frequency indicators. 

ß Platforms are next in relative contribution to spill frequencies (22%) and least

in contribution to spill index (2%). 

ß Wells are by far (at 83%) the highest contributors to spill index, while 

platforms and wells together are responsible for a 82% contribution to the spill 

index. 

ß It can be concluded that pipelines are likely to have the most, but smaller 

spills, while wells will have the least number, but largest spills. Platforms will 

be in between, with a tendency towards more spills than wells, but less or 

about the same number as platforms.

Figures 3 and 4 show relative contributions by facility and spill size to the maximum 

production year 2024 and Life of Field average spill indicators, respectively. Although 

Life of Field average spill indicator absolute values are significantly smaller than the 

maximum production year values, the proportional contributions by spill facility source 

and spill size are almost identical. 

B.4 Variability of Oil Spill Occurrence Indicators

Figures 5, 6, and 7 show the Cumulative Distribution Functions for each of the Chukchi

Sea Life of Field average spill indicators by spill size and source. Generally, the 

following can be observed from the figures:

ß The variance of the frequency spill indicators (Figures 5 and 6) decreases as 

spill size increases for pipelines and platforms. In other words, small and 

medium spills illustrate the largest variability; huge spills show the least 

variability for these facilities. 

ß The opposite occurs for wells.

ß The variability of the spill index (Figure 7) shows the opposite trend for 

pipelines and platforms. 
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

viii

Figure 2

Life of Field Spill Indicators – By Source Composition

Life of Field Average

0

10

20

30

40

50

Spill Frequency

per 1000 years

Well Spills 5.401 7.595

Platform Spills 7.362 8.668

Pipeline Spills 20.301 33.248

Chukchi Sea Chukchi Sea - Non Arctic

Life of Field Average

0.0

0.5

1.0

1.5

2.0

Spill Frequency

 per 10^9 bbl produced

Well Spills 0.194 0.273

Platform Spills 0.265 0.312

Pipeline Spills 0.730 1.196

Chukchi Sea Chukchi Sea - Non Arctic

Life of Field Average

0

100

200

300

400

500

600

700

Spill Index [bbl]

Well Spills 387 544

Platform Spills 9 10

Pipeline Spills 69 125

Chukchi Sea Chukchi Sea - Non Arctic
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

ix

BY SPILL SOURCE BY SPILL SIZE

Figure 3

Chukchi Sea – Year 2024 – Spill Indicator Composition by Source and Spill Size

Year 2024

 Spill Frequency per 10^3 years

24%

58%

18%

P/L

Platforms

Wells TOTAL 50.847

Year 2024

 Spill Frequency per 10^9 bbl produced

24%

58%

18%

P/L

Platforms

Wells TOTAL 0.620

Year 2024

 Spill Index [bbl]

85%

2% 13%

P/L

Platforms

Wells TOTAL 785

Year 2024

 Spill Frequency per 10^3 years

56%

26%

18%

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

 =>10000 bbl

TOTAL 50.847

Year 2024

 Spill Frequency per 10^9 bbl produced

26%

56%

18%

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

 =>10000 bbl

TOTAL 0.620

Year 2024

 Spill Index [bbl]

2%

86%

12%

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

 =>10000 bbl

TOTAL 785
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

x

BY SPILL SOURCE BY SPILL SIZE

Figure 4

Chukchi Sea – Life of Field Average Spill Indicator Composition by Source and Spill Size

LOF Average

 Spill Frequency per 10^3 years

62%

16%

22%

P/L

Platforms

Wells TOTAL 33.063

LOF Average

 Spill Frequency per 10^9 bbl produced

62%

16%

22%

P/L

Platforms

Wells TOTAL 1.190

LOF Average

 Spill Frequency per 10^9 bbl produced

57%

26%

17%

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

 =>10000 bbl

TOTAL 1.190

LOF Average

 Spill Frequency per 10^3 years

57%

17%

26%

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

 =>10000 bbl

TOTAL 33.063

LOF Average

 Spill Index [bbl]

15%

2%

83%

P/L

Platforms

Wells TOTAL 465

LOF Average

 Spill Index [bbl]

2%

13%

85%

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

 =>10000 bbl

TOTAL 465
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

xi

Figure 5

Chukchi Sea Life of Field Average Spill Frequency – CDF

CDF LOF Average - Pipeline

0

10

20

30

40

50

60

70

80

90

100

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28

Spill Frequency per 1000 years

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - Platforms

0

10

20

30

40

50

60

70

80

90

100

0 2 4 6 8 10 12 14 16 18 20

Spill Frequency per 1000 years

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - Pipeline

0

10

20

30

40

50

60

70

80

90

100

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF LOF Average - Platforms

0

10

20

30

40

50

60

70

80

90

100

0 2 4 6 8 10 12 14 16 18 20

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

0 1 2 3 4 5 6

Spill Frequency per 1000 years

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - Platforms + Wells

0

10

20

30

40

50

60

70

80

90

100

0 2 4 6 8 10 12 14 16 18 20

Spill Frequency per 1000 years

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

0 1 2 3 4 5 6 7 8 9 10

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF LOF Average - Platforms + Wells

0

10

20

30

40

50

60

70

80

90

100

0 2 4 6 8 10 12 14 16 18 20 22 24 26

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF LOF Average - All

0

10

20

30

40

50

60

70

80

90

100

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40

Spill Frequency per 1000 years

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - All

0

10

20

30

40

50

60

70

80

90

100

0 5 10 15 20 25 30 35 40 45 50 55

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

xii

Figure 6

Chukchi Sea Life of Field Average Spill Frequency per Barrel Produced – CDF

CDF LOF Average - Pipeline

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Spill Frequency per 10^9 bbl Produced

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - Platforms

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

Spill Frequency per 10^9 bbl Produced

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - Pipeline

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4

Spill Frequency per 10^9 bbl Produced

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF LOF Average - Platforms

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Spill Frequency per 10^9 bbl Produced

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

0.00 0.05 0.10 0.15 0.20

Spill Frequency per 10^9 bbl Produced

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - Platforms + Wells

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

Spill Frequency per 10^9 bbl Produced

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35

Spill Frequency per 10^9 bbl Produced

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF LOF Average - Platforms + Wells

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Spill Frequency per 10^9 bbl Produced

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF LOF Average - All

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5

Spill Frequency per 10^9 bbl Produced

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - All

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8

Spill Frequency per 10^9 bbl Produced

CDF %

Significant Spills

=>1000 bbl

All Spills
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

xiii

Figure 7

Chukchi Sea Life of Field Average Spill Index (bbl) – CDF

CDF LOF Average - Pipeline

0

10

20

30

40

50

60

70

80

90

100

0 10 20 30 40 50 60 70 80 90 100 110 120

Spill Index [bbl]

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - Platforms

0

10

20

30

40

50

60

70

80

90

100

0 2 4 6 8 10 12 14 16 18 20

Spill Index [bbl]

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - Pipeline

0

10

20

30

40

50

60

70

80

90

100

0 10 20 30 40 50 60 70 80 90 100 110 120 130 140

Spill Index [bbl]

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF LOF Average - Platforms

0

10

20

30

40

50

60

70

80

90

100

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

Spill Index [bbl]

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

0 100 200 300 400 500 600 700 800 900

Spill Index [bbl]

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - Platforms + Wells

0

10

20

30

40

50

60

70

80

90

100

0 100 200 300 400 500 600 700 800 900

Spill Index [bbl]

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

0 100 200 300 400 500 600 700 800 900

Spill Index [bbl]

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF LOF Average - Platforms + Wells

0

10

20

30

40

50

60

70

80

90

100

0 100 200 300 400 500 600 700 800 900

Spill Index [bbl]

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF LOF Average - All

0

10

20

30

40

50

60

70

80

90

100

0 100 200 300 400 500 600 700 800 900 1000

Spill Index [bbl]

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - All

0

10

20

30

40

50

60

70

80

90

100

0 100 200 300 400 500 600 700 800 900 1000

Spill Index [bbl]

CDF %

Significant Spills

=>1000 bbl

All Spills
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The Cumulative Distribution Functions contain extensive information on the statistical 

properties of the spill indicators. For example, from Figure 5, it can be seen, for all 

significant spills, that the Life of Field average mean (50%) value of 14 (spills per 1,000 

years) ranges between 23 and 7 at the upper and lower 95% confidence intervals. A 

similar percentage variation is shown for the Life of Field average spill frequency per 

barrel produced in Figure 6. The spill index variability shown in Figure 7 is 

proportionally higher. For example, in Figure 7, the mean value of the significant spills 

index of 450 per billion barrels produced ranges from 250 to 700. 

C. Conclusions on the Methodology and its Applicability

An analytical tool for the prediction of oil spill occurrence indicators for systems without 

history, such as future offshore oil production developments in the Chukchi Sea, has been 

developed based on the utilization of fault tree methodology. Although the results 

generated are voluminous, they are essentially transparent, simple, and easy to 

understand. The analytical tool developed is also quite transparent, very efficient in terms 

of computer time and input-output capability. In addition, the predictive model is setup so 

that any input variables can be entered as distributions. 

A wealth of information that can be utilized for the optimal planning and regulation of 

future developments is generated by the analytical tool. Key aspects of the analytical tool 

capability may be summarized as follows:

ß Ability to generate expected and mean values as well as their variability in 

rigorous numerical statistical format.

ß Use of verifiable input data based on MMS or other historical spill data and 

statistics.

ß Ability to independently vary the impacts of different causes on the spill 

occurrences as well as add new causes such as some of those that may be 

expected for the Arctic or other new environments.

ß Ability to generate spill occurrence indicator characteristics such as annual 

variations, facility contributions, spill size distributions, and life of field (Life of 

Field) averages. 

ß Ability to generate comparative spill occurrence indicators such as those of 

comparable scenarios in more temperate regions. The model developed provides a 

basis for estimating each Arctic effect’s importance through sensitivity analysis as 

well as propagation of uncertainties. 

ß Capability to quantify uncertainties rigorously, together with their measures of 

variability.
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D. Limitations of the Methodology and Results

During the work, a number of limitations in the input data, the scenarios, the application 

of the fault tree methodology, and finally the oil spill occurrence indicators themselves 

have been identified. These shortcomings are summarized in the following paragraphs.

Two categories of input data were used; namely the historical spill data and the Arctic 

effect data. Although a verifiable and optimal historical spill data set has been used, the 

following shortcomings may be noted:

ß Gulf of Mexico (OCS) historical data bases were provided by MMS for 

pipelines and facilities, and were used as a starting point for the fault tree 

analysis. Although these data are adequate, a broader population base would 

give more robust statistics. Unfortunately, data from a broader population 

base, such as the North Sea, do not contain the level of detail provided in the 

GOM data.

ß The Arctic effects include modifications in causes associated with the 

historical data set as well as additions of spill causes unique to the Arctic 

environment. Quantification of existing causes for Arctic effects was done in a 

relative cursory way restricted to engineering judgment. 

ß Upheaval buckling effect assessments were included on the basis of an 

educated guess; no engineering analysis was carried out for the assessment of 

frequencies to be expected for these effects. 

ß A reproducible but relatively elementary analysis of gouging and scour effects 

was carried out. 

The scenarios are those developed for use in the MMS Alaska OCS Region 

Environmental Impact Statements for Oil and Gas Lease Sales. As estimated they appear 

reasonable and were incorporated in the form provided. 

ß The only shortcoming appears to be that the facility abandonment rate is

significantly lower than the rate of decline in production.

The following comments can be made on limitations associated with the indicators that 

have been generated:

ß The indicators have inherited the deficiencies of the input and scenario data 

noted above. 

ß The model generating the indicators is fundamentally a linear model which 

ignores the effects of scale, of time variations such as the learning and wearout curves (Bathtub curve), and production volume non-linear effects. 
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E. Recommendations

The following recommendations based on the work may be made:

ß Continue to utilize the Monte Carlo spill occurrence indicator model for new 

scenarios to support MMS needs, as it is currently the best predictive spill 

occurrence model available.

ß Utilize the oil spill occurrence indicator model to generate additional model 

validation information, including direct application to specific non-Arctic 

scenarios, such as GOM projects, which have an oil spill statistical history.

ß Utilize the oil spill occurrence indicator model in a sensitivity mode to 

identify the importance of different Arctic effect variables introduced to 

provide a prioritized list of those items having the highest potential impact on 

Arctic oil spills.

ß Generalize the model so that it can be run both in an adjusted expected value 

and a distributed value (Monte Carlo) form with the intent that expected value 

form can be utilized without the Monte Carlo add-in for preliminary estimates 

and sensitivity analyses, while for more comprehensive rigorous studies, the 

Monte Carlo version can be used. 
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TABLE OF CONTENTS

VOLUME I

CHAPTER PAGE

Abstract.................................................................................................................................i

Acknowledgements...............................................................................................................ii

Executive Summary.............................................................................................................iii

Table of Contents............................................................................................................. xvii

List of Appendices.............................................................................................................xix

List of Tables...................................................................................................................... xx

List of Figures................................................................................................................... xxi

Glossary of Terms and Acronyms.................................................................................... xxii

1 Introduction ................................................................................................... 1.1

1.1 General Introduction.............................................................................................1.1

1.2 Study Objectives...................................................................................................1.1

1.3 Study Area Definition...........................................................................................1.2

1.4 General Background .............................................................................................1.2

1.5 Technical Approaches..........................................................................................1.4

1.6 Scope of Work ......................................................................................................1.5

1.7 Work Organization ...............................................................................................1.6

1.8 Outline of Report..................................................................................................1.8

2 Historical Data ................................................................................................. 2.1

2.1 Approaches to Historical Data ..............................................................................2.1

2.2 Pipeline Oil Spill Data ..........................................................................................2.1

2.3 Platform Spill Data ...............................................................................................2.5

2.4 Oil Well Blowout Data .........................................................................................2.5

2.5 Arctic Effects Historical Data...............................................................................2.9

2.5.1 General Approaches to the Quantification of Arctic Effects....................2.9

2.5.2 Ice Gouging ..............................................................................................2.9

2.5.3 Strudel Scour ..........................................................................................2.10

2.5.4 Upheaval Buckling..................................................................................2.12

2.5.5 Thaw Settlement......................................................................................2.12

2.5.6 Platform Arctic Unique Effects...............................................................2.12

2.6 Historical Spill Size Distribution........................................................................2.14

3 Future Development Scenarios.................................................................... 3.1

3.1 Approaches to Future Development Scenarios.....................................................3.1

3.2 Chukchi Sea Development Scenarios...................................................................3.3
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4 Fault Tree Analysis for Arctic Oil Spill Frequencies.............................. 4.1

4.1 General Description of Fault Tree Analysis.........................................................4.1

4.2 Fault Tree Methodology .......................................................................................4.1

4.2.1 Fault Tree Analysis Basics .......................................................................4.1

4.2.2 Current Application of Fault Trees..........................................................4.3

4.2.3 Monte Carlo Simulation ...........................................................................4.5

4.2.4 Distribution Derived from Historical Data for Monte Carlo Analysis ....4.7

4.2.5 Approaches to Assessment of Arctic Spill Frequency Variability ..........4.10

4.3 Pipeline Fault Tree Analysis...............................................................................4.10

4.3.1 Arctic Pipeline Spill Causal Frequency Distributions ...........................4.10

4.3.3 Arctic Pipeline Fault Tree Frequency Calculations...............................4.14

4.4 Platform Fault Tree Analysis..............................................................................4.21

4.4.1 Arctic Platform Spill Causal Frequency Distributions ..........................4.21

4.4.2 Arctic Platform Fault Tree Spill Frequency Calculations .....................4.21

4.5 Blowout Frequency Analysis..............................................................................4.28

4.5.1 Well Blowout First Order Arctic Effects................................................4.28

4.5.2 Arctic Well Blowout Spill Frequency Calculations................................4.28

4.6 Spill Volume Distributions .................................................................................4.28

5 Oil Spill Occurrence Indicator Quantification......................................... 5.1

5.1 Definition of Oil Spill Occurrence Indicators ......................................................5.1

5.2 Oil Spill Occurrence Indicator Calculation Process.............................................5.1

5.3 Summary of Chukchi Sea Oil Spill Occurrence Indicators..................................5.3

5.3.1 Chukchi Sea Oil Spill Occurrence Indicators ..........................................5.3

5.3.2 Comparative Non-Arctic Indicator Assessment.....................................5.11

5.4 Summary of Representative Oil Spill Occurrence Indicator Results .................5.20

6 Conclusions and Recommendations............................................................ 6.1

6.1 Conclusions ......................................................................................................6.1

6.1.1 General Conclusions................................................................................6.1

6.1.2 Oil Spill Occurrence Indicators by Spill Size ...........................................6.1

6.1.3 Oil Spill Occurrence Indicators by Spill Source ......................................6.4

6.1.4 Variability of Oil Spill Occurrence Indicators.........................................6.4

6.2 Conclusions on the Methodology and Its Applicability .......................................6.5

6.3 Limitations of the Methodology and Results........................................................6.6

6.4 Recommendations.................................................................................................6.7

References................................................................................................................R.1
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LIST OF APPENDICES

(VOLUME II – APPENDICES)

APPENDIX

1 Historical Data Analysis

2 Fault Tree Analysis

3 Hazard Scenarios

4 Spill Occurrence

4.1 Arctic Spill Occurrence – Chukchi Sea

4.2 Arctic Spill Occurrence – Chukchi Sea Non-Arctic

5 Conclusions
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LIST OF TABLES

TABLE PAGE

2.1 GOM OCS Pipeline Spills Statistics Summary (1972-1999)...............................2.2

2.2 Analysis of GOM OCS Spill Data for Causal Distribution and Spill Size..................2.3

2.3 Distribution and Frequency of Historical Spills - Pipeline...................................2.4

2.4 Pipeline Historical Spill Frequency Variability....................................................2.4

2.5 Analysis of GOM OCS Platform Spill Data for Causal Distribution Spill Size (1972-1999).2.6

2.6 Causal and Spill Size Distribution of GOM OCS Platform Spills (1972-1999)..........2.6

2.7 Platform Historical Spill Frequency Variability...................................................2.6

2.8 Summary of North Sea and Gulf of Mexico Blowout Rates................................2.7

2.9 Well Blowout Historical Spill Size Distribution..................................................2.7

2.10 Well Blowout Historical Spill Probability and Size Variability...........................2.8

2.11 Summary of Pipeline Unique Arctic Effect Inputs.............................................2.11

2.12 Summary of Platform Unique Arctic Effect Inputs............................................2.13

2.13 Summary of Historical Spill Size Distribution Parameters................................2.14

3.1 Classification of Development Scenarios.............................................................3.2

3.2 Summary of Exploration and Development Scenario, Chukchi Sea OCS...........3.4

3.3 Chukchi Sea Development Data (2009-2044)......................................................3.5

3.4 Chukchi Sea Development Parameter Ranges (2009-2044) ................................3.8

4.1 Pipeline Spill Frequency Triangular Distribution Properties ...............................4.8

4.2 Platform Spill Frequency Triangular Distribution Properties..............................4.8

4.3 Well Blowout Spill Frequency Triangular Distribution Properties......................4.9

4.4 Pipeline Arctic Effect Derivation Summary.......................................................4.11

4.5 Pipeline Arctic Effect Distribution Derivation Summary ..................................4.13

4.6 Arctic Pipeline Small Spill (50-99 bbl) Frequencies..........................................4.16

4.7 Arctic Pipeline Medium Spill (100-999 bbl) Frequencies..................................4.17

4.8 Arctic Pipeline Large Spill (1,000-9,999 bbl) Frequencies................................4.18

4.9 Arctic Pipeline Huge Spill (=10,000 bbl) Frequencies.......................................4.19

4.10 Arctic Pipeline Spill Frequencies Expected Value Summary ............................4.20

4.11 Platform Arctic Effect Derivation Summary......................................................4.22

4.12 Platform Arctic Effect Distribution Derivation Summary..................................4.23

4.13 Arctic Platform Small and Medium Spill Frequencies.......................................4.25

4.14 Arctic Platform Large and Huge Spill Frequencies............................................4.26

4.15 Arctic Platforms Spill Frequency Expected Value Summary ............................4.27

4.16 Well Fault Tree Analysis Arctic Effect Summary..............................................4.29

4.17 Arctic Well Blowout Frequencies......................................................................4.30

4.18 Summary of Spill Size Distribution Parameters.................................................4.31

5.1 Chukchi Sea Year 2024 – Monte Carlo Results...................................................5.9

5.2 Composition of Spill Indicators –Life of Field Average ....................................5.12

5.3 Summary of Life of Field Average Spill Indicators by Spill Source and Size ...5.17

6.1 Summary of Life of Field Average Spill Indicators by Spill Source and Size .....6.2
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LIST OF FIGURES

FIGURE PAGE

1.1 Study Area Map....................................................................................................1.3

1.2 Calculation Flow Chart.........................................................................................1.7

4.1 Fault Tree Basics ..................................................................................................4.2

4.2 Example of Fault Tree to Transform Historical (GOM) to Arctic Spill Frequencies..4.4

4.3 Monte Carlo Technique Schematic ......................................................................4.6

4.4 Large Spill Frequencies for Pipeline ..................................................................4.15

4.5 Spill Frequencies Platform Fault Tree ................................................................4.24

5.1 CalculationFlow Chart.........................................................................................5.2

5.2 Chukchi Sea Spill Frequency per 1,000 Years.....................................................5.4

5.3 Chukchi Sea Spill Frequency per 109 Barrels Produced ......................................5.4

5.4 Chukchi Sea Spill Index .......................................................................................5.5

5.5 Chukchi Sea Spill Indicators – Pipeline ...............................................................5.6

5.6 Chukchi Sea Spill Indicators – Platforms.............................................................5.7

5.7 Chukchi Sea Spill Indicators – Wells...................................................................5.8

5.8 Chukchi Sea Spill Indicator Distributions – Year 2024 .....................................5.10

5.9 Chukchi Sea Life of Field Average Spill Frequency..........................................5.13

5.10 Chukchi Sea Life of Field Average Spills per Barrel Produced.........................5.14

5.11 Chukchi Sea Spill Frequency – Arctic and Non-Arctic......................................5.15

5.12 Chukchi Sea Spill Frequency per 109 Barrels Produced – Arctic and Non-Arctic..5.15

5.13 Chukchi Sea Spill Index – Arctic and Non-Arctic .............................................5.16

5.14 Life of Field Spill Indicators –By Spill Size ......................................................5.18

5.15 Life of Field Spill Indicators – By Source Composition....................................5.19

5.16 Chukchi Sea – Year 2024 – Spill Indicator Composition by Source .................5.21

5.17 Chukchi Sea – Life of Field Average Spill Indicator Composition by Source ..5.22

5.18 Chukchi Sea Life of Field Average Spill Frequency - CDF...............................5.24

5.19 Chukchi Sea Life of Field Average Spill Frequency per Barrel Produced – CDF..5.25

5.20 Chukchi Sea Life of Field Average Spill Index (bbl) – CDF .............................5.30

6.1 Life of Field Spill Indicators – By Spill Size .......................................................6.3
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GLOSSARY OF TERMS AND ACRONYMS

Bbbl Billion Barrels

CDF Cumulative Distribution Function

Consequence The direct effect of an accidental event.

GOM Gulf of Mexico

Hazard A condition with a potential to create risks such as accidental

leakage of natural gas from a pressurized vessel.

KBpd Thousand Barrels per day

LOF Life of Field

MMbbl Million Barrels

MMS Minerals Management Service, Department of the Interior

Monte Carlo A numerical method for evaluating algebraic combinations of

statistical distributions.

OCS Outer Continental Shelf

QRA Quantitative Risk Assessment

Risk A compound measure of the probability and magnitude of adverse 

effect.

RLS Release

SINTEF The Foundation of Scientific and Industrial Research at the

Norwegian Institute of Technology

Spill Frequency The number of spills of a given spill size range per year. Usually

expressed as spills per 1,000 years (and so indicated).

Spill Frequency per 

Barrel Produced

The number of spills of a given spill size range per barrel

produced. Usually expressed as spills per billion barrels produced 

(and so indicated).

Spill Index The product of spill frequency for a given spill size range and the 

mean spill size for that spill size range.

Spill Occurrence Characterization of an oil spill as an annual frequency and

associated spill size or spill size range.

Spill Occurrence 

Indicator

Any of the oil spill occurrence characteristics; namely, spill

frequency, spill frequency per barrel produced, or spill index

(defined above).

Spill Sizes Small (S): 50 - 99 bbl

Medium (M): 100 - 999 bbl

Large (L): 1,000 - 9,999 bbl

Huge (H): >=10,000 bbl

Significant (SG): >=1,000 bbl
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1.1

CHAPTER 1

INTRODUCTION

1.1 General Introduction

The MMS Alaska Outer Continental Shelf (OCS) Region uses oil spill occurrence 

estimates for National Environmental Policy Act assessments for all parts of their area of 

jurisdiction, ranging from near shore through shallow water, to deeper water. Although 

land to 3 nautical miles is not within MMS jurisdiction, it is included in the MMS 

environmental impact analysis; hence it is also included in the study area here. In 2002

and early 2006, studies were carried out by Bercha International Inc. [11, 12] * to assess 

and quantify oil spill occurrence indicators for the Beaufort and Chukchi Seas. In this 

study, methodologies based on fault tree analysis were developed for the assessment of 

oil spill rates associated with exploration and production facilities and operations in 

deeper waters in the Chukchi and Beaufort Seas. 

The prediction of the reliability (or failure) of systems without history can be approached 

through a variety of mathematical techniques, with one of the most preferable and 

accepted being fault trees [7, 10, 14, 23, 26, 45, 51, 65], and their combination with 

numerical distribution methods such as Monte Carlo simulation [9, 45]. In the previous

study [12], fault tree methodology was applied to the prediction of oil spill rates for oil 

and gas developments such as those now operational or contemplated for the Beaufort 

and Chukchi Seas in the Alaska OCS, and used to generate predictions of oil spill 

occurrence indicators. 

As there is a paucity of offshore Arctic oil spill occurrences, associated data worldwide

and from the Gulf of Mexico (GOM) were used as a starting point to develop a 

simulation model of oil spill occurrence probabilities. The model for non-Arctic 

occurrence probabilities was then modified to include Arctic effects and their 

variabilities. In the preceding Beaufort Sea study [12], variability in the non-Arctic input 

data was considered; but variability of the future development scenario physical facility 

parameters, such as miles of sub-sea pipeline, was not considered. In the present study, 

both the historical data variability and that of the future development scenario 

characteristics is included in calculation of oil spill occurrence probabilities. 

1.2 Study Objectives

The objectives of this study are as follows:

• Assimilate and analyze world-wide and US OCS oil spill statistics and evaluate their 

applicability to lease tracts which could be offered in the upcoming Chukchi Sea 

sales.

 

*

 Numbers in square brackets refer to citations listed in the “References” section of this report.
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1.2

• Develop the fault tree method for estimating oil spill occurrences from Chukchi Sea 

developments associated with spills of different size categories.

• Using the fault tree approach, develop alternative oil spill indicators and assess their 

variability, including effect of variability of both the historical data the future 

development scenario parameters. 

• Provide statistical support to MMS in evaluation of statistical issues in estimation of 

oil spill rates. 

• One of the specific objectives of this study was to add the variability of the nonArctic factors.

1.3 Study Area Definition

The geographical study area is the offshore continental shelf in the U.S. Chukchi Sea, as 

generally illustrated in Figure 1.1. Of interest is the offshore area from landfall to 

approximately the 60-meter isobath. This area is selected due to the possibility of future 

oil and gas development within it, based on potential leases. Although a depth greater

than 60 meters was originally contemplated as part of the study area, the analysis of 

development scenarios has indicated that it is highly unlikely that any oil and gas 

developments will take place in depths greater than 60 meters. More details on the leases 

and the geology of the study area are described in several MMS publications [35, 36, 37, 

38, 39].

Temporally, the study scenarios investigated span into the future from the Year 2009 to 

2044. 

1.4 General Background

The final reports, dated August 2002 [11] and January 2006 [12], described the 

methodology and results of the fault tree method for the evaluation of oil spill occurrence 

estimators for the Beaufort and Chukchi Seas. The focus of the first reports was on the 

initial development of a fault tree method to model both non-Arctic GOM spill causes as 

well as Arctic causes and effects that would be encountered in the Beaufort and Chukchi 

Seas OCS Regions. The variability of the parameters associated with Arctic effects was 

developed in order to provide an estimate of the variance in the spill occurrence 

predictions resulting directly from variances in the Arctic effects. In addition, in 2006

[12], variance in the Gulf of Mexico (GOM) historical data was incorporated. However, 

neither of the two earlier studies [11, 12] considered the variability of the future 

development scenario parameters. In the present study, this variability is also considered; 

accordingly, the number of wells and pipeline lengths likely to be installed is included as 

a distribution rather than as single valued quantities. These variances were numerically 

incorporated through the use of Monte Carlo simulation for the fault tree model 

numerical predictions. 
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1.3

Figure 1.1

Study Area Map

CHUKCHI

SEA BEAUFORT

SEA

U.S.A.

CANADA

180°

130°

STUDY AREA REPRESENTED AS:

SHOWS OFFSHORE FROM LANDFALL T0

 600-METER ISOBATH, APPROXIMATELY

70°
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1.4

1.5 Technical Approaches

Uncertainties in the results of oil spill occurrence predictions generated in this study can 

be attributed to uncertainties in input data, scenario characterization, and the occurrence 

model. In the original 2002 study [11], uncertainties in input data were quantified for the 

Arctic effects only. Uncertainties in the scenario were included through the choice of 

scenarios representing the expected and maximum development levels. In the 2006 study 

[12], uncertainties in the non-Arctic input data were also included. Thus the principal 

source of uncertainty in the occurrence results was that caused by uncertainties in the 

Arctic and non-Arctic input parameters themselves. 

The non-Arctic input parameters fall under two principal categories as follows:

ß Spill frequencies

ß Spill volumes

These spill frequencies and volumes as used in the study were derived from the following 

principal sources:

ß Pipeline spills – GOM data

ß Platform spills – GOM data

ß Well (drilling and production) blowout spills – Worldwide data

The specific sources of the data are described in detail in Chapter 2 of this report.

In the current study, in addition to the above data uncertainties, those of the following 

main facility parameters were also considered:

ß Number of wells drilled

ß Number of platforms and sub-sea production wells

ß Sub-sea pipeline length

o For pipelines less than nominal 10” diameter

o For pipelines greater than or equal to 10” nominal diameter.

The inclusion of all of these types of variability – Arctic effects, non-Arctic data, and 

facility parameters – is intended to provide a realistic estimate of the spill occurrence 

indicators and their resultant variability. 
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1.5

1.6 Scope of Work

Task 1: Data Assimilation

a) Update of GOM pipeline and platform spill data.

b) Identification of alternative data sources including the Foundation 

of Scientific and Industrial Research at the Norwegian Institute of 

Technoloty (SINTEF), United Kingdom Health & Safety 

Executive (HSE), and others.

c) Assimilation and analysis of additional blowout data (SINTEF).

d) Chukchi Sea scenario development from MMS information. 

Task 2: Development of Non-Arctic Total Annual Spill Frequency and Volume 

Probability Distributions

a) Development of non-Arctic total annual spill frequency and 

volume distribution for pipelines.

b) Development of non-Arctic total annual spill frequency and 

volume distribution for platforms.

c) Development of non-Arctic total annual spill frequency and 

volume distribution for well drilling and production wells.

Task 3: Development of Arctic Spill Frequency Causal Event and Total 

Probability Distributions

a) Development of Arctic spill frequency causal event probability 

distributions associated with pipeline spills.

b) Development of Arctic spill frequency causal event probability 

distributions associated with platform spills.

c) Development of Arctic spill frequency causal event probability 

distributions associated with well drilling and production well 

blowouts.

Task 4: Generation of Oil Spill Occurrence Estimator Probability Distributions

a) Modification of model to accommodate variability in future 

development scenario parameters.

b) Model runs for variable Chukchi Sea scenario.

c) Model runs for comparative non-Arctic scenario.

Task 5: Reporting

a) Preliminary results following completion of Tasks 1, 2, 3, and 4.

b) Draft Final Report and Final Report.
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1.7 Work Organization

The present study consisted of statistical and engineering investigations, followed by 

numerical simulation. Although the assimilation of historical and future scenario data is 

of key significance to the work, the salient contribution consisted primarily of the 

analytical work involving fault trees and oil spill occurrence indicator generation. 

Although the individual calculations are relatively simple, the subdivision of the 

calculations into realistic representative categories of facilities, spill sizes, and water 

depth for different variable development scenarios resulted in a relatively complex mix of 

computations, generally illustrated in the flow chart in Figure 1.2. 

The flow chart in Figure 1.2, of course, does not show all the different combinations and

permutations; rather, it indicates the typical calculations for one case, and suggests the 

balance by dotted lines. Moving from left to right; initially historical data were obtained 

for each of three principal facility categories, pipelines, platforms, and wells. Pipelines 

were further subdivided among < 10 inch and >=10 inch diameter lines. Wells were

categorized in two ways: according to producing (production) wells and the drilling (D) 

of exploration and development wells. For each of the above facility subcategories, spill 

causes were analyzed for small, medium, large, huge, and significant spills, defined as 

follows:

ß Small (S) - 50 to 99 bbl

ß Medium (M) - 100 to 999 bbl

ß Large (L) - 1,000 to 9,999 bbl

ß Huge (H) - >= 10,000 bbl

ß Significant (SG) - >= 1,000 bbl

Significant spills, which are spills of 1,000 bbl or more (Large and Huge) are also 

identified. Fractional spill sizes were rounded up or down to the nearest whole number, 

with rounding up for any decimal ending in 5. For example, a spill of 99.5 bbl is taken as 

100 bbl; 99.42 is taken as 99 bbl.

In the interests of conciseness and clarity, the above main categories of spill sizes will 

generally be designated by either their name (small, medium, large, huge, significant) or, 

when space is limited, by their acronym (S, M, L, H, SG), in the balance of this report. 
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1.7

Figure 1.2 

Calculation Flow Chart

Fault Tree Analysis Hazard Scenarios Spill Occurrence

Spill Size

Frequency and Cause Arctic Spill Frequency Annual Annual 

Small Spill 50-99 bbl Shallow Water Depth <10 m Frequency

Medium Water Depth >=10<30 m Frequency per 109 bbl Produced

<10" Dia

Deep Water Depth >=30<60 m Spill Index 

Medium Spill 100-999 bbl LOF Average Frequency

Pipeline

Large Spill 1000-9999 bbl LOF Av Freq per 109

 bbl Produced

Huge Spill >= 10000 bbl LOF Average Spill Index

>=10" Dia

Small and Medium Spills Shallow Water Depth <10 m

Medium Water Depth >=10<30 m

Deep Water Depth >=30<60 m

Large and Huge Spills

Small and Medium Spills Shallow Water Depth <10 m

Large Spill Medium Water Depth >=10<30 m

Deep Water Depth >=30<60 m

Spill 10000-149999 bbl

Spill >=150000 bbl

Historical Data Analysis

Platform

Chukchi Sea

Non Arctic

Chukchi Sea

Facility

Development Well Drilling

Production Well

Exploration Well Drilling
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Next, in the frequency analysis utilizing fault trees, each of three representative water 

depth ranges was assessed as follows:

ß Shallow - < 10 meters

ß Medium - 10 to 29 meters

ß Deep - 30 to 60 meters

Although originally it was anticipated that ‘very deep’ water would be considered, it was 

found that none of the development scenarios anticipated by MMS for the Chukchi Sea 

extended beyond the 60-meter isobath. 

One principal future development scenario was defined for the Chukchi Sea, as well as a 

compatible non-Arctic (hypothetical) scenario. Each scenario was described for each year 

in its development history, from the year 2009 to the year 2044. The hypothetical nonArctic scenario was developed for comparative purposes on the assumption that it was 

located with the same facility distribution in a non-Arctic area. This permitted the 

comparison of the spill indicator results with and without the application of the fault tree 

analysis to account for Arctic effects. 

Finally, for each of the scenarios considered, four oil spill occurrence indicators were 

generated, as follows:

ß Oil spill frequency

ß Oil spill frequency per barrel produced

ß Spill index, which is the product of the oil spill frequency and the mean spill 

size (for the particular category under consideration)

ß Life of Field Indices

1.8 Outline of Report

Following this brief introductory chapter, Volume I of the final report addresses each of 

the principal tasks and subtasks in its logical sequence. Accordingly, Chapter 2 describes 

the historical data assimilation and analysis, Chapter 3 defines the future development 

scenario used, Chapter 4 discusses the fault tree analysis to obtain Arctic oil spill 

frequencies, while Chapter 5 summarizes the results of the oil spill occurrence indicator 

computations and their distributions. Chapter 6 summarizes conclusions and 

recommendations including a section on the benefits and shortcomings of the present 

study. Extensive references and bibliography are given in the References. 

The appendices given in Volume II form an integral part of the work for the reader who 

wishes to learn about background and calculation details. Accordingly, Appendix 1

summarizes the historical data assimilated and analyzed. Appendix 2 gives details of the 

fault tree analysis. Appendix 3 gives details on the future development scenario utilized 
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as a basis for the study. Appendix 4 gives a printout of all the calculation steps, including 

results, utilized in the development of the Arctic oil spill occurrence indicators using the 

Monte Carlo approach. Appendix 5 gives general conclusions and results. The 

appendices are provided in pdf format on a CD-ROM.
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2.1

CHAPTER 2

HISTORICAL DATA

2.1 Approaches to Historical Data

Historical data on offshore oil spills were utilized as a numerical starting point for 

predicting Arctic offshore oil spill characteristics. Because a statistical history on Arctic 

offshore oil spills does not exist, oil spill histories for temperate offshore locations were 

utilized. Although Arctic offshore exploration and production was started in the early 

1970s, operations have been sporadic, with very few spills, so that a statistical history 

cannot be generated.

The following data sets or databases were utilized:

(a) GOM OCS Pipeline Spills (1972-1999)

(b) GOM OCS Platform Spills (1972-1999)

(c) Oil Blowouts, Worldwide (1955-1995)

The above categories of data are discussed and summarized in Appendix 1. The contents 

of the balance of this chapter are restricted to the presentation and discussion of only 

those data sets utilized in the present study. 

2.2 Pipeline Oil Spill Data

The MMS database called PPL_REPAIRS was used as a basis for the assessment of 

subsea pipeline oil spills [2]. This database contains records of all reported spills in the 

GOM. The database was used to obtain spill records for spills of 50 bbl or more between 

January 1st, 1972 and December 31st, 1999. The 32 spills reported in this date range were 

further subdivided into volume, pipeline diameter, pipeline segment length, and pipeline 

segment depth ranges as summarized in Table 2.1. 

Next, 32 GOM OCS pipeline spill records were reviewed and analyzed for causal 

and spill size distributions. Table 2.2 shows the summary of the causal record 

information, while Table 2.3 summarizes the spill cause distributions for two spill size 

ranges (small and medium, large and huge). Finally, Table 2.4 gives the principal 

parameters of the spill population for pipelines. The “Historical” value is the historical 

average value from Table 2.1; the low value is the most common annual low value (0 

spills), and the high value is the approximate upper 90% confidence interval value. 
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Table 2.1

GOM OCS Pipeline Spills Statistics Summary (1972-1999)

(App. Table 1.3)

Spill 

Statistics Exposure Frequency

GOM OCS Pipeline Spills, Categorized 1972-99

Number 

of Spills km-years

Spills per

105

km-years

< 10" 16 105,336 15.1894

By Pipe Diameter *

>= 10" 16 81,847 19.5488

Small 50-99 bbl 6 187,183 3.2054

Medium 100 - 999 bbl 13 187,183 6.9451

Large 1000 - 9999 bbl 10 187,183 5.3424

By Spill Size

Huge >=10000 bbl 3 187,183 1.6027

Small 50-99 bbl 4 105,336 3.7974

Medium 100 - 999 bbl 7 105,336 6.6454

Large 1000 - 9999 bbl 4 105,336 3.7974

< 10"

Huge >=10000 bbl 1 105,336 0.9493

Small <100 bbl 2 81,847 2.4436

Medium 100 - 999 bbl 6 81,847 7.3308

Large 1000 - 9999 bbl 6 81,847 7.3308

By Diameter, 

By Spill Size

>= 10"

Huge >=10000 bbl 2 81,847 2.4436

*14 of the 32 records have both MIN_WATER_DEPTH and MAX_WATER_DEPTH set to "0".
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Table 2.2

Analysis of GOM OCS Pipeline Spill Data for Causal Distribution and Spill Size

(App.Table 1.1)

NUMBER

OF SPILLS SPILL SIZE

BBL CAUSE 

CLASSIFICATION

# OF 

SPILLS

1 2 3 4 5 6 7 8 9 10 S M L H SM LH

CORROSION 4 1 2 1 3 1

External 1 80 1 1

Internal 3 100 5000 414 2 1 2 1

THIRD PARTY IMPACT 16 2 5 6 3 7 9

Anchor Impact 10 19833 65 50 300 900 323 15576 2000 800 1211 2 4 2 2 6 4

Jackup Rig or Spud Barge 1 3200 1 1

Trawl/Fishing Net 5 4000 100 14423 4569 4533 1 3 1 1 4

OPERATION IMPACT 4 3 1 3 1

Rig Anchoring 1 50 1 1

Work Boat Anchoring 3 50 5100 50 2 1 2 1

MECHANICAL 2 2 2

Connection Failure 1 135 1 1

Material Failure 1 210 1 1

NATURAL HAZARD 4 1 1 2 2 2

Mud Slide 3 250 80 8212 1 1 1 2 1

Storm/ Hurricane 1 3500 1 1

ARCTIC

Ice Gouging

Strudel Scour

Upheaval Buckling

Thaw Settlement

Other

UNKNOWN 2 119 190 2 2

TOTALS 32 7 12 10 3 19 13
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Table 2.3

Distribution and Frequency of Historical Spills – Pipeline

(App. Table 1.2)

Small and Medium Spills

50-999 bbl

Large and Huge Spills

>=1000 bbl

CAUSE 

CLASSIFICATION HISTORICAL

DISTRIBUTION

%

NUMBER 

OF 

SPILLS

EXPOSURE

[km-years]

FREQUENCY

spill per

105km-year

HISTORICAL 

DISTRIBUTION

%

NUMBER 

OF 

SPILLS

EXPOSURE

[km-years]

FREQUENCY

spill per

105 km-year

CORROSION 15.79 3 1.6027 7.69 1 0.5342

External 5.26 1 0.5342

Internal 10.53 2 1.0685 7.69 1 0.5342

THIRD PARTY IMPACT 36.84 7 3.7397 69.23 9 4.8081

Anchor Impact 31.58 6 3.2054 30.77 4 2.1369

Jackup Rig or Spud Barge 7.69 1 0.5342

Trawl/Fishing Net 5.26 1 0.5342 30.77 4 2.1369

OPERATION IMPACT 15.79 3 1.6027 7.69 1 0.5342

Rig Anchoring 5.26 1 0.5342

Work Boat Anchoring 10.53 2 1.0685 7.69 1 0.5342

MECHANICAL 10.53 2 1.0685

Connection Failure 5.26 1 0.5342

Material Failure 5.26 1 0.5342

NATURAL HAZARD 10.53 2 1.0685 15.38 2 1.0685

Mud Slide 10.53 2 1.0685 7.69 1 0.5342

Storm/ Hurricane 7.69 1 0.5342

ARCTIC

Ice Gouging

Strudel Scour

Upheaval Buckling

Thaw Settlement

Other

UNKNOWN 10.53 2 1.0685

TOTALS 100.00 19

187183

10.1505 100.00 13

187183

6.9451

Table 2.4

Pipeline Historical Spill Frequency Variability

Frequency

spill per 105 km-years

GOM OCS Pipeline Spills,

Categorized 1972-99 Historical Low Mode High

By Diameter, By Spill Size

< 10” Small 3.7974 0 1.6329 9.7592

Medium 6.6454 0 2.8575 17.0786

Large 3.7974 0 1.6329 9.7592

Huge 0.9493 0 0.4082 2.4398

= 10" Small 2.4436 0 1.0507 6.2800

Medium 6.1090 0 2.6269 15.7001

Large 7.3308 0 3.1522 18.8401

Huge 2.4436 0 1.0507 6.2800
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For example, if there were 30 data points, the upper 90% (or high value) was the third 

highest, while the lower 90% (or low value) was selected as the third lowest, which was 

invariably zero, as numerous years had no spills. Next, the third highest value was 

divided by the historical value to get the high factor. Finally, the high factor was used to 

obtain the high value by multiplying the applicable historical frequency by this high 

factor. The mode was then calculated from the triangular distribution relationship [13], as 

follows:

Mode = 3 x Historical - High - Low (2.1)

2.3 Platform Spill Data

Platform spills in the MMS database are given for the period from 1972 to 1999 [2]. The 

platform spill data are given for an exposure of producing well-years. As for pipelines, 

the spill records themselves were accessed in order to obtain the correlation between spill 

cause and spill size. Table 2.5 shows the results of the causal and spill size distribution 

analysis, while Table 2.6 gives the causal distribution as well as the spill frequency per 

10,000 well-years. Finally, Table 2.7 gives the principal variability parameters of the spill 

population for platforms. The high values were chosen as the annual spill rates closest to 

the upper and lower 90% confidence interval, and calculated as described in Section 2.2; 

the low value is zero.

In order to assess spill occurrence from platform facilities, using the above per well-year 

frequency, it is necessary to estimate the number of wells per platform. For the Chukchi 

Sea scenario, there is only one platform to which all production wells were attributed as 

on-platform or subsea wells tied to the platform with umbilicals.

2.4 Oil Well Blowout Data

The development scenarios considered under this study include both the drilling of 

exploratory and development wells, and the production wells producing oil. To identify a

basis for the non-Arctic historical oil well blowout statistics, a number of sources were 

reviewed including the Northstar and Liberty oil development project reports [52], a 

study by ScanPower giving the cumulative distribution function for oil blowout releases 

[59], as well as the book by Per Holand entitled “Offshore Blowouts”, which gives risk 

analysis data from the SINTEF worldwide offshore blowout database [25]. The most 

comprehensive historical information was found in the latter reference [25], which not 

only gives the results of database analyses for the North Sea and the Gulf of Mexico, but 

also provides confidence intervals calculated from these databases. Table 2.8 gives a 

summary of the historical data analysis by Per Holland [25] for production wells and the

drilling of exploratory and development wells. The combination of these statistics 

together with the cumulative distribution function for oil blowout release volumes given 

in [59], generated in support of the Northstar project, permits the blowout spill volume 

frequency distribution as summarized in Table 2.9. Finally, combining the population 

parameters of oil well blowouts from Table 2.8 with the size distribution factors – which

can be derived from Table 2.9 – one arrives at the historical oil spill blowout distribution

characteristics by spill size and well type, summarized in Table 2.10.
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Table 2.5

Analysis of GOM OCS Platform Spill Data for Causal Distribution and Spill Size 

(1972-1999)

(App.Table 1.5)

NUMBER

OF SPILLS SPILL SIZE

BBL CAUSE 

CLASSIFICATION

# OF 

SPILLS

1 2 3 4 5 6 7 8 9 10 11 12 13 S M L H SM LH

PROCESS FACILITY RLS. 13 130 50 120 104 60 1456 125 50 50 55 400 280 75 6 6 1 12 1

STORAGE TANK RLS. 3 9935 7000 435 1 2 1 2

STRUCTURAL FAILURE 1 58 1 1

HURRICANE/STORM 2 75 66 2 2

COLLISION 2 600 108 2 2

TOTALS 21 9 9 3 18 3

Table 2.6

Causal and Spill Size Distribution of GOM OCS Platform Spills (1972-1999)

(App. Table 1.6)

Small and Medium Spills Large and Huge Spills

CAUSE 

CLASSIFICATION

HIST. 

DISTRIBUTION

(%)

# OF 

SPILLS

EXPOSURE

(well-yr)

FREQUENCY

(spill per

104 well-yr)

HIST. 

DISTRIBUTION

(%)

# OF 

SPILLS

EXPOSURE

(well-yr)

FREQUENCY

(spill per

104 well-yr)

PROCESS FACILITY RLS. 66.67 12 1.0024 33.33 1 0.0835

STORAGE TANK RLS. 5.56 1 0.0835 66.67 2 0.1671

STRUCTURAL FAILURE 5.56 1 0.0835

HURRICANE/STORM 11.11 2 0.1671

COLLISION 11.11 2 0.1671

TOTALS 100.00 18

119714

1.5036 100.00 3

119714

0.2506

Table 2.7

Platform Historical Spill Frequency Variability

Spill Size Frequency

Unit Historical Low Mode High

Small and Medium Spills

50-999 bbl spill per 104 well-year 1.5036 0.0000 0.1804 4.3303

Large and Huge Spills

>=1000 bbl spill per 104 well-year 0.2506 0.0000 0.0301 0.7217
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Table 2.8

Summary of North Sea and Gulf of Mexico Blowout Rates

(Holand, 1997)

Well Type Unit Low

90% CI Average High90% CI

Production Well Spills per 104

well-year

0.86 1.91 2.95

Exploration 

Well Drilling 11.00 25.05 51.00

Development 

Well Drilling

Spills per 104

wells

4.00 9.15 16.10

Table 2.9

Well Blowout Historical Spill Size Distribution

(ScanPower, 2001) (App. Table 1.8) Small and Medium Spills 50-999 bbl Large Spills 1000-9999 bbl Small, Medium, and Large Spills 50-9999 bbl

Spills 10000-149999 bblSpills >=150000 bblAll spills

EVENT

FREQUENCY UNIT

HISTORICAL FREQUENCY

PRODUCTION WELL

spills

per 104

well-year

0.15 1.03 1.18 0.44 0.29 1.91

EXPLORATION WELL

DRILLING

spills

per 104

wells

1.97 13.75 15.72 5.91 3.42 25.05

DEVELOPMENT 

WELL

DRILLING

spills

per 104

wells

0.65 4.57 5.22 1.96 1.96 9.15
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Table 2.10

Well Blowout Historical Spill Probability and Size Variability

(App. Table 1.9)

Frequencies

EVENT FREQUENCY

UNIT

Historical Low Mode High Low

Factor

High

Factor

Small and Medium Spills

50-999 bbl

PRODUCTION WELL spill per 104well-year 0.448 1.545 0.147 0.066 0.148 0.227

EXPLORATION WELL DRILLING spill per 104wells 0.439 2.036 1.966 0.863 1.032 4.002

DEVELOPMENT WELL DRILLING spill per 104wells 0.437 1.760 0.654 0.286 0.526 1.151

Large Spills

1000-9999 bbl

PRODUCTION WELL spill per 104well-year 0.448 1.545 1.028 0.460 1.037 1.588

EXPLORATION WELL DRILLING spill per 104wells 0.439 2.036 13.754 6.039 7.220 28.001

DEVELOPMENT WELL DRILLING spill per 104wells 0.437 1.760 4.570 1.998 3.671 8.041

Small, Medium and Large Spills

50-9999 bbl

PRODUCTION WELL spill per 104well-year 0.448 1.545 1.175 0.526 1.185 1.815

EXPLORATION WELL DRILLING spill per 104wells 0.439 2.036 15.719 6.903 8.252 32.003

DEVELOPMENT WELL DRILLING spill per 104wells 0.437 1.760 5.224 2.284 4.197 9.192

Spill 10000-149999 bbl

PRODUCTION WELL spill per 104well-year 0.448 1.545 0.441 0.197 0.444 0.681

EXPLORATION WELL DRILLING spill per 104wells 0.439 2.036 5.909 2.595 3.102 12.031

DEVELOPMENT WELL DRILLING spill per 104wells 0.437 1.760 1.963 0.858 1.577 3.454

Spill >=150000 bbl

PRODUCTION WELL spill per 104well-year 0.448 1.545 0.294 0.132 0.296 0.454

EXPLORATION WELL DRILLING spill per 104wells 0.439 2.036 3.421 1.502 1.796 6.965

DEVELOPMENT WELL DRILLING spill per 104wells 0.437 1.760 1.963 0.858 1.577 3.454
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2.5 Arctic Effects Historical Data

2.5.1 General Approaches to the Quantification of Arctic Effects

There are essentially two main categories of Arctic effects; namely, those that are unique 

to the Arctic, such as marine ice effects, and those that are the same types of effects as 

those in temperate areas, but occurring with a different frequency, such as anchor impacts 

on subsea pipelines. The first will be termed “unique” effects; the second, “modified” 

effects. Modified Arctic effects are dealt with in conjunction with the fault tree analysis 

described in Chapter 4. Only those Arctic effects or hazards unique to the Arctic, and 

potentially having a historical occurrence database, such as ice gouging, are discussed in 

the balance of this section. 

2.5.2 Ice Gouging

Ice gouging occurs when a moving ice feature contacts the sea bottom and penetrates into 

it, generally as it moves against a positive sea bottom slope. The ice feature can be a 

multiyear ridge, a hummock, or ice rafting formation. Various studies have been 

conducted on the frequency and depth distribution of ice gouges [8, 27, 29, 30, 46, 67, 

68], and a number of assessments of the likelihood of resultant subsea pipeline failure [8, 

29] have also been carried out. Pipeline failure frequencies at different water depth 

regimes as a result of ice gouging in this study have been estimated on the basis of the 

historical ice gouge characteristics [29] together with an analytical assessment [8, 68] of 

their likelihood to damage a pipeline. 

According to Weeks [67, 68], a relationship between the expected probability of pipeline 

failure from ice gouging and ice gouging local characteristics may be expressed as 

follows:

N = e-kx HS ? F ? T ? LP ? sin? (2.2)

Where:

N = Number of pipeline failures at burial depth of cover x (meters)

k = Inverse of mean scour depth (m-1)

x = Depth of cover (m)

HS = Probability of pipeline failure given ice gouge impact or hit

F = Scour flux per km-yr

T = Exposure time (years)

LP = Length of pipeline (km)

? = Gouge orientation (degrees) from pipeline centerline
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For the Northstar project, according to [30], the mean scour depth is 0.2 m giving a k

factor of 5.0. In addition, a good estimate of scour flux for shallow water is 2 gouges/kmyr. Using an average pipeline depth of cover of 2.5 m, an average directional angle of 

45°, a conditional failure probability (HS) of 0.83, gives a frequency of 5.26 x 10-6/km-yr. 

For the purposes of the ana lysis, this frequency must be distributed among different spill 

size consequences. Due to the difficulty of detecting spills under ice, one can expect that 

the majority of spills would be in the large and huge categories. However, huge spills 

would be limited by segment length. Thus, a conditional probability (given a spill) of 

50% has been assigned to large spills, and one of 14% to huge spills. Least likely are 

small spills, and accordingly they have been given a probability of 13%. The remaining 

probability of 23% has been assigned to medium sized spills. The resultant distribution of 

expected frequencies of spill sizes associated with ice gouging is given in Table 2.11. 

Also, high and low values have been assigned in order to permit an analysis of the likely 

distribution of the effects. Essentially, these variations in effect probability were obtained 

through a parametric sensitivity analysis using Equation 2.1 for a range of likely values 

of depth of cover from 2.0 m to 3.0 m (with an expected value of 2.5 m). These resultant 

low and high values are also summarized in Table 2.11. For medium water depth (10 to 

29 m), an analogous process was carried out with a reduced gouge flux of 1.5 gouges/kmyr. For deep water (>= 30 m) no gouging is expected.

2.5.3 Strudel Scour

When water collects on top of the landfast ice, generally from rivers running into the 

Arctic seas, and drains through a hole in the ice, its hydrodynamic effect on the ocean 

floor below forms a depression which is called a strudel scour. Numerous studies have 

been conducted on strudel scour [29, 30], so that a prediction on the number of strudel 

scours per unit area can be made on the basis of historical data. Strudel scours are 

restricted to shallow water. With an average strudel scour frequency of 4 scours/mi2 (1.5 

scours/km2) [30], the methodology in [30] can be utilized to predict a possible failure rate 

of subsea pipelines in shallow waters due to strudel scour of approximately 8.9 x 

10-8/km-yr. Using reasoning similar to that for the distribution of spill sizes for ice 

gouging, and assigning limits based on parametric sensitivity studies, the distribution of 

strudel scour frequencies for sha llow water as shown in Table 2.11 can be derived. 

Strudel scours are not expected in water depths greater than 10 m.
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Table 2.11

Summary of Pipeline Unique Arctic Effect Inputs

(App. Table 2.2)

Water Depth

Shallow Medium Deep

Frequency Increment per 105 km-year

Cause 

Classification

Spill 

Size

Min Mode Max Min Mode Max Min Mode Max

S 0.0060 0.0680 0.8290 0.0048 0.0544 0.6632

M 0.0090 0.1210 1.4670 0.0072 0.0968 1.1736

L 0.0210 0.2610 3.1900 0.0168 0.2088 2.5520

Ice Gouging

H 0.0060 0.0730 0.8930 0.0048 0.0584 0.7144

S 0.0004 0.0012 0.0044

M 0.0006 0.0020 0.0078

L 0.0014 0.0045 0.0170

Strudel Scour

H 0.0004 0.0012 0.0048

S 0.00007 0.00023 0.00088 0.00007 0.00023 0.00088 0.00007 0.00023 0.00088

M 0.00013 0.00041 0.00156 0.00013 0.00041 0.00156 0.00013 0.00041 0.00156

L 0.00028 0.00089 0.00340 0.00028 0.00089 0.00340 0.00028 0.00089 0.00340

Upheaval Buckling

H 0.00008 0.00025 0.00095 0.00008 0.00025 0.00095 0.00008 0.00025 0.00095

S 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000

M 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000

L 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000

Thaw Settlement

H 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000 0.00000

S 0.00162 0.01738 0.20869 0.00123 0.01369 0.16613 0.00003 0.00009 0.00033

M 0.00246 0.03092 0.36929 0.00185 0.02435 0.29399 0.00005 0.00015 0.00059

L 0.00571 0.06670 0.80303 0.00431 0.05253 0.63928 0.00011 0.00033 0.00128

Other

H 0.00163 0.01865 0.22480 0.00123 0.01469 0.17896 0.00003 0.00009 0.00036
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2.5.4 Upheaval Buckling

Upheaval buckling occurs in a pipeline as a result of its thermal expansion which causes 

it to buckle upwards to accommodate the extra length generated from thermal effects. 

Unfortunately, there appears to be no defensible analytical method for calculating the 

probability of upheaval buckling of Arctic subsea pipelines in general. Accordingly, 

upheaval buckling has been taken simply as a percentage of the strudel scour effects. 

Assuming that a upheaval buckling occurs 20% as often as strudel scour, the distribution 

shown in Table 2.9 can be derived. Upheaval buckling is expected to be independent of 

water depth; accordingly, the same values have been used for each water depth range.

2.5.5 Thaw Settlement

Thaw settlement occurs when a permafrost lens or formation over which the pipeline was 

installed melts as a result of the heat generated by the pipeline and ceases to support the 

pipeline so that the pipeline overburden loads the pipeline and causes it to deflect 

downwards. As there are no permafrost strata in the Chukchi study area, no thaw 

settlement is expected.

2.5.6 Platform Arctic Unique Effects

Potential causes of platform spills (other than blowouts, which are included under wells) 

that are uniquely associated with the Arctic are ice forces and low temperature effects. 

Although the possibility that ice forces will cause spills varies greatly from facility to 

facility, some broad assumptions have been made in regards to the likelihood of spills 

being caused by ice force effects. Specifically, it was assumed that the platforms are 

designed for a 10,000 year return period with a reliability level of 96%, in accordance 

with the Draft ISO WG8 Arctic Structures Reliability Section 7.2.2.3 [28]. That is, 4% of 

the time, the 10,000 year return period ice force can cause a spill. Further, it was assumed 

that 85% of spills so caused are small and medium, with large and huge spills associated 

with the other 15%. In regards to facility low temperature, a percentage of historical 

facility releases was taken. Specifically, it was assumed that the facility low temperature 

effects will cause medium spills at a rate of 6% of that of total historical small and 

medium spills, and large and huge spills at a rate of 3% of that associated with large and 

huge historical spills. Finally, other Arctic unique causes were assumed to constitute 

another 10% of the sum of the above spill rates in each of the spill categories. Table 2.12

summarizes the resultant Arctic unique effect frequencies derived for platforms on a perwell year basis. 
Chukchi Oil Spill Estimators Final Report – P2507

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2.13

Table 2.12

Summary of Platform Unique Arctic Effect Inputs

(App. Table 2.8)

FREQUENCY INCREMENT 

PER 104 well-year (Mode) CAUSE SPILL SIZE

Shallow Medium Deep

REASON

Small, Medium 0.0340 0.0510 0.0765

Ice Force

Large, Huge 0.0060 0.0090 0.0135

Assumed 10,000 year return period ice force 

causes spill 4% occurrences (96% 

reliability). 85% of the spills are 

Small/Medium.

Small, Medium 0.1000 0.1000 0.1000

Facility Low 

Temperature

Large, Huge 0.0080 0.0080 0.0080

Assumed fraction of Historical Process 

Facilities release frequency with 6% for 

Small/Medium and 3% for Large/Huge spill 

sizes.

Small, Medium 0.0134 0.0151 0.0177

Other

Large, Huge 0.0014 0.0017 0.0022

10% of sum of above.
Chukchi Oil Spill Estimators Final Report – P2507

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October, 2006

2.14

2.6 Historical Spill Size Distribution

Table 2.13 gives the historical spill size distributions obtained from the available 

historical data. Here, the mode was taken as the historical average spill size in each spill

size category, while the high and low values were taken to be the upper and lower bounds 

of each spill size category. The Huge spill high values were chosen on the basis of the 

upper 90% confidence interval spill volumes in the databases.

Table 2.13

Summary of Historical Spill Size Distribution Parameters

Spill Size Small Spills

(50-99 bbl)

Medium Spills

(100-999 bbl)

Large Spills

(1,000-9,999 bbl)

Huge Spills

(= 10,000 bbl)

Spill 

Expectation Low Mode High Low Mode High Low Mode High Low Mode High

Pipeline 

(Diameter <10”)

Spill

50 58 99 100 226 999 1000 4436 9999 10000 14423 20000

PIPELINE

SPILL 

VOLUMES

Pipeline

(Diameter >10”)

Spill

50 58 99 100 387 999 1000 3932 9999 10000 17705 20000

Spill Size Small and Medium Spills

(50-999 bbl)

Large and Huge Spills

(= 1,000 bbl)

Spill 

Expectation Low Mode High Low Mode High

PLATFORM

SPILL 

VOLUMES

Platform

Spill 50 158 999 1000 6130 10000

Spill Size Small and Medium Spills

(50-999 bbl)

Large Spills

(1,000-9,999 bbl)

Spills

(10,000-149,999 bbl)

Spills

(= 150,000 bbl)

Spill 

Expectation Low Mode High Low Mode High Low Mode High Low Mode High

WELL

SPILL 

VOLUMES

Well

Spill 50 500 999 1000 4500 9999 10000 20000 149999 150000 200000 250000
Chukchi Oil Spill Estimators 3.1 Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

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CHAPTER 3

FUTURE DEVELOPMENT SCENARIOS

3.1 Approaches to Future Development Scenarios

For the purposes of the fault tree analysis utilized in this study, future Chukchi Sea 

offshore oil and gas development scenarios need to include the following characteristics

for each year of the development scenario:

ß Water depth range for pipelines

ß Physical quantities of individual facilities (e.g., production wells, pipelines) on an 

annual basis in correspondence with the baseline data exposure factors (e.g., per 

well year or per km-yr)

ß Associated oil production volumes

ß Other characteristics such as pipeline diameter or type of well drilled

Table 3.1 shows the classification of development Scenarios by water depth range and

operation type. The salient aspect of this classification is subdivision into water depth 

ranges among which Arctic hazard characteristics (such as ice gouging rates) may 

change. The following water depth categories are used:

ß Shallow - < 10 meters

ß Medium - 10 to 29 meters

ß Deep - 30 to 60 meters

ß Very Deep - > 60 meters

In Table 3.1, an indication is given of the types of facilities that might be utilized in each 

of the principal types of oil and gas activities, exploration, production, or transportation. 

As will be seen in this chapter, current forecasts for development scenarios over the next 

40 years exclude very deep locations, in excess of 60 m. Accordingly, any suggestions 

for facilities under the very deep scenario would be speculative and will not be used in 

the current study. 

In general, the scenarios described in this chapter were developed to an appropriate level 

and type of detail to match the type of unit spill data and statistics available as a basis for 

the oil spill occurrence indicator quantification. 

The principal regions of interest within the study area are the Chukchi Sea lease areas.
Chukchi Oil Spill Estimators 3.2 Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

Table 3.1

Classification of Development Scenarios

WATER DEPTH

(m) PRINCIPAL 

ACTIVITY SHALLOW

(< 10)

MEDIUM

(10 to 29)

DEEP

(30 to 60)

VERY DEEP

(> 60)

EXPLORATION

ß Artificial island

ß Drill barge

ß Ice island

ß Artificial island

ß Drill ship (summer)

ß Caisson

ß Drill ship (summer)

ß Semisubmersible 

(summer)

ß Drill ship (summer)

ß Semisubmersible 

(summer)

PRODUCTION ß Artificial island

ß Caisson island

ß Caisson island

ß Gravity Base 

Structure (GBS)

ß Caisson island

ß Gravity Base 

Structure (GBS)

ß New design structure

ß Submarine habitat

TRANSPORT ß Subsea pipeline ß Subsea pipeline ß Subsea pipeline

ß Storage & tankers

ß Subsea pipeline

ß Submarine storage

ß Icebreaking tankers

ß Submarine tankers
Chukchi Oil Spill Estimators 3.3 Final Report – P2507

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October, 2006

3.2 Chukchi Sea Development Scenarios

As a basis for the current analysis, the geographic and water depth distribution of the 

facilities and its variation over the life of the development is required in order to 

effectively incorporate the effects of Arctic operations on the oil spill occurrences. Table 

3.2 summarizes the key quantity parameters of a possible Chukchi scenario. The facility 

quantities are hypothetical, and not based on any operator’s plan. No facilities are 

predicted in the very deep region. 

Table 3.3 summarizes the complete development scenario including its temporal 

development from 2009 to Year 2044, at which time it is forecast to cease production. 

For items such as exploration and field delineation well drilling, the actual number of 

wells drilled in a given year were needed, since the statistics of well spill (blowouts) are 

on a per well drilled exposure unit. For items that continue from year to year, such as 

production wells or subsea pipelines, both the annual incremental and the cumulative 

total are needed. Specifically, the following facility quantities were estimated and 

distributed as shown in Table 3.3:

ß Exploration wells drilled – annual

ß Delineation wells drilled – annual

ß Production platforms – only one platform was assumed

ß Production/service wells – annual increment and cumulative number

ß Pipeline lengths for < 10”, and >=10”, and total – annual increment and 

cumulative number of pipeline length in service

ß Oil production volumes – annual

As noted above, these quantities match the type of unit spill data that is available through 

the historical analysis. For example, we have spill data by pipeline diameter only for lines 

< and >=10”, so a full spectrum of pipeline diameters would be redundant. An important 

aspect of the information in Table 3.3, however, is the distribution of the facilities by 

water depth, as there is a significant variation in pipeline Arctic hazards by water depth.

It was assumed that the facility quantities vary in accordance with a uniform distribution. 

Table 3.4 shows the upper and lower limits, and the base or value of each annual quantity 

under consideration. Thus, for example, in the year 2020, the number of on platform

wells can range between 4 and 6.
Chukchi Oil Spill Estimators 3.4 Final Report – P2507

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Table 3.2

Summary of Exploration and Development Scenario, Chukchi Sea OCS

Scenario Element Range Comments

Oil production (Bbbl) 1 First development project only

Natural gas production 0 Delayed for North Slope gas line; reinjected

Exploration wells 3-6 2-5 wells are dry holes or sub -commercial shows

Delineation wells 4-8 Confirm and define the commercial discovery

Production platforms 1 Central platform with processing facility; supports

4-20 subsea satellite templates

Production wells 80-120 Total includes 20-80 subsea production wells

Service wells 20-40 All service wells are on platform

In-field flowlines (mi) 10-50 Gathering system from subsea wells

Offshore sales pipeline (mi) 30-150 Possible distance to landfall

Onshore sales pipeline (mi) Up to 300 Connecting to existing/future North Slope 

pipelines

Peak production (kBpd) 200-250 Oil production only. Associated gas is reinjected

New landfall 1 Point Belcher near Wainwright

New support shorebase 1 Point Belcher near Wainwright

New processing facility 1 Co-located with shorebase

New waste facility 1 Co-located with shorebase

Drilling fluid discharge by

exploration wells (tons) 665-1330 475 tons/well with 80% recycled for all expl anddelin wells (95 tons discharged for 7-14 wells)

Rock cutting discharge by

exploration wells (tons) 4200-8400 600 tons/well (7-14 wells total)

Discharges during development 

drilling 0

80% of drilling fluids are recycled; remaining 

waste fluids and rock cuttings for on-platform 

wells will be disposed of in service wells. Drilling 

wastes from subsea wells will be barged to an onshore disposal facility.

Years of activity 30-40 Period from lease sale to end of oil production
Chukchi Oil Spill Estimators 3.5 Final Report – P2507

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Table 3.3

Chukchi Sea Development Data (2009-2044)

(App. Table 3.1)

Well

Drilling In-use Pipeline Length [miles]

Production

Platforms

On Platform

Production

Wells

Subsea

Production

Wells

Total 

Production

Wells

Sum<10" Sum >=10" Sum All Year

Water

Depth

Exploration

Development

Incr. Cum. Incr. Cum. Incr. Cum. Incr. Cum. Incr. Cum. Incr. Cum. Incr. Cum.

Production

MMbbl

Shallow

Medium

Deep 1

2009

Total 1

Shallow

Medium

Deep 1

2010

Total 1

Shallow

Medium

Deep 2

2011

Total 2

Shallow

Medium

Deep 2

2012

Total 2

Shallow

Medium

Deep 2

2013

Total 2

Shallow

Medium

Deep 1

2014

Total 1

Shallow

Medium

Deep 1

2015

Total 1

Shallow

Medium

Deep 2016

Total

Shallow

Medium

Deep

2017

Total

Shallow

Medium

Deep

2018

Total

Shallow

Medium

Deep 6 6 6 6 6

2019

Total 6 6 6 6 6

Shallow

Medium 30 30 30 30

Deep 11 1 1 5 5 6 12 11 17 10 10 60 60 70 70 54.0

2020

Total 11 1 1 5 5 6 12 11 17 10 10 90 90 100 100 54.0
Chukchi Oil Spill Estimators 3.6 Final Report – P2507

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October, 2006

Table 3.3 ~ Continued ~

Well

Drilling In-use Pipeline Length [miles]

Production

Platforms

On Platform

Production

Wells

Subsea

Production

Wells

Total 

Production

Wells Sum<10" Sum >=10" Sum All

Year Water

Depth

Exploration

Development

Incr. Cum. Incr. Cum. Incr. Cum. Incr. Cum. Incr. Cum. Incr. Cum. Incr. Cum.

Production

MMbbl

Shallow

Medium 30 30

Deep 21 1 15 20 6 18 21 38 5 15 60 5 75 70.0 2021

Total 21 1 15 20 6 18 21 38 5 15 90 5 105 70.0

Shallow

Medium 30 30

Deep 21 1 15 35 6 24 21 59 5 20 60 5 80 82.0

2022

Total 21 1 15 35 6 24 21 59 5 20 90 5 110 82.0

Shallow

Medium 30 30

Deep 21 1 15 50 6 30 21 80 5 25 60 5 85 82.0 2023

Total 21 1 15 50 6 30 21 80 5 25 90 5 115 82.0

Shallow

Medium 30 30

Deep 12 1 6 56 6 36 12 92 5 30 60 5 90 82.0

2024

Total 12 1 6 56 6 36 12 92 5 30 90 5 120 82.0

Shallow

Medium 30 30

Deep 6 1 6 62 36 6 98 30 60 90 82.0

2025

Total 6 1 6 62 36 6 98 30 90 120 82.0

Shallow

Medium 30 30

Deep 1 62 36 98 30 60 90 72.2 2026

Total 1 62 36 98 30 90 120 72.2

Shallow

Medium 30 30

Deep 1 62 36 98 30 60 90 63.5

2027

Total 1 62 36 98 30 90 120 63.5

Shallow

Medium 30 30

Deep 1 62 36 98 30 60 90 55.9

2028

Total 1 62 36 98 30 90 120 55.9

Shallow

Medium 30 30

Deep 1 62 36 98 30 60 90 49.2 2029

Total 1 62 36 98 30 90 120 49.2

Shallow

Medium 30 30

Deep 1 62 36 98 30 60 90 43.3

2030

Total 1 62 36 98 30 90 120 43.3

Shallow

Medium 30 30

Deep 1 62 36 98 30 60 90 38.1

2031

Total 1 62 36 98 30 90 120 38.1

Shallow

Medium 30 30

Deep 1 62 36 98 30 60 90 33.5 2032

Total 1 62 36 98 30 90 120 33.5

Shallow

Medium 30 30

Deep 1 62 36 98 30 60 90 29.5

2033

Total 1 62 36 98 30 90 120 29.5
Chukchi Oil Spill Estimators 3.7 Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

Table 3.3 ~ Continued ~

Well

Drilling In-use Pipeline Length [miles]

Production

Platforms

On Platform

Production

Wells

Subsea

Production

Wells

Total 

Production

Wells Sum<10" Sum >=10" Sum All

Year Water

Depth

Exploration

Development

Incr. Cum. Incr. Cum. Incr. Cum. Incr. Cum. Incr. Cum. Incr. Cum. Incr. Cum.

Production

MMbbl

Shallow

Medium 30 30

Deep 1 62 36 98 30 60 90 26.0 2034

Total 1 62 36 98 30 90 120 26.0

Shallow

Medium 30 30

Deep 1 62 36 98 30 60 90 22.8

2035

Total 1 62 36 98 30 90 120 22.8

Shallow

Medium 30 30

Deep 1 62 36 98 30 60 90 20.1

2036

Total 1 62 36 98 30 90 120 20.1

Shallow

Medium 30 30

Deep 1 62 36 98 30 60 90 17.7 2037

Total 1 62 36 98 30 90 120 17.7

Shallow

Medium 30 30

Deep 1 62 36 98 30 60 90 15.6

2038

Total 1 62 36 98 30 90 120 15.6

Shallow

Medium 30 30

Deep 1 62 -6 30 -6 92 30 60 90 13.7

2039

Total 1 62 -6 30 -6 92 30 90 120 13.7

Shallow

Medium 30 30

Deep 1 -5 57 -6 24 -11 81 30 60 90 12.1 2040

Total 1 -5 57 -6 24 -11 81 30 90 120 12.1

Shallow

Medium 30 30

Deep 1 -15 42 -6 18 -21 60 30 60 90 10.6

2041

Total 1 -15 42 -6 18 -21 60 30 90 120 10.6

Shallow

Medium 30 30

Deep 1 -15 27 -6 12 -21 39 30 60 90 9.3

2042

Total 1 -15 27 -6 12 -21 39 30 90 120 9.3

Shallow

Medium 30 30

Deep 1 -15 12 -6 6 -21 18 30 60 90 8.2 2043

Total 1 -15 12 -6 6 -21 18 30 90 120 8.2

Shallow

Medium 30 30

Deep 1 -6 6 -6 -12 6 30 60 90 7.2

2044

Total 1 -6 6 -6 -12 6 30 90 120 7.2
Chukchi Oil Spill Estimators 3.8 Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

 October, 2006

Table 3.4

Chukchi Sea Development Parameter Ranges (2009-2044)

(App. Table 3.1A)

Well

Drilling

Production

Platforms

On Platform

Production

Wells

Subsea

Production

Wells

Total

Production

Wells

In-use Pipeline Length [miles]

Sum<10" Sum >=10" Sum All Range

Factor

Range

Factor

Range

Factor Range

Factor

Range

Factor

Range

Factor

Year Water

Depth

ExplorationDevelopment

Cum. Cum.

0.80 1.20

Unif.

Dist.

MD.

Cum.

0.80 1.20

Unif.

Dist.

MD.

Cum.

0.80 1.20

Unif.

Dist.

MD. Cum.

0.33 1.67

Unif.

Dist.

MD.

Cum.

0.33 1.67

Unif.

Dist.

MD.

Cum.

0.33 1.67

Unif.

Dist. 

MD.

Production

MMbbl

2009 Shallow

Medium

Deep 1

Total 1

2010 Shallow

Medium

Deep 1

Total 1

2011 Shallow

Medium

Deep 2

Total 2

2012 Shallow

Medium

Deep 2

Total 2

2013 Shallow

Medium

Deep 2

Total 2

2014 Shallow

Medium

Deep 1

Total 1

2015 Shallow

Medium

Deep 1

Total 1

2016 Shallow

Medium

Deep

Total

2017 Shallow

Medium

Deep

Total

2018 Shallow

Medium

Deep

Total
Chukchi Oil Spill Estimators 3.9 Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

 October, 2006

Table 3.4 ~ Continued ~

Well

Drilling

Production

Platforms

On Platform

Production

Wells

Subsea

Production

Wells

Total

Production

Wells

In-use Pipeline Length [miles]

Sum<10" Sum >=10" Sum All Range

Factor

Range

Factor

Range

Factor Range

Factor

Range

Factor

Range

Factor

Year Water

Depth

ExplorationDevelopment

Cum. Cum.

0.80 1.20

Unif.

Dist.

MD.

Cum.

0.80 1.20

Unif.

Dist.

MD.

Cum.

0.80 1.20

Unif.

Dist.

MD. Cum.

0.33 1.67

Unif.

Dist.

MD.

Cum.

0.33 1.67

Unif.

Dist.

MD.

Cum.

0.33 1.67

Unif.

Dist. 

MD.

Production

MMbbl

2019 Shallow

Medium

Deep 6 6 5 7 6 6 5 7 6

Total 6 6 5 7 6 6 5 7 6

2020 Shallow

Medium 30 10 50 30 30 10 50 30

Deep 11 1 5 4 6 5 12 10 14 12 17 14 20 17 10 3 17 10 60 20 100 60 70 23 117 70 54.0

Total 11 1 5 4 6 5 12 10 14 12 17 14 20 17 10 3 17 10 90 30 150 90 100 33 167 100 54.0

2021 Shallow

Medium 30 10 50 30 30 10 50 30

Deep 21 1 20 16 24 20 18 14 22 18 38 30 46 38 15 5 25 15 60 20 100 60 75 25 125 75 70.0

Total 21 1 20 16 24 20 18 14 22 18 38 30 46 38 15 5 25 15 90 30 150 90 105 35 175 105 70.0

2022 Shallow

Medium 30 10 50 30 30 10 50 30

Deep 21 1 35 28 42 35 24 19 29 24 59 47 71 59 20 7 33 20 60 20 100 60 80 26 134 80 82.0

Total 21 1 35 28 42 35 24 19 29 24 59 47 71 59 20 7 33 20 90 30 150 90 110 36 184 110 82.0

2023 Shallow

Medium 30 10 50 30 30 10 50 30

Deep 21 1 50 40 60 50 30 24 36 30 80 64 96 80 25 8 42 25 60 20 100 60 85 28 142 85 82.0

Total 21 1 50 40 60 50 30 24 36 30 80 64 96 80 25 8 42 25 90 30 150 90 115 38 192 115 82.0

2024 Shallow

Medium 30 10 50 30 30 10 50 30

Deep 12 1 56 45 67 56 36 29 43 36 92 74 110 92 30 10 50 30 60 20 100 60 90 30 150 90 82.0

Total 12 1 56 45 67 56 36 29 43 36 92 74 110 92 30 10 50 30 90 30 150 90 120 40 200 120 82.0

2025 Shallow

Medium 30 10 50 30 30 10 50 30

Deep 6 1 62 50 74 62 36 29 43 36 98 78 118 98 30 10 50 30 60 20 100 60 90 30 150 90 82.0

Total 6 1 62 50 74 62 36 29 43 36 98 78 118 98 30 10 50 30 90 30 150 90 120 40 200 120 82.0

2026 Shallow

Medium 30 10 50 30 30 10 50 30

Deep 1 62 50 74 62 36 29 43 36 98 78 118 98 30 10 50 30 60 20 100 60 90 30 150 90 72.2

Total 1 62 50 74 62 36 29 43 36 98 78 118 98 30 10 50 30 90 30 150 90 120 40 200 120 72.2

2027 Shallow

Medium 30 10 50 30 30 10 50 30

Deep 1 62 50 74 62 36 29 43 36 98 78 118 98 30 10 50 30 60 20 100 60 90 30 150 90 63.5

Total 1 62 50 74 62 36 29 43 36 98 78 118 98 30 10 50 30 90 30 150 90 120 40 200 120 63.5

2028 Shallow

Medium 30 10 50 30 30 10 50 30

Deep 1 62 50 74 62 36 29 43 36 98 78 118 98 30 10 50 30 60 20 100 60 90 30 150 90 55.9

Total 1 62 50 74 62 36 29 43 36 98 78 118 98 30 10 50 30 90 30 150 90 120 40 200 120 55.9

2029 Shallow

Medium 30 10 50 30 30 10 50 30

Deep 1 62 50 74 62 36 29 43 36 98 78 118 98 30 10 50 30 60 20 100 60 90 30 150 90 49.2

Total 1 62 50 74 62 36 29 43 36 98 78 118 98 30 10 50 30 90 30 150 90 120 40 200 120 49.2

2030 Shallow
Chukchi Oil Spill Estimators 3.10 Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

 October, 2006

Table 3.4 ~ Continued ~

Well

Drilling

Production

Platforms

On Platform

Production

Wells

Subsea

Production

Wells

Total

Production

Wells

In-use Pipeline Length [miles]

Sum<10" Sum >=10" Sum All Range

Factor

Range

Factor

Range

Factor Range

Factor

Range

Factor

Range

Factor

Year Water

Depth

ExplorationDevelopment

Cum. Cum.

0.80 1.20

Unif.

Dist.

MD.

Cum.

0.80 1.20

Unif.

Dist.

MD.

Cum.

0.80 1.20

Unif.

Dist.

MD. Cum.

0.33 1.67

Unif.

Dist.

MD.

Cum.

0.33 1.67

Unif.

Dist.

MD.

Cum.

0.33 1.67

Unif.

Dist. 

MD.

Production

MMbbl

Medium 30 10 50 30 30 10 50 30

Deep 1 62 50 74 62 36 29 43 36 98 78 118 98 30 10 50 30 60 20 100 60 90 30 150 90 43.3

Total 1 62 50 74 62 36 29 43 36 98 78 118 98 30 10 50 30 90 30 150 90 120 40 200 120 43.3

2031 Shallow

Medium 30 10 50 30 30 10 50 30

Deep 1 62 50 74 62 36 29 43 36 98 78 118 98 30 10 50 30 60 20 100 60 90 30 150 90 38.1

Total 1 62 50 74 62 36 29 43 36 98 78 118 98 30 10 50 30 90 30 150 90 120 40 200 120 38.1

2032 Shallow

Medium 30 10 50 30 30 10 50 30

Deep 1 62 50 74 62 36 29 43 36 98 78 118 98 30 10 50 30 60 20 100 60 90 30 150 90 33.5

Total 1 62 50 74 62 36 29 43 36 98 78 118 98 30 10 50 30 90 30 150 90 120 40 200 120 33.5

2033 Shallow

Medium 30 10 50 30 30 10 50 30

Deep 1 62 50 74 62 36 29 43 36 98 78 118 98 30 10 50 30 60 20 100 60 90 30 150 90 29.5

Total 1 62 50 74 62 36 29 43 36 98 78 118 98 30 10 50 30 90 30 150 90 120 40 200 120 29.5

2034 Shallow

Medium 30 10 50 30 30 10 50 30

Deep 1 62 50 74 62 36 29 43 36 98 78 118 98 30 10 50 30 60 20 100 60 90 30 150 90 26.0

Total 1 62 50 74 62 36 29 43 36 98 78 118 98 30 10 50 30 90 30 150 90 120 40 200 120 26.0

2035 Shallow

Medium 30 10 50 30 30 10 50 30

Deep 1 62 50 74 62 36 29 43 36 98 78 118 98 30 10 50 30 60 20 100 60 90 30 150 90 22.8

Total 1 62 50 74 62 36 29 43 36 98 78 118 98 30 10 50 30 90 30 150 90 120 40 200 120 22.8

2036 Shallow

Medium 30 10 50 30 30 10 50 30

Deep 1 62 50 74 62 36 29 43 36 98 78 118 98 30 10 50 30 60 20 100 60 90 30 150 90 20.1

Total 1 62 50 74 62 36 29 43 36 98 78 118 98 30 10 50 30 90 30 150 90 120 40 200 120 20.1

2037 Shallow

Medium 30 10 50 30 30 10 50 30

Deep 1 62 50 74 62 36 29 43 36 98 78 118 98 30 10 50 30 60 20 100 60 90 30 150 90 17.7

Total 1 62 50 74 62 36 29 43 36 98 78 118 98 30 10 50 30 90 30 150 90 120 40 200 120 17.7

2038 Shallow

Medium 30 10 50 30 30 10 50 30

Deep 1 62 50 74 62 36 29 43 36 98 78 118 98 30 10 50 30 60 20 100 60 90 30 150 90 15.6

Total 1 62 50 74 62 36 29 43 36 98 78 118 98 30 10 50 30 90 30 150 90 120 40 200 120 15.6

2039 Shallow

Medium 30 10 50 30 30 10 50 30

Deep 1 62 50 74 62 30 24 36 30 92 74 110 92 30 10 50 30 60 20 100 60 90 30 150 90 13.7

Total 1 62 50 74 62 30 24 36 30 92 74 110 92 30 10 50 30 90 30 150 90 120 40 200 120 13.7

2040 Shallow

Medium 30 10 50 30 30 10 50 30

Deep 1 57 46 68 57 24 19 29 24 81 65 97 81 30 10 50 30 60 20 100 60 90 30 150 90 12.1

Total 1 57 46 68 57 24 19 29 24 81 65 97 81 30 10 50 30 90 30 150 90 120 40 200 120 12.1

2041 Shallow

Medium 30 10 50 30 30 10 50 30

Deep 1 42 34 50 42 18 14 22 18 60 48 72 60 30 10 50 30 60 20 100 60 90 30 150 90 10.6
Chukchi Oil Spill Estimators 3.11 Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

 October, 2006

Table 3.4 ~ Continued ~

Well

Drilling

Production

Platforms

On Platform

Production

Wells

Subsea

Production

Wells

Total

Production

Wells

In-use Pipeline Length [miles]

Sum<10" Sum >=10" Sum All Range

Factor

Range

Factor

Range

Factor Range

Factor

Range

Factor

Range

Factor

Year Water

Depth

ExplorationDevelopment

Cum. Cum.

0.80 1.20

Unif.

Dist.

MD.

Cum.

0.80 1.20

Unif.

Dist.

MD.

Cum.

0.80 1.20

Unif.

Dist.

MD. Cum.

0.33 1.67

Unif.

Dist.

MD.

Cum.

0.33 1.67

Unif.

Dist.

MD.

Cum.

0.33 1.67

Unif.

Dist. 

MD.

Production

MMbbl

Total 1 42 34 50 42 18 14 22 18 60 48 72 60 30 10 50 30 90 30 150 90 120 40 200 120 10.6

2042 Shallow

Medium 30 10 50 30 30 10 50 30

Deep 1 27 22 32 27 12 10 14 12 39 31 47 39 30 10 50 30 60 20 100 60 90 30 150 90 9.3

Total 1 27 22 32 27 12 10 14 12 39 31 47 39 30 10 50 30 90 30 150 90 120 40 200 120 9.3

2043 Shallow

Medium 30 10 50 30 30 10 50 30

Deep 1 12 10 14 12 6 5 7 6 18 14 22 18 30 10 50 30 60 20 100 60 90 30 150 90 8.2

Total 1 12 10 14 12 6 5 7 6 18 14 22 18 30 10 50 30 90 30 150 90 120 40 200 120 8.2

2044 Shallow

Medium 30 10 50 30 30 10 50 30

Deep 1 6 5 7 6 6 5 7 6 30 10 50 30 60 20 100 60 90 30 150 90 7.2

Total 1 6 5 7 6 6 5 7 6 30 10 50 30 90 30 150 90 120 40 200 120 7.2
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4.1

CHAPTER 4

FAULT TREE ANALYSIS FOR

ARCTIC OIL SPILL FREQUENCIES

4.1 General Description of Fault Tree Analysis

Fault trees are a method for modeling the occurrence of failures. They are used when an 

adequate history to provide failure statistics is not available. Developed initially by 

Rasmussen for the US Nuclear Regulatory Commission in the early 1970s [65, 51], fault 

trees have become a popular risk analytic tool for predicting risks, assessing relative 

risks, and quantifying comparative risks [7, 9, 14, 15, 18, 23, 26, 45]. In 1976, we first 

used fault trees to quantify oil spill probabilities in the Canadian Beaufort Sea for the 

Canadian Department of the Environment [10, 11]. In the present study they are used for 

the transformation of historical oil spill statistics for non-Arctic regions to predictive oil 

spill statistics for Arctic regions in the study area. 

4.2 Fault Tree Methodology

4.2.1 Fault Tree Analysis Basics

The basic symbols used in the graphic depiction of simple (as used here) fault tree 

networks are illustrated in Figure 4.1(a). As may be seen, the two types of symbols 

designate logic gates and event types. The basic fault tree building blocks are the events 

and associated sub-events, which form a causal network. The elements linking events are 

the AND and OR gates, which define the logical relationship among events in the 

network. The output event from an OR gate occurs if any one or more of the input events 

to the gate occurs. The output event from an AND gate occurs only if all the input events 

occur simultaneously.

The basic structure of a fault tree is illustrated in Figure 4.1(b). Because of their 

connection through an AND gate, Event D and Event E must both occur for the resultant 

Event B to occur. An OR gate connects Events B and C; therefore, the occurrence of 

either one or both of Events B and C results in the occurrence of the resultant Event A. 

As may be seen, the principal fault tree structures are easy to apply; however, the 

representation of complex problems often requires very large fault trees, which become 

more difficult to analyze and require more advanced techniques such as minimal cut-set 

analysis [2, 14, 18, 23, 51]. For the present application, a simple system connected 

through OR gates only will used.
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SYMBOL DESCRIPTION

A. LOGIC

EITHER / OR GATE

AND GATE

B. EVENT

RESULTANT EVENT

BASIC EVENT

(a) Basic Fault Tree Symbols

(b) Basic Fault Tree Structure

Figure 4.1

Fault Tree Basics
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Computationally, the probability of input events joined through an AND gate are 

multiplied to calculate the probabilities of the output event. The probabilities of input 

events joined through an OR gate are added to calculate the probability of the output 

event. The relevant equations and associated assumptions may be summarized as follows:

For AND Gate: (4.1a)

Example: Output Event Probability = Px

Input Events failure probabilities, P1, P2, ....

(4.1b)

For OR Gate: (4.2a)

Example: Output Event Probability = Py

Input Event failure probabilities, P1, P2, ...

(4.2b)

In more complex fault trees, it is necessary to assure that base events which affect more 

than one fault tree branch are not numerically duplicated. This is done through the use of 

minimal cut-set theory [14, 18, 23, 51]. However, as indicated earlier, the fault trees used 

in this study are sufficiently simple in structure and level of detail to exclude the 

requirement of using minimal cut-set theory in their computation algorithms.

4.2.2 Current Application of Fault Trees

Figure 4.2 illustrates a two-tier fault tree that can be used to develop pipeline large spill 

frequencies for the Arctic study area from the historical frequencies. Note that this 

example is illustrative of the process only, and does not correspond to the same numerical 

values used in computations later. The type of fault tree shown, to be used extensively 

later, is a relatively simple fault tree showing the resultant event, the spill, generated from 

a series of subresultant events corresponding to the pipeline spill causal classification, 

such as that shown in Table 2.3. The upper tier of numbers (marked “H”) below each of 

the events in the fault tree represents the historical frequency (per 100,000 km-yr) while 

the lower one (marked “A”) represents the modified frequency for Arctic operations. As 

these fault trees are composed entirely of OR gates, the computation of resultant events is 

quite simple – consisting of the addition of the probabilities of events at each level of the 

fault tree to obtain the resultant probability at the next higher value.

i

i

n

P P

=1

= Π

( )( ) Px = P1 P2 P3

1 (1 )

1

i

i

n

P = − Π − P

=

1 (1 )(1 )(1 ) P P1 P2 P3

n

y = −Π − − −

; 0.1 Py = P1 + P2 + P3for Pi ≤
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4.4

Figure 4.2

Example of Fault Tree to Transform Historical (GOM) to Arctic Spill Frequencies

1

1 The input data used here are only illustrative and do not represent the inputs used later in this study.
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For example, to obtain the “Natural Hazard” Arctic (“A”) probability of 0.151, add 0.043 

and 0.108. Essentially, the fault tree resultant (top event) shows that the Arctic frequency 

of spills (for the example pipeline category, location, and spill size) is approximately 1 in 

100,000 km-yr or 1.015 x 10-5/km-yr. The non-Arctic historical frequency for this spill 

size, by comparison, is 2.799 x 10-5/km-yr, or approximately 2.8 times higher. Both 

frequencies are for illustrative purposes only.

4.2.3 Monte Carlo Simulation

A type of numerical simulation, called Monte Carlo simulation [9] can be used to obtain 

the outcome of a set of interactions for equations in which the independent variables are 

described by distributions of any arbitrary form. The Monte Carlo simulation is a 

systematic method for selecting values from each of the independent variable 

distributions and computing all valid combinations of these values to obtain the 

distribution of the dependent variable. Naturally, this is done utilizing a computer, so that 

thousands of combinations can be rapidly computed and assembled to give the output 

distribution. 

Consider the example of the following equation:

X = X1 + X2 (4.3)

Where X is the dependent variable (such as the resultant spill frequency) and X1 and X2

are base event probabilities joined through an “and” gate. Suppose now that X1 and X2

are some arbitrary distributions that can be described by a collection of values x1 and x2. 

What we do in the Monte Carlo process, figuratively, is to put the collection of the X1

values into one hat, the X1 hat, and the same for the X2 values – into an X2 hat. We then 

randomly draw one value from each of the hats and compute the resultant value of the 

dependent variable, X, using equation 4.3. This is done several thousand times. Thus, a 

resultant or dependent variable distribution, X, is estimated from the computations of all 

valid combinations of the independent variables (X1 and X2). 

Generally, the resultant can be viewed as a cumulative distribution function as illustrated 

in Figure 4.3. Such a cumulative distribution function (CDF) is also a measure of the

accuracy or, conversely, the variance of the distribution. As can be seen from this figure, 

if the distribution is a vertical line, no matter where one draws on the vertical axis, the 

same value of the variable will result – that is, the variable is a constant. At the other 

extreme, if the variable is completely random then the distribution will be represented as 

a diagonal straight line between the minimum and maximum value. Intermediate 

qualitative descriptions of the randomness of the variable follow from inspection of the 

CDF in Figure 4.3.
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Figure 4.3

Monte Carlo Technique Schematic
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There are two other important concepts related to the CDF enter into Monte Carlo 

modeling: auto-correlation and cross-correlation. Suppose the variables X1 can vary only 

within a specified interval over the simulation time increment. Then, after the first 

random draw, the next draw would be restricted within certain limits of the initial draw 

simply as a result of the physical restrictions of the problem. Such a restriction is 

represented as an auto-correlation coefficient. Now, suppose that not only are the X1

restricted, but also the X2. Suppose further, however, that given a certain X1, a restriction 

were placed on the range of X2 associated with that X1. Say, only small X1 could 

associate with the full range of X2, while large X1 could only be associated with certain 

lower X2. Then, such a relationship would be expressed as a cross-correlation factor and 

certain limits would be imposed for the drawing on both X1 and associated X2. In the 

present analysis, all distributed variables are considered to be independent – so that auto 

and cross-correlations need not be invoked.

4.2.4 Distribution Derived from Historical Data for Monte Carlo Analysis

In order to model the variability of the base data and its distribution through the Arctic 

effects, using the Monte Carlo approach, an appropriate distribution needs to be derived. 

As in the previous study [12], a Triangular Distribution was selected. 

According to [13], the Triangular Distribution is typically used as a descriptor of a 

population for which there is only limited sample data, as is the current case. The 

distribution is based on a knowledge of a minimum and maximum, which was derived 

from the historical data here, and an educated guess as to what the modal value might be. 

Here, the modal value was chosen to be a function of the average historical value, as 

given in Equation 2.1. Despite being a simplistic description of a population, the 

Triangular Distribution is a very useful one for modeling processes where the relationship 

between variables is understood, but data are scarce. 

Also, when combining several variables in a functional relationship utilizing numerical 

methods, as is done in Monte Carlo Simulation, the Triangular Distribution is a preferred 

one due to its simplicity and relatively accurate probabilistic resultant when evaluated by 

a large number of random draws, as occurs in the Monte Carlo process. The data used 

here typifies sparse data with a preferred or modal value and an easily identifiable 

maximum and minimum. Then, for the case of the simple upper and lower 100% 

confidence interval (called High and Low), the expected value E (or mean value) of the 

Triangular Distribution can be expressed as:

E = (High + Mode + Low) / 3 (4.4)

For maximum and minimum which are not at the 100% confidence interval level – such 

as those at 90% confidence levels – a Monte Carlo computation is used to evaluate the 

expected value of each distribution, giving results somewhat different from Equation 4.4. 

Based on the historical data earlier presented in Tables 2.4, 2.7, and 2.10, the Triangular 

Distribution expected value computed from the low, mode, and high values at 90% 

confidence intervals are given in Tables 4.1, 4.2, and 4.3, for pipelines, platforms, and 

wells respectively. The high and low values were calculated as described in Section 2.2.
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4.8

Table 4.1

Pipeline Spill Frequency Triangular Distribution Properties

(App. Table 1.4)

Frequency

spill per 105 km-years

GOM OCS 

Pipeline Spills,

Categorized

1972-99

Low

Factor

High

Factor

Historical Low Mode High Expected

By Diameter, By Spill Size

Small 0 2.57 3.7974 0 1.6329 9.7592 5.1720

Medium 0 2.57 6.6454 0 2.8575 17.0786 9.0510

Large 0 2.57 3.7974 0 1.6329 9.7592 5.1720

<10”

Huge 0 2.57 0.9493 0 0.4082 2.4398 1.2930

Small 0 2.57 2.4436 0 1.0507 6.2800 3.3282

Medium 0 2.57 6.1090 0 2.6269 15.7001 8.3205

Large 0 2.57 7.3308 0 3.1522 18.8401 9.9846

=>10"

Huge 0 2.57 2.4436 0 1.0507 6.2800 3.3282

Table 4.2

Platform Spill Frequency Triangular Distribution Properties

(App. Table 1.7)

Spill Size Frequency

Unit

Low

Factor

High

Factor Historical Low Mode High Expected

Small and Medium Spills

50-999 bbl spill per 104 well-year 0 2.88 1.5036 0.0000 0.1804 4.3303 2.1571

Large and Huge Spills

=>1000 bbl spill per 104 well-year 0 2.88 0.2506 0.0000 0.0301 0.7217 0.3595
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Table 4.3

Well Blowout Frequency Triangular Distribution Properties

(App. Table 1.9)

Frequencies

EVENT FREQUENCY

UNIT

Historical Low Mode High Expected Low

Factor

High

Factor

Small and Med ium Spills

50-999 bbl

PRODUCTION WELL spill per 104well-year 0.448 1.545 0.147 0.066 0.148 0.227 0.147

EXPLORATION WELL DRILLING spill per 104wells 0.439 2.036 1.966 0.863 1.032 4.002 2.262

DEVELOPMENT WELL DRILLING spill per 104wells 0.437 1.760 0.654 0.286 0.526 1.151 0.692

Large Spills

1000-9999 bbl

PRODUCTION WELL spill per 104well-year 0.448 1.545 1.028 0.460 1.037 1.588 1.026

EXPLORATION WELL DRILLING spill per 104wells 0.439 2.036 13.754 6.039 7.220 28.001 15.824

DEVELOPMENT WELL DR ILLING spill per 104wells 0.437 1.760 4.570 1.998 3.671 8.041 4.833

Small, Medium and Large Spills

50-9999 bbl

PRODUCTION WELL spill per 104well-year 0.448 1.545 1.175 0.526 1.185 1.815 1.173

EXPLORATION WELL DRILLING spill per 104wells 0.439 2.036 15.719 6.903 8.252 32.003 18.086

DEVELOPMENT WELL DRILLING spill per 104wells 0.437 1.760 5.224 2.284 4.197 9.192 5.525

Spill 10000-149999 bbl

PRODUCTION WELL spill per 104well-year 0.448 1.545 0.441 0.197 0.444 0.681 0.440

EXPLORATION WELL DRILLING spill per 104wells 0.439 2.036 5.909 2.595 3.102 12.031 6.799

DEVELOPMENT WELL DRILLING spill per 104wells 0.437 1.760 1.963 0.858 1.577 3.454 2.076

Spill =>150000 bbl

PRODUCTION WELL spill per 104well-year 0.448 1.545 0.294 0.132 0.296 0.454 0.293

EXPLORATION WELL DRILLING spill per 104wells 0.439 2.036 3.421 1.502 1.796 6.965 3.936

DEVELOPMENT WELL DRILLING spill per 104wells 0.437 1.760 1.963 0.858 1.577 3.454 2.076
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4.2.5 Approaches to Assessment of Arctic Spill Frequency Variability

The method for assessment of Arctic spill frequency variability consists of systematically 

perturbing the variability of all the causal events, plus that of the Arctic unique effects. In 

this approach, the non-Arctic variable distribution is multiplied by an adjustment or 

correction distribution to obtain the Arctic variable distribution. 

4.3 Pipeline Fault Tree Analysis

4.3.1 Arctic Pipeline Spill Causal Frequency Distributions

The effects of the Arctic environment and operations are reflected in the effect on facility 

failure rates in two ways; namely, through “Modified Effects”, those changing the 

frequency component of certain fault contributions such as anchor impacts which are 

common to both Arctic and temperate zones, and through “Unique Effects” or additive 

elements such as ice gouging which are unique to the Arctic offshore environment. Table 

4.4 shows the frequency modifications (in %) and frequency increment additions (per 105

km-yr)developed for Arctic pipelines for different spill sizes throughout the three 

relevant water depth ranges. The right hand column of the table gives a summary of the 

reasoning behind the effects. For the Arctic unique effects, both the expected value (from 

Table 2.9) and the median value, determined through the Monte Carlo analysis, are given. 

The median values differ from the expected values due to skewness of the distributions 

introduced through the assigned values of the upper and lower bounds (Table 2.9). The 

following comments can be made for each of the causes described:

ß External corrosion – Due to the low temperature, limited biological and lowered 

chemical effects are expected. Coatings will be state of art and high level of quality 

control will be used during pipeline installation resulting in high integrity levels of 

coating to prevent external corrosion.

ß Internal corrosion – Additional (above historical levels) inspection or smart pigging 

is anticipated.

ß Anchor impact – The very low traffic densities of third party shipping in the area 

justify a 50% reduction in anchor impact expectations on the pipeline.

ß Jack-up rig or spud barges – Associated or other operations are going to be 

substantially more limited than they are in the historical data population in the Gulf of 

Mexico.

ß Trawl/Fishing net – Very limited fishing is expected in the Chukchi Sea. 
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Table 4.4

Pipeline Arctic Effect Derivation Summary

(App. Table 2.1)

Shallow Medium Deep CAUSE

CLASSIFICATION Spill Size Historical Expected Frequency 

Change %

Reason

CORROSION

External All (30) (30) (30) Low temperature and bio effects. Extra smart pigging.

Internal All (30) (30) (30) Extra smart pigging.

THIRD PARTY IMPACT

Anchor Impact All (50) (50) (50) Low traffic.

Jackup Rig or Spud Barge All (50) (50) (50) Low facility density.

Trawl/Fishing Net All (50) (60) (70) Low fishing activity. Less bottom fishing in deeper water.

OPERATION IMPACT

Rig Anchoring All (20) (20) (20) Low marine traffic during ice season (8 months).

Work Boat Anchoring All (20) (20) (20) Low work boat traffic during ice season (8 months). 

MECHANICAL

Connection Failure All

Material Failure All

NATURAL HAZARD

Mud Slide All (60) (50) (40) Gradient low. Mud slide potential (gradient) increases with water depth.

Storm/ Hurricane All (50) (50) (50) Fewer severe storms.

Freq. Increment

per 105 km-year

Expected Expected Expected

Mode Mode Mode

ARCTIC

0.3495 0.2796 S

0.0680 0.0544 

0.6178 0.4943 M

0.1210 0.0968 

1.3438 1.0750 L

0.2610 0.2088 

0.3762 0.3010 

Ice Gouging

H

0.0730 0.0584 

Ice gouge failure rate calculated using exponential failure distribution for 

2.5-m cover, 0.2-m average gouge depth, 2 gouges per km-yr flux. Spill 

size Distribution explained in text Section 2.5.2. Medium depth has 0.8 as 

many gouges as shallow.

0.0021 S

0.0012 

0.0038 M

0.0020 

0.0082 L

0.0045 

0.0023 

Strudel Scour

H

0.0012 

Only in shallow water. Average frequency of 4 scours/mile2 and 100 ft of 

bridge length with 10% conditional Pipelines failure probability. The same 

spill size distribution as above.

0.0004 0.0004 0.0004 S

0.0002 0.0002 0.0002 

0.0008 0.0008 0.0008 M

0.0004 0.0004 0.0004 

0.0016 0.0016 0.0016 L

0.0009 0.0009 0.0009 

0.0005 0.0005 0.0005 

Upheaval Buckling

H

0.0002 0.0002 0.0002 

All water depth. The failure frequency is 20% of that of Strudel Scour.

0.0002 0.0002 0.0002 S

0.0001 0.0001 0.0001 

0.0004 0.0004 0.0004 M

0.0002 0.0002 0.0002 

0.0008 0.0008 0.0008 L

0.0004 0.0004 0.0004 

0.0002 0.0002 0.0002 

Thaw Settlement

H

0.0001 0.0001 0.0001 

All water depth. The failure frequency is 10% of that of Strudel Scour.

0.0881 0.0701 0.0002 S

0.0174 0.0137 0.0001 

0.1557 0.1238 0.0003 M

0.0309 0.0244 0.0002 

0.3386 0.2694 0.0006 L

0.0667 0.0525 0.0003 

0.0948 0.0754 0.0002 

Other

H

0.0187 0.0147 0.0001 

25% of sum of above.
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ß Rig anchoring – Although it is anticipated that no marine traffic except possibly 

icebreakers will occur during the ice season, an increased traffic density during the 

four month open water season to resupply the platforms is expected, justifying only a 

20% decrease in this failure cause.

ß Workboat anchoring – The same applies to workboat anchoring as to rig anchoring.

ß Mechanical connection failure or material failure – No change was made to account 

for Arctic effects.

ß Mudslide – A relative ly low gradient resulting in limited mudslide potential is 

anticipated. A gradual increase in the mudslide potential (reflected by smaller 

decreases in failure frequency) ranging from 60% for shallow water to only 40% in 

deep water was included to account for the anticipated increase in gradient as deeper 

waters are encountered.

ß Storms – Considerably fewer severe storms are anticipated on an annual basis in the 

Arctic than in GOM, due to damping of the ocean surface by ice cover.

ß Arctic effects – Arctic effects are effects which are unique to the Arctic and are not 

reflected in the historical fault tree itself. Arctic effects were discussed in detail in 

Chapter 2, Section 2.5. The discussion in that section is summarized in the right hand 

column of Table 4.4. The frequency increments in this table are given as both the 

“mode” values and the “expected” values. The mode values are the mode values 

given in Table 2.11. The expected values, however, are those calculated using the 

Monte Carlo method with the low, mode, and high values from Table 2.11, as inputs 

to the Monte Carlo. The expected or mean values are clearly considerably higher than 

the mode or most likely values. This lack of coincidence between expected and mode

values is due to the skewness of the distribution. 

Derivation of the Arctic effect distributions is accomplished through the construction of a 

secondary triangular distribution by which the historical causal frequency distributions 

are multiplied to provide the resultant Arctic effect distribution. This secondary 

distribution utilizes the value of mode adjustments from Table 4.4, with appropriate 

second order perturbations for the upper and lower 90% confidence interval bounds. 

Table 4.5 summarizes these Arctic effect distributions. For the Arctic modified effects,

given in the top of the table, the secondary distribution is simply the frequency change 

used as the mode of the distribution, and 90% upper and lower confidence interval 

changes given under the Min and Max columns. For the Arctic unique effects, total 

frequency increments are given, with the upper confidence interval value at 

approximately 12 times the mode, and the lower bound value at approximately 1/10 of the 

modal value.
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Table 4.5

Pipeline Arctic Effect Distribution Derivation Summary

(App. Table 2.2)

Shallow Medium Deep

Frequency Change % CAUSE 

CLASSIFICATION

Spill 

Size

Min Mode Max Min Mode Max Min Mode Max

CORROSION

External All (90) (30) (10) (90) (30) (10) (90) (30) (10)

Internal All (90) (30) (10) (90) (30) (10) (90) (30) (10)

THIRD PARTY IMPACT

Anchor Impact All (90) (50) (10) (90) (50) (10) (90) (50) (10)

Jackup Rig or Spud Barge All (90) (50) (10) (90) (50) (10) (90) (50) (10)

Trawl/Fishing Net All (90) (50) (10) (90) (60) (10) (90) (70) (10)

OPERATION IMPACT

Rig Anchoring All (50) (20) (10) (50) (20) (10) (50) (20) (10)

Work Boat Anchoring All (50) (20) (10) (50) (20) (10) (50) (20) (10)

MECHANICAL

Connection Failure All

Material Failure All

NATURAL HAZARD

Mud Slide All (90) (60) (10) (90) (50) (10) (90) (40) (10)

Storm/ Hurricane All (90) (50) (10) (90) (50) (10) (90) (50) (10)

Frequency Increment per 105 km-year

ARCTIC

S 0.0060 0.0680 0.8290 0.0048 0.0544 0.6632

M 0.0090 0.1210 1.4670 0.0072 0.0968 1.1736

L 0.0210 0.2610 3.1900 0.0168 0.2088 2.5520 Ice Gouging

H 0.0060 0.0730 0.8930 0.0048 0.0584 0.7144

S 0.0004 0.0012 0.0044

M 0.0006 0.0020 0.0078

L 0.0014 0.0045 0.0170 Strudel Scour

H 0.0004 0.0012 0.0048

S 0.00007 0.00023 0.00088 0.00007 0.00023 0.00088 0.00007 0.00023 0.00088

M 0.00013 0.00041 0.00156 0.00013 0.00041 0.00156 0.00013 0.00041 0.00156

L 0.00028 0.00089 0.00340 0.00028 0.00089 0.00340 0.00028 0.00089 0.00340 Upheaval Buckling

H 0.00008 0.00025 0.00095 0.00008 0.00025 0.00095 0.00008 0.00025 0.00095

S 0.00004 0.00012 0.00044 0.00004 0.00012 0.00044 0.00004 0.00012 0.00044

M 0.00006 0.00020 0.00078 0.00006 0.00020 0.00078 0.00006 0.00020 0.00078

L 0.00014 0.00045 0.00170 0.00014 0.00045 0.00170 0.00014 0.00045 0.00170 Thaw Settlement

H 0.00004 0.00012 0.00048 0.00004 0.00012 0.00048 0.00004 0.00012 0.00048

S 0.00162 0.01738 0.20869 0.00123 0.01369 0.16613 0.00003 0.00009 0.00033

M 0.00246 0.03092 0.36929 0.00185 0.02435 0.29399 0.00005 0.00015 0.00059

L 0.00571 0.06670 0.80303 0.00431 0.05253 0.63928 0.00011 0.00033 0.00128

Other

H 0.00163 0.01865 0.22480 0.00123 0.01469 0.17896 0.00003 0.00009 0.00036
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4.3.2 Arctic Pipeline Fault Tree Frequency Calculations

Incorporation of the frequency effects as variations in and additions to the historical 

frequencies can be represented in a fault tree, as shown for the large spill size for Arctic 

pipelines in Figure 4.4. In this figure, the historical frequency as well as that associated 

with small, medium, and deep-water zones are shown under each of the event boxes. 

Each box is further split into two, for pipelines less than or at least 10” diameter as 

represented in the historical database. Such fault trees were developed for all of the 

pipeline spill sizes, and these additional spill size fault trees, for small, medium, large, 

and huge spills are presented in Appendix 2, where the complete calculations are given. 

Of greatest importance, however, are the pipeline failure frequencies or failure rates per 

km-yr calculated from the first and second order input distributions using Monte Carlo 

simulation. These failure rates for the entire range of pipeline spill sizes, small, medium, 

large, and huge, are given in Tables 4.6, 4.7, 4.8, and 4.9, respectively.

Indeed, a huge array of numbers is shown in these tables. Consider Table 4.8, which is 

the frequency calculation corresponding to the large spill size fault tree shown in Figure 

4.4. Consider the bottom line opposite totals. What the table tells us is that the total spill 

frequency for pipelines < 10” diameter was 5.172 (per 105 km-yr) historically. With the 

first and second order frequency changes attributable to Arctic effects, this frequency is 

reduced to 4.374 for shallow water, to 4.003 for medium depth water, and to 2.635 for 

deep water. A similar trend in the reduction of failure frequencies with increasing water

depth for pipelines >= 10” is manifested in the right hand side of the table. Because the 

frequencies per unit pipeline length and operating year are the key drivers in the balance 

of the analysis, they have been given in the body of the report (in Tables 4.6 to 4.9) for

each of the spill sizes for pipelines. Finally, Table 4.10 summarizes the expected values

of the pipeline spill frequencies. 
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

4.15

Figure 4.4

Large Spill Frequencies for Pipeline

(Appendix Figure 2.3)

Shallow Water Depth Frequency

Medium Water Depth Frequency

Deep Water Depth Frequency

Dia<10" Dia>=10" Dia<10" Dia>=10" Dia<10" Dia>=10"

0.796 1.536 H 0.000 0.000 H 0.000 0.000

0.390 0.752 S 0.000 0.000 S 1.692 1.692

0.398 0.768 M 0.000 0.000 M 1.346 1.346

0.406 0.784 D 0.000 0.000 D 0.002 0.002

Dia<10" Dia>=10" Dia<10" Dia>=10" Dia<10" Dia>=10"

H 0.398 0.768 H 0.000 0.000 H 0.000 0.000

S 0.191 0.368 S 1.344 1.344 S 0.002 0.002

M 0.199 0.384 M 1.075 1.075 M 0.002 0.002

D 0.207 0.400 D 0.000 0.000 D 0.002 0.002

Dia<10" Dia>=10" Dia<10" Dia>=10" Dia<10" Dia>=10"

H 0.398 0.768 H 0.000 0.000 H 0.000 0.000

S 0.199 0.384 S 0.008 0.008 S 0.000 0.000

M 0.199 0.384 M 0.000 0.000 M 0.000 0.000

D 0.199 0.384 D 0.000 0.000 D 0.000 0.000

Dia<10" Dia>=10"

H 0.000 0.000

S 0.338 0.338

M 0.269 0.269

D 0.000 0.000

Thaw Settlement

Other

NATURAL HAZARD

Mud Slide

Storm/ Hurricane

UNKNOWN ARCTIC

Ice Gouging Upheaval Buckling

Strudel Scour

Dia<10" Dia>=10" P/L Size

All Values per 100000 km-year H 5.172 9.985 Historical Frequency

S 4.374 6.869 Shallow Water Depth Frequency

M 4.003 6.475 Medium Water Depth Frequency

D 2.635 5.085 Deep Water Depth Frequency

Dia<10" Dia>=10" Dia<10" Dia>=10"

0.398 0.768 H 0.000 0.000 H

0.287 0.553 S 0.000 0.000 S

0.287 0.553 M 0.000 0.000 M

0.287 0.553 D 0.000 0.000 D

Dia<10" Dia>=10" Dia<10" Dia>=10"

H 0.000 0.000 H 0.000 0.000

S 0.000 0.000 S 0.000 0.000

M 0.000 0.000 M 0.000 0.000

D 0.000 0.000 D 0.000 0.000

Dia<10" Dia>=10" Dia<10" Dia>=10"

H 0.398 0.768 H 0.000 0.000

S 0.287 0.553 S 0.000 0.000

M 0.287 0.553 M 0.000 0.000

D 0.287 0.553 D 0.000 0.000

Connection Failure

Material Failure

Rig Anchoring

Pipeline Large Spill 1000-9999 bbl

MECHANICAL

Work Boat Anchoring

OPERATION IMPACT

Note : All Values per 100000 km-year

Dia<10" Dia>=10" Dia<10" Dia>=10"

H 0.398 0.768 H 3.581 6.912 H

S 0.215 0.415 S 1.790 3.456 S

M 0.215 0.415 M 1.757 3.393 M

D 0.215 0.415 D 1.725 3.330 D

Dia<10" Dia>=10" Dia<10" Dia>=10"

H 0.000 0.000 H 1.591 3.072

S 0.000 0.000 S 0.796 1.536

M 0.000 0.000 M 0.796 1.536

D 0.000 0.000 D 0.796 1.536

Dia<10" Dia>=10" Dia<10" Dia>=10"

H 0.398 0.768 H 0.398 0.768

S 0.215 0.415 S 0.199 0.384

M 0.215 0.415 M 0.199 0.384

D 0.215 0.415 D 0.199 0.384

Dia<10" Dia>=10"

H 1.591 3.072

S 0.796 1.536

M 0.763 1.472

D 0.731 1.410

THIRD PARTY IMPACT

Trawl/Fishing Net

Anchor Impact

CORROSION

External

Internal Jackup Rig or Spud Barge
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

4.16

Table 4.6

Arctic Pipeline Small Spill (50-99 bbl) Frequencies

(App. Table 2.3)

Pipeline Diameter <10" Pipeline Diameter >= 10"

Shallow Medium Deep Shallow Medium Deep

CAUSE 

CLASSIFICATION

HIST. DISTRIBUTION 

%

FREQUENCY 

spills per 10

5km- year

Frequency 

Change

New 

Frequency

New 

Distribution %

Frequency 

Change

New 

Frequency

New 

Distribution %

Frequency 

Change

New 

Frequency

New 

Distribution %

FREQUENCY 

spills per 10

5km- year

Frequency 

Change

New 

Frequency

New 

Distribution %

Frequency 

Change

New 

Frequency

New 

Distribution %

Frequency 

Change

New 

Frequency

New 

Distribution %

CORROSION 15.79 0.817 (0.375) 0.442 11.71 (0.375) 0.442 11.98 (0.375) 0.442 13.21 0.526 (0.241) 0.284 11.00 (0.241) 0.284 11.38 (0.241) 0.284 13.21

External 5.26 0.272 (0.125) 0.147 3.90 (0.125) 0.147 3.99 (0.125) 0.147 4.40 0.175 (0.080) 0.095 3.67 (0.080) 0.095 3.79 (0.080) 0.095 4.40

Internal 10.53 0.544 (0.250) 0.294 7.81 (0.250) 0.294 7.98 (0.250) 0.294 8.81 0.350 (0.161) 0.190 7.33 (0.161) 0.190 7.59 (0.161) 0.190 8.80

THIRD PARTY 

IMPACT 36.84 1.905 (0.953) 0.953 25.25 (0.958) 0.947 25.68 (0.964) 0.942 28.15 1.226 (0.613) 0.613 23.72 (0.617) 0.609 24.40 (0.620) 0.606 28.15

Anchor Impact 31.58 1.633 (0.817) 0.817 21.65 (0.817) 0.817 22.14 (0.817) 0.817 24.42 1.051 (0.526) 0.526 20.33 (0.526) 0.526 21.04 (0.526) 0.526 24.41

Jackup Rig or 

Spud Barge

Trawl/Fishing Net 5.26 0.272 (0.136) 0.136 3.61 (0.142) 0.130 3.54 (0.147) 0.125 3.74 0.175 (0.088) 0.088 3.39 (0.091) 0.084 3.36 (0.095) 0.080 3.74

OPERATION 

IMPACT 15.79 0.817 (0.228) 0.588 15.60 (0.228) 0.588 15.95 (0.228) 0.588 17.59 0.526 (0.147) 0.379 14.65 (0.147) 0.379 15.16 (0.147) 0.379 17.59

Rig Anchoring 5.26 0.272 (0.076) 0.196 5.20 (0.076) 0.196 5.32 (0.076) 0.196 5.86 0.175 (0.049) 0.126 4.88 (0.049) 0.126 5.05 (0.049) 0.126 5.86

Work Boat 

Anchoring 10.53 0.544 (0.152) 0.392 10.40 (0.152) 0.392 10.63 (0.152) 0.392 11.73 0.350 (0.098) 0.252 9.77 (0.098) 0.252 10.10 (0.098) 0.252 11.73

MECHANICAL 10.53 0.544 0.544 14.43 0.544 14.76 0.544 16.28 0.350 0.350 13.55 0.350 14.02 0.350 16.28

Connection Failure 5.26 0.272 0.272 7.22 0.272 7.38 0.272 8.14 0.175 0.175 6.78 0.175 7.01 0.175 8.14

Material Failure 5.26 0.272 0.272 7.22 0.272 7.38 0.272 8.14 0.175 0.175 6.78 0.175 7.01 0.175 8.14

NATURAL 

HAZARD 10.53 0.544 (0.283) 0.261 6.92 (0.272) 0.272 7.38 (0.261) 0.283 8.48 0.350 (0.182) 0.168 6.50 (0.175) 0.175 7.01 (0.168) 0.182 8.48

Mud Slide 10.53 0.544 (0.283) 0.261 6.92 (0.272) 0.272 7.38 (0.261) 0.283 8.48 0.350 (0.182) 0.168 6.50 (0.175) 0.175 7.01 (0.168) 0.182 8.48

Storm/ Hurricane

ARCTIC 0.440 0.440 11.66 0.350 0.350 9.49 0.001 0.001 0.02 0.440 0.440 17.03 0.350 0.350 14.01 0.001 0.001 0.02

Ice Gouging 0.3495 0.3495 9.26 0.2796 0.2796 7.58 0.3495 0.3495 13.52 0.2796 0.2796 11.19

Strudel Scour 0.0021 0.0021 0.06 0.0021 0.0021 0.08

Upheaval Buckling 0.0004 0.0004 0.01 0.0004 0.0004 0.01 0.0004 0.0004 0.01 0.0004 0.0004 0.02 0.0004 0.0004 0.02 0.0004 0.0004 0.02

Thaw Settlement

Other 0.0880 0.0880 2.33 0.0700 0.0700 1.90 0.0001 0.0001 0.00 0.0880 0.0880 3.41 0.0700 0.0700 2.80 0.0001 0.0001 0.00

UNKNOWN 10.53 0.544 0.544 14.43 0.544 14.76 0.544 16.28 0.350 0.350 13.55 0.350 14.02 0.350 16.28

TOTALS 100.00 5.172 (1.399) 3.773 100.00 (1.484) 3.688 100.00 (1.827) 3.345 100.00 3.328 (0.744) 2.585 100.00 (0.830) 2.498 100.00 (1.176) 2.152 100.00
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

4.17

Table 4.7

Arctic Pipeline Medium Spill (100-999 bbl) Frequencies

(App. Table 2.4) 

Pipeline Diameter <10" Pipeline Diameter >= 10"

Shallow Medium Deep Shallow Medium Deep

CAUSE 

CLASSIFICATION

HIST. DISTRIBUTION 

%

FREQUENCY 

spills per 10

5km- year

Frequency 

Change

New 

Frequency

New 

Distribution %

Frequency 

Change

New 

Frequency

New 

Distribution %

Frequency 

Change

New 

Frequency

New 

Distribution %

FREQUENCY 

spills per 10

5km- year

Frequency 

Change

New 

Frequency

New 

Distribution %

Frequency 

Change

New 

Frequency

New 

Distribution %

Frequency 

Change

New 

Frequency

New 

Distribution %

CORROSION 15.79 1.429 (0.656) 0.773 11.70 (0.656) 0.773 11.97 (0.656) 0.773 13.21 1.577 (0.724) 0.853 11.83 (0.724) 0.853 12.07 (0.724) 0.853 13.21

External 5.26 0.476 (0.219) 0.258 3.90 (0.219) 0.258 3.99 (0.219) 0.258 4.40 0.526 (0.241) 0.284 3.94 (0.241) 0.284 4.02 (0.241) 0.284 4.40

Internal 10.53 0.953 (0.437) 0.515 7.80 (0.437) 0.515 7.98 (0.437) 0.515 8.81 1.051 (0.482) 0.569 7.88 (0.482) 0.569 8.05 (0.482) 0.569 8.81

THIRD PARTY 

IMPACT 36.84 3.335 (1.667) 1.667 25.22 (1.677) 1.657 25.65 (1.687) 1.648 28.15 3.679 (1.839) 1.839 25.50 (1.850) 1.828 25.89 (1.861) 1.818 28.15

Anchor Impact 31.58 2.858 (1.429) 1.429 21.62 (1.429) 1.429 22.12 (1.429) 1.429 24.42 3.153 (1.577) 1.577 21.86 (1.577) 1.577 22.32 (1.577) 1.577 24.42

Jackup Rig or 

Spud Barge

Trawl/Fishing Net 5.26 0.476 (0.238) 0.238 3.60 (0.248) 0.228 3.53 (0.258) 0.219 3.74 0.526 (0.263) 0.263 3.64 (0.274) 0.252 3.57 (0.284) 0.241 3.74

OPERATION 

IMPACT 15.79 1.429 (0.399) 1.030 15.58 (0.399) 1.030 15.94 (0.399) 1.030 17.59 1.577 (0.441) 1.136 15.75 (0.441) 1.136 16.08 (0.441) 1.136 17.59

Rig Anchoring 5.26 0.476 (0.133) 0.343 5.19 (0.133) 0.343 5.31 (0.133) 0.343 5.86 0.526 (0.147) 0.379 5.25 (0.147) 0.379 5.36 (0.147) 0.379 5.86

Work Boat 

Anchoring 10.53 0.953 (0.266) 0.686 10.38 (0.266) 0.686 10.62 (0.266) 0.686 11.73 1.051 (0.294) 0.757 10.50 (0.294) 0.757 10.72 (0.294) 0.757 11.73

MECHANICAL 10.53 0.953 0.953 14.41 0.953 14.75 0.953 16.28 1.051 1.051 14.57 1.051 14.88 1.051 16.28

Connection 

Failure 5.26 0.476 0.476 7.21 0.476 7.37 0.476 8.14 0.526 0.526 7.29 0.526 7.44 0.526 8.14

Material Failure 5.26 0.476 0.476 7.21 0.476 7.37 0.476 8.14 0.526 0.526 7.29 0.526 7.44 0.526 8.14

NATURAL 

HAZARD 10.53 0.953 (0.496) 0.457 6.91 (0.476) 0.476 7.37 (0.457) 0.496 8.48 1.051 (0.547) 0.504 6.98 (0.526) 0.526 7.44 (0.504) 0.547 8.48

Mud Slide 10.53 0.953 (0.496) 0.457 6.91 (0.476) 0.476 7.37 (0.457) 0.496 8.48 1.051 (0.547) 0.504 6.98 (0.526) 0.526 7.44 (0.504) 0.547 8.48

Storm/ Hurricane

ARCTIC 0.778 0.778 11.77 0.619 0.619 9.58 0.001 0.001 0.02 0.778 0.778 10.79 0.619 0.619 8.76 0.001 0.001 0.01

Ice Gouging 0.6178 0.6178 9.35 0.4943 0.4943 7.65 0.6178 0.6178 8.57 0.4943 0.4943 7.00

Strudel Scour 0.0038 0.0038 0.06 0.0038 0.0038 0.05

Upheaval Buckling 0.0008 0.0008 0.01 0.0008 0.0008 0.01 0.0008 0.0008 0.01 0.0008 0.0008 0.01 0.0008 0.0008 0.01 0.0008 0.0008 0.01

Thaw Settlement

Other 0.1556 0.1556 2.35 0.1238 0.1238 1.92 0.0002 0.0002 0.00 0.1556 0.1556 2.16 0.1238 0.1238 1.75 0.0002 0.0002 0.00

UNKNOWN 10.53 0.953 0.953 14.41 0.953 14.75 0.953 16.28 1.051 1.051 14.57 1.051 14.88 1.051 16.28

TOTALS 100.00 9.051 (2.441) 6.610 100.00 (2.590) 6.461 100.00 (3.198) 5.853 100.00 9.985 (2.773) 7.212 100.00 (2.921) 7.063 100.00 (3.528) 6.457 100.00
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

4.18

Table 4.8

Arctic Pipeline Large Spill (1,000-9,999 bbl) Frequencies

(App. Table 2.5) 

Pipeline Diameter <10" Pipeline Diameter >= 10"

Shallow Medium Deep Shallow Medium Deep

CAUSE 

CLASSIFICATION

HIST. DISTRIBUTION 

%

FREQUENCY 

spills per 10

5km- year

Frequency 

Change

New 

Frequency

New 

Distribution %

Frequency 

Change

New 

Frequency

New 

Distribution %

Frequency 

Change

New 

Frequency

New 

Distribution %

FREQUENCY 

spills per 10

5km- year

Frequency 

Change

New 

Frequency

New 

Distribution %

Frequency 

Change

New 

Frequency

New 

Distribution %

Frequency 

Change

New 

Frequency

New 

Distribution %

CORROSION 7.69 0.398 (0.183) 0.215 4.92 (0.183) 0.215 5.38 (0.183) 0.215 8.17 0.768 (0.353) 0.415 6.05 (0.353) 0.415 6.42 (0.353) 0.415 8.17

External

Internal 7.69 0.398 (0.183) 0.215 4.92 (0.183) 0.215 5.38 (0.183) 0.215 8.17 0.768 (0.353) 0.415 6.05 (0.353) 0.415 6.42 (0.353) 0.415 8.17

THIRD PARTY 

IMPACT 69.23 3.581 (1.790) 1.790 40.93 (1.823) 1.757 43.90 (1.855) 1.725 65.47 6.912 (3.456) 3.456 50.31 (3.520) 3.393 52.39 (3.582) 3.330 65.49

Anchor Impact 30.77 1.591 (0.796) 0.796 18.19 (0.796) 0.796 19.88 (0.796) 0.796 30.20 3.072 (1.536) 1.536 22.36 (1.536) 1.536 23.72 (1.536) 1.536 30.21

Jackup Rig or 

Spud Barge

7.69 0.398 (0.199) 0.199 4.55 (0.199) 0.199 4.97 (0.199) 0.199 7.55 0.768 (0.384) 0.384 5.59 (0.384) 0.384 5.93 (0.384) 0.384 7.55

Trawl/Fishing Net 30.77 1.591 (0.796) 0.796 18.19 (0.829) 0.763 19.05 (0.861) 0.731 27.72 3.072 (1.536) 1.536 22.36 (1.600) 1.472 22.74 (1.662) 1.410 27.73

OPERATION 

IMPACT 7.69 0.398 (0.111) 0.287 6.55 (0.111) 0.287 7.16 (0.111) 0.287 10.88 0.768 (0.215) 0.553 8.06 (0.215) 0.553 8.55 (0.215) 0.553 10.88

Rig Anchoring

Work Boat 

Anchoring 7.69 0.398 (0.111) 0.287 6.55 (0.111) 0.287 7.16 (0.111) 0.287 10.88 0.768 (0.215) 0.553 8.06 (0.215) 0.553 8.55 (0.215) 0.553 10.88

MECHANICAL

Connection 

Failure

Material Failure

NATURAL 

HAZARD 15.38 0.796 (0.406) 0.390 8.91 (0.398) 0.398 9.94 (0.390) 0.406 15.41 1.536 (0.784) 0.752 10.95 (0.768) 0.768 11.86 (0.752) 0.784 15.42

Mud Slide 7.69 0.398 (0.207) 0.191 4.36 (0.199) 0.199 4.97 (0.191) 0.207 7.86 0.768 (0.400) 0.368 5.36 (0.384) 0.384 5.93 (0.368) 0.400 7.86

Storm/ Hurricane 7.69 0.398 (0.199) 0.199 4.55 (0.199) 0.199 4.97 (0.199) 0.199 7.55 0.768 (0.384) 0.384 5.59 (0.384) 0.384 5.93 (0.384) 0.384 7.55

ARCTIC 1.692 1.692 38.69 1.346 1.346 33.62 0.002 0.002 0.08 1.692 1.692 24.63 1.346 1.346 20.78 0.002 0.002 0.04

Ice Gouging 1.3438 1.3438 30.72 1.0750 1.0750 26.86 1.3438 1.3438 19.56 1.0750 1.0750 16.60

Strudel Scour 0.0082 0.0082 0.19 0.0082 0.0082 0.12

Upheaval Buckling 0.0016 0.0016 0.04 0.0016 0.0016 0.04 0.0016 0.0016 0.06 0.0016 0.0016 0.02 0.0016 0.0016 0.03 0.0016 0.0016 0.03

Thaw Settlement

Other 0.3384 0.3384 7.74 0.2692 0.2692 6.72 0.0004 0.0004 0.02 0.3384 0.3384 4.93 0.2692 0.2692 4.16 0.0004 0.0004 0.01

UNKNOWN

TOTALS 100.00 5.172 (0.798) 4.374 100.00 (1.169) 4.003 100.00 (2.537) 2.635 100.00 9.985 (3.115) 6.869 100.00 (3.509) 6.475 100.00 (4.899) 5.085 100.00
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

4.19

Table 4.9

Arctic Pipeline Huge Spill (>= 10,000 bbl) Frequencies

(App. Table 2.6)

Pipeline Diameter <10" Pipeline Diameter >= 10"

Shallow Medium Deep Shallow Medium Deep

CAUSE 

CLASSIFICATION

HIST. DISTRIBUTION 

%

FREQUENCY 

spills per 10

5km- year

Frequency 

Change

New 

Frequency

New 

Distribution %

Frequency 

Change

New 

Frequency

New 

Distribution %

Frequency 

Change

New 

Frequency

New 

Distribution %

FREQUENCY 

spills per 10

5km- year

Frequency 

Change

New 

Frequency

New 

Distribution %

Frequency 

Change

New 

Frequency

New 

Distribution %

Frequency 

Change

New 

Frequency

New 

Distribution %

CORROSION 7.69 0.099 (0.046) 0.054 4.70 (0.046) 0.054 5.17 (0.046) 0.054 8.17 0.256 (0.118) 0.138 6.30 (0.118) 0.138 6.64 (0.118) 0.138 8.17

External

Internal 7.69 0.099 (0.046) 0.054 4.70 (0.046) 0.054 5.17 (0.046) 0.054 8.17 0.256 (0.118) 0.138 6.30 (0.118) 0.138 6.64 (0.118) 0.138 8.17

THIRD PARTY 

IMPACT 69.23 0.895 (0.448) 0.448 39.12 (0.456) 0.439 42.20 (0.464) 0.431 65.46 2.304 (1.152) 1.152 52.38 (1.173) 1.131 54.20 (1.194) 1.110 65.50

Anchor Impact 30.77 0.398 (0.199) 0.199 17.39 (0.199) 0.199 19.11 (0.199) 0.199 30.19 1.024 (0.512) 0.512 23.28 (0.512) 0.512 24.54 (0.512) 0.512 30.21

Jackup Rig or 

Spud Barge 7.69 0.099 (0.050) 0.050 4.35 (0.050) 0.050 4.78 (0.050) 0.050 7.55 0.256 (0.128) 0.128 5.82 (0.128) 0.128 6.13 (0.128) 0.128 7.55

Trawl/Fishing Net 30.77 0.398 (0.199) 0.199 17.39 (0.207) 0.191 18.32 (0.215) 0.183 27.72 1.024 (0.512) 0.512 23.28 (0.533) 0.491 23.52 (0.554) 0.470 27.74

OPERATION 

IMPACT 7.69 0.099 (0.028) 0.072 6.26 (0.028) 0.072 6.88 (0.028) 0.072 10.88 0.256 (0.072) 0.184 8.39 (0.072) 0.184 8.84 (0.072) 0.184 10.88

Rig Anchoring

Work Boat 

Anchoring

7.69 0.099 (0.028) 0.072 6.26 (0.028) 0.072 6.88 (0.028) 0.072 10.88 0.256 (0.072) 0.184 8.39 (0.072) 0.184 8.84 (0.072) 0.184 10.88

MECHANICAL

Connection 

Failure

Material Failure

NATURAL 

HAZARD 15.38 0.199 (0.102) 0.097 8.51 (0.099) 0.099 9.55 (0.097) 0.102 15.41 0.512 (0.261) 0.251 11.40 (0.256) 0.256 12.27 (0.251) 0.261 15.42

Mud Slide 7.69 0.099 (0.052) 0.048 4.17 (0.050) 0.050 4.78 (0.048) 0.052 7.86 0.256 (0.133) 0.123 5.58 (0.128) 0.128 6.13 (0.123) 0.133 7.87

Storm/ Hurricane 7.69 0.099 (0.050) 0.050 4.35 (0.050) 0.050 4.78 (0.050) 0.050 7.55 0.256 (0.128) 0.128 5.82 (0.128) 0.128 6.13 (0.128) 0.128 7.55

ARCTIC 0.474 0.474 41.40 0.377 0.377 36.19 0.001 0.001 0.09 0.474 0.474 21.54 0.377 0.377 18.06 0.001 0.001 0.03

Ice Gouging 0.3762 0.3762 32.88 0.3010 0.3010 28.91 0.3762 0.3762 17.11 0.3010 0.3010 14.42

Strudel Scour 0.0023 0.0023 0.20 0.0023 0.0023 0.10

Upheaval Buckling 0.0005 0.0005 0.04 0.0005 0.0005 0.04 0.0005 0.0005 0.07 0.0005 0.0005 0.02 0.0005 0.0005 0.02 0.0005 0.0005 0.03

Thaw Settlement

Other 0.0947 0.0947 8.28 0.0754 0.0754 7.24 0.0001 0.0001 0.02 0.0947 0.0947 4.31 0.0754 0.0754 3.61 0.0001 0.0001 0.01

UNKNOWN

TOTALS 100.00 1.293 (0.149) 1.144 100.00 (0.252) 1.041 100.00 (0.634) 0.659 100.00 3.328 (1.129) 2.199 100.00 (1.242) 2.087 100.00 (1.633) 1.695 100.00
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

4.20

Table 4.10

Arctic Pipeline Spill Frequencies Expected Value Summary

(App. Table 2.2A)

PipelineDiameter <10" Pipeline Diameter >=10"

Pipeline Spill Arctic Frequency Arctic Frequency

Size Historical

Frequency

spills per

105km-year Shallow Medium Deep

Historical

Frequency

spills per

105km-year Shallow Medium Deep

SMALL SPILLS

50-99 bbl 5.172 3.671 3.587 3.243 3.328 2.519 2.433 2.087

MEDIUM SPILLS

100-999 bbl 9.051 6.432 6.283 5.676 8.320 5.975 5.826 5.218

LARGE SPILLS

1000-9999 bbl 5.172 4.374 4.003 2.635 9.985 6.870 6.476 5.086

HUGE SPILLS

>=10000 bbl 1.293 1.144 1.041 0.659 3.328 2.200 2.087 1.695
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4.21

4.4 Platform Fault Tree Analysis

4.4.1 Arctic Platform Spill Causal Frequency Distributions

Table 4.11 summarizes the variations in the modified and unique Arctic effect inputs for

platforms. As for pipeline unique effects, both the Triangular Distribution expected and 

modal values are given.

The first three modified cause classifications, the process facility release, storage tank 

release, and structural failure were reduced by 20 to 30% primarily as a result of the 

state-of-the-art engineering, construction, and operational standards and practices 

expected. As before, storms tend to be less severe in the Arctic, and certainly during the 

ice season would have limited impact on the facility. Due to the extremely low traffic 

density, as for the case of pipelines, the ship collision cause has been reduced by 50%. 

Unique effects are also included. Increments in facility spills were attributed to ice force, 

low temperature effects, and unknown effects which were taken as a percentage of the 

other unique Arctic effects. Ice force effect calculations were based on the 1/10,000 year 

ice force causing spills, predominantly small and medium. Ice forces are also considered 

to increase as a contributor to oil spill occurrences with water depth, due to the increasing 

severity of ice loads as one moves towards the edge of the landfast ice zone with 

increasing water depth. Increase of low temperature effects with water depth was 

estimated as 10% of historical process facility spill rates. 

Changes in frequency distribution attributable to Arctic effects were calculated using the 

secondary effect probability distribution, as was done for pipelines. Table 4.12

summarizes the principal distribution parameters for both the Arctic modified and Arctic 

unique effect distributions.

4.4.2 Arctic Platform Fault Tree Spill Frequency Calculations

Figure 4.5 shows the fault tree developed for Arctic platform spills for the different water 

depth zones for large and huge spill sizes, which were grouped together as described for 

platforms in Chapter 2. Again, the fault tree gives the historical value, together with the 

calculated values for shallow, medium, and deep water. In the case of this particular fault 

tree, there was room to represent both the small and medium or less than 1,000 bbl and 

the large and huge or at least 1,000 bbl spills. Like pipelines, it is evident that platforms 

manifest a somewhat lower frequency for both spill size categories for the Arctic 

conditions. Tables 4.13 and 4.14 show the frequency calculations for platforms for small 

and medium and large and huge spill sizes, respectively. Table 4.15 summarizes the 

historical and derived Arctic expected values of platform spill frequencies.
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4.22

Table 4.11

Platform Arctic Effect Derivation Summary

(App. Table 2.7)

Historical Expected Frequency 

CAUSE Change %

CLASSIFICATION

Spill 

Size

Shallow Medium Deep

Reason

PROCESS FACILITY RLS. All (30) (30) (30) State of the art now, High QC, High Inspection and 

Maintenance Requirements

STORAGE TANK RLS. All (30) (30) (30) State of the art now, High QC, High Inspection and 

Maintenance Requirements

STRUCTURAL FAILURE All (20) (20) (20) High safety factor, Monitoring Programs

HURRICANE/STORM All (50) (40) (30) Less severe storms. More intensity in deep water.

COLLISION All (50) (50) (50) Very low traffic density.

Freq. Increment per 104 well-year

Expected Expected Expected

Mode Mode Mode

ARCTIC

0.1447 0.2170 0.3256 

SM

0.0340 0.0510 0.0765 

0.0255 0.0383 0.0575 

Ice Force

LH

0.0060 0.0090 0.0135 

Assumed 10,000 year return period ice force causes spill 4% of 

occurrences (96% reliability). 85% of the spills are SM.

0.1000 0.1000 0.1000 

SM

0.1000 0.1000 0.1000 

0.0080 0.0080 0.0080 

Facility Low Temperature

LH

0.0080 0.0080 0.0080 

Assumed fraction of Historical Process Facilities release 

frequency with 6% SM and 3% for LH spill sizes. 

0.0244 0.0316 0.0424 

SM

0.0134 0.0151 0.0177 

0.0033 0.0046 0.0065 

Other

LH

0.0014 0.0017 0.0022 

10% of sum of abov e.
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4.23

Table 4.12

Platform Arctic Effect Distribution Derivation Summary

(App. Table 2.8)

Shallow Medium Deep

Frequency Change %

CAUSE

CLASSIFICATION

Spill 

Size

Min Mode Max Min Mode Max Min Mode Max

PROCESS FACILITY RLS. All (60) (30) (10) (60) (30) (10) (60) (30) (10)

STORAGE TANK RLS. All (60) (30) (10) (60) (30) (10) (60) (30) (10)

STRUCTURAL FAILURE All (60) (20) (10) (60) (20) (10) (60) (20) (10)

HURRICANE/STORM All (90) (50) (10) (90) (40) (10) (90) (30) (10)

COLLISION All (90) (50) (10) (90) (50) (10) (90) (50) (10)

Frequency Increment per 104 well-year

ARCTIC

SM 0.003 0.034 0.340 0.005 0.051 0.510 0.008 0.077 0.765

Ice Force

LH 0.001 0.006 0.060 0.001 0.009 0.090 0.001 0.014 0.135

SM 0.050 0.100 0.150 0.050 0.100 0.150 0.050 0.100 0.150

Facility Low Temperature

LH 0.004 0.008 0.012 0.004 0.008 0.012 0.004 0.008 0.012

SM 0.005 0.013 0.049 0.006 0.015 0.066 0.006 0.018 0.092

Other

LH 0.000 0.001 0.007 0.000 0.002 0.010 0.001 0.002 0.015
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4.24

Figure 4.5

Spill Frequencies Platform Fault Tree

(Appendix Figure 2.5)

SM

50-999

bbl

LH

=>1000

bbl

Spill Size

All Values per 10000 well-years H 2.157 0.360 Historical Frequency

S 1.619 0.274 Shallow Water Depth Frequency

M 1.704 0.288 Medium Water Depth Frequency

D 1.828 0.309 Deep Water Depth Frequency

SM LH SM LH SM LH SM LH

0.120 0.000 H 0.240 0.000 H 0.240 0.000 H 0.000 0.000

0.082 0.000 S 0.120 0.000 S 0.120 0.000 S 0.269 0.037

0.082 0.000 M 0.125 0.000 M 0.120 0.000 M 0.349 0.051

0.082 0.000 D 0.130 0.000 D 0.120 0.000 D 0.468 0.072

SM LH

H 0.000 0.000

S 0.145 0.026

M 0.217 0.038

D 0.326 0.057

SM LH

H 0.000 0.000

S 0.100 0.008

M 0.100 0.008

D 0.100 0.008

SM LH

H 0.000 0.000

S 0.024 0.003

M 0.032 0.005

D 0.042 0.007

ARCTIC

Platform Spill

Other

Ice Force

Facility Low Temperature

STRUCTURAL FAILURE HURRICANE/STORM COLLISION

Note : All Values per 10000 well-years

SM LH SM LH

H 1.438 0.120 H 0.120 0.240 H

S 0.950 0.079 S 0.079 0.158 S

M 0.950 0.079 M 0.079 0.158 M

D 0.950 0.079 D 0.079 0.158 D

PROCESS FACILITY RLS. STORAGE TANK RLS.
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4.25

Table 4.13

Arctic Platform Small and Medium Spill Frequencies

(App. Table 2.9)

SMALL AND MEDIUM SPILLS

50-999 bbl

Shallow Medium Deep

CAUSE

CLASSIFICATION

HISTORICAL DISTRIBUTION

%

FREQUENCY

spills per

10

4well-year

Frequency

Change

New Frequency

New Distribution

 %

Frequency

Change

New Frequency

New Distribution

 %

Frequency

Change

New Frequency

New Distribution

 %

PROCESS FACILITY 

RLS. 66.67 1.438 (0.488) 0.950 58.65 (0.488) 0.950 55.74 (0.488) 0.950 51.96

STORAGE TANK RLS. 5.56 0.120 (0.041) 0.079 4.89 (0.041) 0.079 4.65 (0.041) 0.079 4.33

STRUCTURAL FAILURE 5.56 0.120 (0.038) 0.082 5.04 (0.038) 0.082 4.79 (0.038) 0.082 4.46

HURRICANE/STORM 11.11 0.240 (0.120) 0.120 7.40 (0.115) 0.125 7.33 (0.110) 0.130 7.09

COLLISION 11.11 0.240 (0.120) 0.120 7.40 (0.120) 0.120 7.03 (0.120) 0.120 6.56

ARCTIC 0.269 0.269 16.62 0.349 0.349 20.46 0.468 0.468 25.60

Ice Force 0.145 0.145 8.94 0.217 0.217 12.74 0.326 0.326 17.81

Facility Low Temperature 0.100 0.100 6.18 0.100 0.100 5.87 0.100 0.100 5.47

Other 0.024 0.024 1.51 0.032 0.032 1.86 0.042 0.042 2.32

TOTALS 100.00 2.157 (0.538) 1.619 100.00 (0.453) 1.704 100.00 (0.329) 1.828 100.00
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4.26

Table 4.14

Arctic Platform Large and Huge Spill Frequencies

(App. Table 2.10)

LARGE AND HUGE SPILLS

>=1000 bbl

Shallow Medium Deep

CAUSE

CLASSIFICATION

HISTORICAL DISTRIBUTION

%

FREQUENCY

spills per

10

4well-year

Frequency

Change

New Frequency

New Distribution

 %

Frequency

Change

New Frequency

New Distribution

 %

Frequency

Change

New Frequency

New Distribution

 %

PROCESS FACILITY 

RLS. 33.33 0.120 (0.041) 0.079 28.85 (0.041) 0.079 27.45 (0.041) 0.079 25.58

STORAGE TANK RLS. 66.67 0.240 (0.081) 0.158 57.70 (0.081) 0.158 54.89 (0.081) 0.158 51.16

STRUCTURAL 

FAILURE

HURRICANE/STORM

COLLISION

ARCTIC 0.037 0.037 13.44 0.051 0.051 17.66 0.072 0.072 23.27

Ice Force 0.026 0.026 9.31 0.038 0.038 13.28 0.057 0.057 18.57

Facility Low Temperature 0.008 0.008 2.92 0.008 0.008 2.77 0.008 0.008 2.59

Other 0.003 0.003 1.22 0.005 0.005 1.60 0.007 0.007 2.11

TOTALS 100.00 0.360 (0.085) 0.274 100.00 (0.071) 0.288 100.00 (0.050) 0.309 100.00
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4.27

Table 4.15

Arctic Platforms Spill Frequency Expected Value Summary

(App. Table 2.8A)

Arctic Frequency

Platform Spill Size

Historical

Frequency

spills per

104 well-year Shallow Medium Deep

SMALL AND MEDIUM SPILLS

50-999 bbl 2.157 1.619 1.704 1.828

LARGE AND HUGE SPILLS

>=1,000 bbl 0.360 0.274 0.288 0.309
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4.28

4.5 Blowout Frequency Analysis

4.5.1 Well Blowout First Order Arctic Effects

The historical data, as described in Chapter 2, was modified for each well type, spill size, 

and water depth range, as described in Table 4.16. No Arctic unique effects were 

introduced for well blowouts. 

4.5.2 Arctic Well Blowout Spill Frequency Calculation

Table 4.17 gives the details of the frequency calculation for well blowouts. No fault tree 

was required here, as only base events with no causal distributions were modeled for each 

case. The modifications given in Table 4.16 were applied to all three values (minimum, 

mode, maximum) to yield the values summarized in Table 4.17.

4.6 Spill Volume Distributions

Table 4.18 summarizes the spill volume distribution parameters for each facility type,

including the expected value that was calculated utilizing a Monte Carlo calculation. The 

spill volume parameters were derived from the historical data as described in Section 2.7. 
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Table 4.16

Well Fault Tree Analysis Arctic Effect Summary

(App. Table 2.11)

Historical Expected Frequency 

Change % Reas on EVENT FREQUENCY

UNIT

Shallow Medium Deep

Small and Medium Spills

50-999 bbl

PRODUCTION WELL spill per 104well-year (30) (30) (30) State of the art now, High QC, High 

Inspection and Maintenance Requirements

EXPLORATION WELL DRILLING spill per 104wells (30) (20) (10) Highly qualified drilling contractor. Better 

logistics support in shallow water.

DEVELOPMENT WELL DRILLING spill per 104wells (30) (20) (10) Highly qualified drilling contractor. Better 

logistics support in shallow water.

Large Spills

1000-9999 bbl

PRODUCTION WELL spill per 104well-year (30) (30) (30) State of the art now, High QC, High 

Inspection and Maintenance Requirements

EXPLORATION WELL DRILLING spill per 104wells (30) (20) (10) Highly qualified drilling contractor. Better 

logistics support in shallow water.

DEVELOPMENT WELL DRILLING spill per 104wells (30) (20) (10) Highly qualified drilling contractor. Better 

logistics support in shallow water.

Spill 10000-149999 bbl

PRODUCTION WELL spill per 104well-year (30) (30) (30) State of the art now, High QC, High 

Inspection and Maintenance Requirements

EXPLORATION WELL DRILLING spill per 104wells (30) (20) (10) Highly qualified drilling contractor. Better 

logistics support in shallow water.

DEVELOPMENT WELL DRILLING spill per 104wells (30) (20) (10) Highly qualified drilling contractor. Better 

logistics support in shallow water.

Spill >=150000 bbl

PRODUCTION WELL spill per 104well-year (30) (30) (30) State of the art now, High QC, High 

Inspection and Maintenance Requirements

EXPLORATION WELL DRILLING spill per 104wells (30) (20) (10) Highly qualified drilling contractor. Better 

logistics support in shallow water.

DEVELOPMENT WELL DRILLING spill per 104wells (30) (20) (10) Highly qualified drilling contractor. Better 

logis tics support in shallow water.
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4.30

Table 4.17

Arctic Well Blowout Frequencies

(App. Table 2.12)

Shallow Medium Deep

EVENT FREQUENCY UNIT HISTORICAL

FREQUENCY Frequency

Change

New 

Frequency

Frequency

Change

New 

Frequency

Frequency

Change

New 

Frequency

Small and Medium Spills

50-999 bbl

PRODUCTION WELL spill per 104 well-year 0.147 -0.044 0.103 -0.044 0.103 -0.044 0.103

EXPLORATION WELL 

DRILLING spill per 104 wells 2.262 -0.678 1.583 -0.452 1.809 -0.226 2.035

DEVELOPMENT WELL 

DRILLING spill per 104 wells 0.692 -0.208 0.484 -0.138 0.554 -0.069 0.623

Large Spills

1000-9999 bbl

PRODUCTION WELL spill per 104 well-year 1.026 -0.308 0.718 -0.308 0.718 -0.308 0.718

EXPLORATION WELL 

DRILLING spill per 104 wells 15.824 -4.747 11.077 -3.165 12.659 -1.582 14.242

DEVELOPMENT WELL 

DRILLING spill per 104 wells 4.833 -1.450 3.383 -0.967 3.867 -0.483 4.350

Spills 10000-149999 bbl

PRODUCTION WELL spill per 104 well-year 0.440 -0.132 0.308 -0.132 0.308 -0.132 0.308

EXPLORATION WELL 

DRILLING spill per 104 wells 6.799 -2.040 4.759 -1.360 5.439 -0.680 6.119

DEVELOPMENT WELL 

DRILLING spill per 104 wells 2.076 -0.623 1.453 -0.415 1.661 -0.208 1.868

Spills >=150000 bbl

PRODUCTION WELL spill per 104 well-year 0.293 -0.088 0.205 -0.088 0.205 -0.088 0.205

EXPLORATION WELL 

DRILLING spill per 104 wells 3.936 -1.181 2.755 -0.787 3.149 -0.394 3.543

DEVELOPMENT WELL 

DRILLING spill per 104 wells 2.076 -0.623 1.453 -0.415 1.661 -0.208 1.868
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4.31

Table 4.18

Summary of Spill Size Distribution Parameters

(App. Table 2.13)

PIPELINE SPILL VOLUMES

Spill Size Small Spills

50-99 bbl

Medium Spills

100-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

>=10000 bbl

Spill Expectation Low Mode High Expected Low Mode High Expected Low Mode High Expected Low Mode High Expected

Pipelines Diameter

10" Spill 50 58 99 71 100 226 999 485 1000 4436 9999 5279 10000 14423 20000 14880 

Pipelines Diameter

10" Spill 50 58 99 71 100 387 999 516 1000 3932 9999 5176 10000 17705 20000 15552 

PLATFORM SPILL VOLUMES

Spill Size Small and Medium Spills

50-999 bbl

Large and Huge Spills

>=1000 bbl

Spill Expectation Low Mode High Expected Low Mode High Expected

Platform Spill 50 158 999 452 1000 6130 10000 5631 

WELL SPILL VOLUMES

Spill Size Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl Spills 10000-149999 bbl Spills >=150000 bbl

Spill Expectation Low Mode High Expected Low Mode High Expected Low Mode High Expected Low Mode High Expected

Well Spill 50 500 999 519 1000 4500 9999 5292 10000 20000 149999 68349 150000 200000 250000 200000 
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5.1

CHAPTER 5

OIL SPILL OCCURRENCE INDICATOR QUANTIFICATION

5.1 Definition of Oil Spill Occurrence Indicators

Four primary oil spill occurrence indicators (generally referred to as “spill indicators” 

after this) were quantified in this study. These are as follows:

ß Frequency in spills per year.

ß Frequency in spills per barrel produced in each year.

ß Spill index, the product of spill frequency and associated average spill size.

ß Life of field indicators.

The spill indicators defined above are subdivided as follows for this study:

ß By scenario (two scenarios).

ß By water depth (three ranges).

ß By facility type (six types).

ß By spill size (four sizes).

ß By year (2009 to 2044 is 36 years inclusive ).

The above combinations translate into 144 sets of spill indicators per year. Given that 

these are calculated for each year, with the scenario lasting for 36 years, gives 5,184 sets 

of indicators. In this chapter, we will try to summarize only the salient results of the 

indicators; the Appendix 4 gives the full calculation printouts for the Monte Carlo results 

used in the body of this report.

5.2 Oil Spill Occurrence Indicator Calculation Process

The oil spill occurrence indicator calculation process is shown in the flow chart originally 

given in Figure 1.2, and again presented as Figure 5.1. This chapter discusses the spill

occurrence indicator calculations as shown in the shaded rectangle in Figure 5.1. Previous

chapters covered the balance of the items in that figure.

Essentially, this chapter addresses the combining of the development scenarios described 

in Chapter 3 with the unit-spill frequency distributions presented in Chapter 4 to provide 

measures of oil spill occurrence, the oil spill indicators. Although the calculation is 

complex because of the many combinations considered (approximately 5,000), in 

principle, it is a simple process of accounting. Essentially, the quantities of potential oil 

spill sources are multiplied by their appropriate unit oil spill frequency to give the total 

expected spill distributions. To develop the probability distributions by the Monte Carlo

process, each of the 5,000 combinations needs to be sampled, in this case a sampling of 

5,000 iterations was carried out for each combination studied. This translates into roughly 

25 million arithmetic operations to generate the Monte Carlo results.
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5.2

Chapter 5

Figure 5.1

Calculation Flow Chart

Fault Tree Analysis Hazard Scenarios Spill Occurrence

Spill Size

Frequency and Cause Arctic Spill Frequency Annual Annual 

Small Spill 50-99 bbl Shallow Water Depth <10 m Frequency

Medium Water Depth >=10<30 m Frequency per 109

 bbl Produced

<10" Dia

Deep Water Depth >=30<60 m Spill Index 

Medium Spill 100-999 bbl LOF Average Frequency

Pipeline

Large Spill 1000-9999 bbl LOF Av Freq per 109

 bbl Produced

Huge Spill >= 10000 bbl LOF Average Spill Index

>=10" Dia

Small and Medium Spills Shallow Water Depth <10 m

Medium Water Depth >=10<30 m

Deep Water Depth >=30<60 m

Large and Huge Spills

Small and Medium Spills Shallow Water Depth <10 m

Large Spill Medium Water Depth >=10<30 m

Deep Water Depth >=30<60 m

Spill 10000-149999 bbl

Spill >=150000 bbl

Historical Data Analysis

Platform

Chukchi Sea

Non Arctic

Chukchi Sea

Facility

Development Well Drilling

Production Well

Exploration Well Drilling
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5.3

5.3 Summary of Chukchi Sea Oil Spill Occurrence Indicators

5.3.1 Chukchi Sea Oil Spill Occurrence Indicators

Each of the principal oil spill occurrence indicators calculated for the pipelines, 

platforms, and wells under Sale 1 for each year is given in Figures 5.2, 5.3, and 5.4.

As can be seen, each of these figures spans the development scenario to year 2044 as

described in Table 3.3. Further, each of the indicators has been subdivided into three 

segments for each year, those corresponding to spills 50-999 bbl (small and medium), 

spills 1,000-9,999 bbl (large), and spills >=10,000 bbl (huge). It should be noted that the 

spill frequency associated with each spill size is only the shaded increment shown in each 

of the bars. Thus, for example, for the year 2030, small and medium spills are 

approximately 30.0 per thousand years. Next, in that year, large spills are approximately 

13.0 per thousand years, as shown in the second bar increment (i.e., 43.0 – 30.0 = 13.0). 

Finally, the top increment corresponds to huge spills, and is approximately 9.0 per 

thousand years. The same form of presentation applies for spills per barrel produced and 

for the spill index shown in Figures 5.3 and 5.4. For years in which no production exists, 

the spills per barrel produced are not applicable. Clearly, the spill index is dominated by 

the huge spills. The spills per barrel produced continue to rise to the final production year

(2043), because the facility quantities (and hence spill rate) remain relatively high, while 

production volumes decrease significantly each year. The reader should note that 

following this detailed presentation of the spill indicators in separate figures, all three 

spill indicators will be given in one figure in order to conserve space and make the report 

a little more concise. 

Spill indicators by facility type were also quantified. All three spill indicators for 

pipelines are shown in Figure 5.5. Figure 5.6 shows the spill indicators for platforms and 

Figure 5.7 shows the spill indicators for drilling of wells and producing wells. The graph 

ordinate axes have intentionally been kept the same to facilitate comparison. Numerous 

conclusions can be drawn from the comparison of these spill indicators. For example, it 

can be seen that the major contributors to spill frequency are platforms. The largest of the 

facility spill expectations, as represented by spill index, are the wells, simply because 

they have the potential to release the largest amounts of oil in blowouts. 

Finally, as part of the assessment of the Chukchi Sea development scenario, a Monte 

Carlo analysis was carried out for each year, with the distributed inputs described earlier. 

The tabular results of the Monte Carlo simulation of 5,000 iterations, is summarized in 

Table 5.1. This table gives the statistical characteristics of the calculated indicators for 

each of three spill size ranges, as well as a tabular summary of their cumulative 

distribution curves for a representative production year (2024). Figure 5.8 shows graphs 

of the calculated cumulative distribution functions. Basically, the vertical axis gives the

probability in percent that the corresponding value on the horizontal axis will not be 

exceeded. Thus, for example, referring to the central graph, for significant spills >= 1,000 

bbl (large and huge), there is a 50% probability that a spill frequency will be no more 

than 0.25 per billion barrels produced in year 2024.
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5.4

Figure 5.2

Chukchi Sea Spill Frequency per 1,000 Years

(Appendix Figure 4.1.01)

Figure 5.3

Chukchi Sea Spill Frequency per 109 Barrels Produced

(Appendix Figure 4.1.02)

Spill Frequency

0

5

10

15

20

25

30

35

40

45

50

55

200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038203920402041204220432044

Spill Frequency per 1000 years

Huge Spills

=>10000 bbl

Large Spills

1000-9999 bbl

Small and Medium Spills

50-999 bbl

Spill Frequency per 109 bbl Produced

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038203920402041204220432044

Spill Frequency per 10

9 bbl Produced

Huge Spills

=>10000 bbl

Large Spills

1000-9999 bbl

Small and Medium Spills

50-999 bbl
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5.5

Figure 5.4

Chukchi Sea Spill Index

(Appendix Figure 4.1.03)

Spill Index

0

100

200

300

400

500

600

700

800

200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038203920402041204220432044

Spill Index [bbl]

Huge Spills

=>10000 bbl

Large Spills

1000-9999 bbl

Small and Medium Spills

50-999 bbl
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5.6

Figure 5.5

Chukchi Sea Spill Indicators – Pipeline

(Appendix Figures 4.1.04, 4.1.05, 4.1.06)

Spill Frequency - P/L

0

5

10

15

20

25

30

35

40

45

50

55

200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038203920402041204220432044

Spill Frequency per 1000 years

Huge Spills

=>10000 bbl

Large Spills

1000-9999 bbl

Small and Medium Spills

50-999 bbl

Spill Frequency per 109 bbl Produced - P/L

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038203920402041204220432044

Spill Frequency per 10

9 bbl produced

Huge Spills

=>10000 bbl

Large Spills

1000-9999 bbl

Small and Medium Spills

50-999 bbl

Spill Index - P/L

0

100

200

300

400

500

600

700

800

200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038203920402041204220432044

Spill Index [bbl]

Huge Spills

=>10000 bbl

Large Spills

1000-9999 bbl

Small and Medium Spills

50-999 bbl
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

5.7

Figure 5.6

Chukchi Sea Spill Indicators – Platforms

(Appendix Figures 4.1.07, 4.1.08, 4.1.09)

Spill Frequency - Platforms

0

5

10

15

20

25

30

35

40

45

50

55

200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038203920402041204220432044

Spill Frequency per 1000 years

Large and Huge Spills

=>1000 bbl

Small and Medium Spills

50-999 bbl

Spill Frequency per 109 bbl Produced - Platforms

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038203920402041204220432044

Spill Frequency per 10

9 bbl produced

Large and Huge Spills

=>1000 bbl

Small and Medium Spills

50-999 bbl

Spill Index - Platforms

0

100

200

300

400

500

600

700

800

200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038203920402041204220432044

Spill Index [bbl]

Large and Huge Spills

=>1000 bbl

Small and Medium Spills

50-999 bbl
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

5.8

Figure 5.7

Chukchi Sea Spill Indicators – Wells

(Appendix Figures 4.1.10, 4.1.11, 4.1.12)

Spill Frequency - Wells

0

5

10

15

20

25

30

35

40

45

50

55

200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038203920402041204220432044

Spill Frequency per 1000 years

Huge Spills

=>10000 bbl

Large Spills

1000-9999 bbl

Small and Medium Spills

50-999 bbl

Spill Frequency per 109 bbl Produced - Wells

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038203920402041204220432044

Spill Frequency per 10

9 bbl produced

Huge Spills

=>10000 bbl

Large Spills

1000-9999 bbl

Small and Medium Spills

50-999 bbl

Spill Index - Wells

0

100

200

300

400

500

600

700

800

200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038203920402041204220432044

Spill Index [bbl]

Huge Spills

=>10000 bbl

Large Spills

1000-9999 bbl

Small and Medium Spills

50-999 bbl
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

5.9

Table 5.1

Chukchi Sea Year 2024 – Monte Carlo Results (App. Table 4.1.14)

Year 2024

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

Significant Spills

=>1000 bbl

All Spills

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

Significant Spills

=>1000 bbl

All Spills

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

Significant Spills

=>1000 bbl

All Spills

Frequency

Spills per 103years

Frequency

Spills per 109 bbl Produced Spill Index [bbl]

Mean = 28.62 13.25 9.00 22.24 50.86 0.35 0.16 0.11 0.27 0.62 11.85 90.75 681.33 772.08 783.93

Std Deviation = 9.58 5.70 2.40 6.73 12.77 0.12 0.07 0.03 0.08 0.16 6.57 45.99 244.70 251.14 251.46

Variance = 91.791 32.506 5.743 45.293 163.102 0.014 0.005 0.001 0.007 0.024 43.199 2115.125 59877.300 63068.880 63234.000

Skewness = 0.57 1.10 0.55 0.83 0.54 0.57 1.10 0.55 0.83 0.54 1.21 1.23 0.60 0.59 0.59

Kurtosis = 3.24 4.37 3.33 3.82 3.29 3.24 4.37 3.33 3.82 3.29 4.92 5.54 3.45 3.44 3.44

Mode = 25.37 11.35 7.34 34.77 46.61 0.31 0.14 0.09 0.42 0.57 13.68 72.01 592.71 385.11 808.80

Minimum = 6.959 2.233 2.698 7.478 19.166 0.085 0.027 0.033 0.091 0.234 0.070 7.189 122.468 190.640 201.190

5% Perc = 14.801 6.186 5.498 13.138 31.932 0.180 0.075 0.067 0.160 0.389 3.883 31.924 322.006 406.207 416.050

10% Perc = 17.026 7.118 6.143 14.641 35.23 4 0.208 0.087 0.075 0.179 0.430 4.891 40.694 389.326 468.625 481.656

15% Perc = 18.780 7.812 6.565 15.653 37.731 0.229 0.095 0.080 0.191 0.460 5.644 47.454 436.771 520.138 530.393

20% Perc = 20.186 8.445 6.931 16.547 39.950 0.246 0.103 0.085 0.202 0.487 6.364 52.287 474.957 556.814 568.368

25% Perc = 21.421 9.056 7.289 17.285 41.730 0.261 0.110 0.089 0.211 0.509 7.047 57.930 506.613 591.448 603.815

30% Perc = 22.786 9.614 7.577 18.136 43.264 0.278 0.117 0.092 0.221 0.528 7.687 62.830 535.962 624.978 636.837

35% Perc = 24.053 10.251 7.881 18.906 45.020 0.293 0.125 0.096 0.231 0.549 8.330 67.786 566.772 654.256 666.580

40% Perc = 25.298 10.804 8.171 19.616 46.469 0.309 0.132 0.100 0.239 0.567 8.939 72.357 594.537 683.643 695.143

45% Perc = 26.372 11.402 8.452 20.381 48.104 0.322 0.139 0.103 0.249 0.587 9.694 77.248 624.378 716.518 728.524

50% Perc = 27.659 12.074 8.747 21.222 49.564 0.337 0.147 0.107 0.259 0.604 10.457 82.870 655.379 747.614 760.963

55% Perc = 28.854 12.696 9.047 22.026 51.248 0.352 0.155 0.110 0.269 0.625 11.293 88.617 687.216 779.291 791.385

60% Perc = 30.179 13.465 9.348 22.850 52.923 0.368 0.164 0.114 0.279 0.645 12.053 94.054 720.446 811.147 823.953

65% Perc = 31.604 14.284 9.662 23.826 54.763 0.385 0.174 0.118 0.291 0.668 12.949 99.517 754.067 844.205 856.545

70% Perc = 32.981 15.279 10.064 24.871 56.785 0.402 0.186 0.123 0.303 0.692 13.900 106.880 785.081 880.688 891.481

75% Perc = 34.572 16.337 10.461 26.089 58.812 0.422 0.199 0.128 0.318 0.717 15.164 113.996 826.945 922.591 933.668

80% Perc = 36.468 17.475 10.946 27.449 61.204 0.445 0.213 0.133 0.335 0.746 16.602 123.177 875.826 971.241 983.217

85% Perc = 38.630 19.073 11.507 29.141 64.459 0.471 0.233 0.140 0.355 0.786 18.547 135.503 936.725 1030.085 1040.930

90% Perc = 41.498 20.957 12.236 31.377 68.218 0.506 0.256 0.149 0.383 0.832 20.683 149.750 1008.444 1114.361 1129.230

95% Perc = 45.695 24.519 13.366 34.951 73.336 0.557 0.299 0.163 0.426 0.894 24.617 175.429 1123.291 1221.134 1231.424

Maximum = 71.083 40.789 19.820 54.524 113.299 0.867 0.497 0.242 0.665 1.382 54.955 342.292 1813.537 1897.859 1904.195
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

5.10

Figure 5.8

Chuckchi SeaSpill Indicator Distributions – Year 2024

(Appendix Figure 4.1.13)

 Spill Frequency - CDF Year 2024

0

10

20

30

40

50

60

70

80

90

100

0 10 20 30 40 50 60 70

Spill Frequency per 1000 years

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

 Spill Frequency - CDF Year 2024

0

10

20

30

40

50

60

70

80

90

100

0 10 20 30 40 50 60 70 80 90 100 110

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills

 Spill Frequency per bbl Produced - CDF Year 2024

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9

Spill Frequency per 10^9 bbl Produced

CDF %Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

 Spill Frequency per bbl Produced - CDF Year 2024

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4

Spill Frequency per 10^9 bbl Produced

CDF %

Significant Spills

=>1000 bbl

All Spills

 Spill Index - CDF Year 2024

0

10

20

30

40

50

60

70

80

90

100

0 200 400 600 800 1000 1200 1400 1600 1800

Spill Index [bbl]

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

 Spill Index - CDF Year 2024

0

10

20

30

40

50

60

70

80

90

100

0 200 400 600 800 1000 1200 1400 1600 1800

Spill Index [bbl]

CDF %

Significant Spills

=>1000 bbl

All Spills
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

5.11

In other words, there is a 50% chance that large and huge spills will occur at a rate of 

0.25 per billion bbl or less. 

The frequency spill indicator variability can be estimated from the upper (95%) and 

lower (5%) bound values. For example, for large spill frequency (from Table 5.1), the 

lower bound (6.186) is 48% of the mean (12.074); the upper bound (24.579), 103% of the 

mean.

In addition, since the Life of Field (LOF) averages were calculated, results from these are 

available for each scenario. Only selected ones are given in the text, with the balance 

given in the appendix. Table 5.2 shows the composition of the spill indicators for the Sale 

1 Life of Field average. The composition both by spill size (on the left hand side of the 

table) and by facility contribution (on the right hand side of the table). The variability of 

the spill frequencies Life of Field averages is shown in the following figures: Figure 5.9 

illustrates the variability of the spill frequency, while Figure 5.10 shows variability of

frequency per billion barrels produced.

5.3.2 Comparative Non-Arctic Indicator Assessment

To give an idea of the effect of the frequency variations introduced in Chapter 4, the 

Chukchi Sea scenario was also modeled utilizing unaltered historical frequencies. That is, 

no changes to incorporate the Arctic effects were introduced in the spill indicator 

calculations. Put yet another way, it was assumed that the facilities of the scenario would 

behave as if they were in the Gulf of Mexico environment rather than in the Arctic 

environment. Figures 5.11, 5.12, and 5.13 show the total values calculated for each of the 

three spill indicators. The dark histogram bar on the right side corresponds to the Arctic 

spill indicator, while that, on the left, corresponds to the computation based on historical 

frequencies only. Spill frequency in an absolute sense is significantly reduced for the 

Arctic situation roughly by 32%. The spills per barrel produced are also significantly 

reduced, as can be seen in Figures 5.14 and 5.15. The spill index (Figure 5.13), because 

of the disproportionate effect of large spills, shows a reduction of approximately 34%. 

What the comparison shows is that the Arctic development scenarios can be expected to 

have a lower oil spill occurrence rate than similar development scenarios in the GOM.
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

5.12

Table 5.2

Composition of Spill Indicators –Life of Field Average (App. Table 4.1.21)

Spill Source Spill Size

P/L Platforms Wells Platforms

and Wells All

S+M

50-999

bbl

Large

1000-9999

bbl

Huge

 =>10000

bbl

Significant

=>1000

bbl

All Spills Spill Size

LOF Average - Spill Frequency per 10^3 years

Spill Source

 LOF Average - Spill Frequency per 10^3 years

Small and Medium Spills

50-999 bbl 11.854 58% 6.296 86% 0.599 11% 6.895 54% 18.750 57% P/L 11.854 63% 6.404 73% 2.042 37% 8.446 59% 20.301 61%

Large Spills

1000-9999 bbl 6.404 32% 0.533 7% 1.798 33% 2.331 18% 8.735 26% Platforms 6.296 34% 0.533 6% 0.533 10% 1.066 7% 7.362 22%

Huge Spills

 =>10000 bbl 2.042 10% 0.533 7% 3.004 56% 3.536 28% 5.578 17% Wells 0.599 3% 1.798 21% 3.004 54% 4.802 34% 5.401 16%

Significant Spills

=>1000 bbl 8.446 42% 1.066 14% 4.802 89% 5.867 46% 14.313 43% Platformsand Wells 6.895 37% 2.331 27% 3.536 63% 5.867 41% 12.763 39%

All Spills 20.301 100% 7.362 100% 5.401 100% 12.763 100% 33.063 100% All 18.750 100% 8.735 100% 5.578 100% 14.313 100% 33.063 100%

LOF Average - Spill Frequency per 10^9 bbl produced LOF Average - Spill Frequency per 10^9 bbl produced

Small and Medium Spills

50-999 bbl 0.427 58% 0.227 86% 0.022 11% 0.248 54% 0.675 57% P/L 0.427 63% 0.230 73% 0.073 37% 0.304 59% 0.730 61%

Large Spills

1000-9999 bbl 0.230 32% 0.019 7% 0.065 33% 0.084 18% 0.314 26% Platforms 0.227 34% 0.019 6% 0.019 10% 0.038 7% 0.265 22%

Huge Spills

 =>10000 bbl 0.073 10% 0.019 7% 0.108 56% 0.127 28% 0.201 17% Wells 0.022 3% 0.065 21% 0.108 54% 0.173 34% 0.194 16%

Significant Spills

=>1000 bbl 0.304 42% 0.038 14% 0.173 89% 0.211 46% 0.515 43% Platformsand Wells 0.248 37% 0.084 27% 0.127 63% 0.211 41% 0.459 39%

All Spills 0.730 100% 0.265 100% 0.194 100% 0.459 100% 1.190 100% All 0.675 100% 0.314 100% 0.201 100% 0.515 100% 1.190 100%

LOF Average - Spill Index [bbl] LOF Average - Spill Index [bbl]

Small and Medium Spills

50-999 bbl 5 7% 3 32% 0 0% 3 1% 8 2% P/L 5 59% 33 57% 31 8% 65 14% 69 15%

Large Spills

1000-9999 bbl 33 48% 3 34% 22 6% 25 6% 58 13% Platforms 3 37% 3 5% 3 1% 6 1% 9 2%

Huge Spills

 =>10000 bbl 31 46% 3 34% 365 94% 368 93% 399 86% Wells 0 4% 22 38% 365 91% 387 85% 387 83%

Significant Spills

=>1000 bbl 65 93% 6 68% 387 100% 393 99% 457 98% Platformsand Wells 3 41% 25 43% 368 92% 393 86% 396 85%

All Spills 69 100% 9 100% 387 100% 396 100% 465 100% All 8 100% 58 100% 399 100% 457 100% 465 100%
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

5.13

Figure 5.9

Chukchi Sea Life of Field Average Spill Frequency

(Appendix Figure 4.1.14)

CDF LOF Average - Pipeline

0

10

20

30

40

50

60

70

80

90

100

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28

Spill Frequency per 1000 years

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - Platforms

0

10

20

30

40

50

60

70

80

90

100

0 2 4 6 8 10 12 14 16 18 20

Spill Frequency per 1000 years

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - Pipeline

0

10

20

30

40

50

60

70

80

90

100

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF LOF Average - Platforms

0

10

20

30

40

50

60

70

80

90

100

0 2 4 6 8 10 12 14 16 18 20

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

0 1 2 3 4 5 6

Spill Frequency per 1000 years

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

0 1 2 3 4 5 6 7 8 9 10

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

5.14

Figure 5.10

Chukchi Sea Life of

Field Average Spills

per Barrel Produced

(Appendix 

Figure 4.1.15)

CDF LOF Average - Pipeline

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Spill Frequency per 10^9 bbl Produced

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - Pipeline

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4

Spill Frequency per 10^9 bbl Produced

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF LOF Average - Platforms

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

Spill Frequency per 10^9 bbl Produced

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - Platforms

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Spill Frequency per 10^9 bbl Produced

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

0.00 0.05 0.10 0.15 0.20

Spill Frequency per 10^9 bbl Produced

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35

Spill Frequency per 10^9 bbl Produced

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF LOF Average - Platforms + Wells

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

Spill Frequency per 10^9 bbl Produced

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - Platforms + Wells

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Spill Frequency per 10^9 bbl Produced

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF LOF Average - All

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5

Spill Frequency per 10^9 bbl Produced

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - All

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8

Spill Frequency per 10^9 bbl Produced

CDF %

Significant Spills

=>1000 bbl

All Spills
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

5.15

Figure 5.11

Chukchi Sea Spill Frequency – Arctic and Non-Arctic

(Appendix Figure 5.3)

Figure 5.12

Chukchi Sea Spill Frequency per 109 Barrels Produced – Arctic and Non-Arctic

(Appendix Figure 5.4)

Chukchi Sea Spill Frequency

0

5

10

15

20

25

30

35

40

45

50

55

60

65

70

75

80

200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038203920402041204220432044

Spill Frequency per 1000 years

Non Arctic Spills

Arctic Spills

Chukchi Sea Spill Frequency per 109 bbl Produced

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

4.5

5.0

5.5

6.0

6.5

7.0

7.5

200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038203920402041204220432044

Spill Frequency per 10

9 bbl Produced

Non Arctic Spills

Arctic Spills
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

5.16

Figure 5.13

Chukchi Sea Spill Index – Arctic and Non-Arctic

(Appendix Figure 5.5)

Chukchi Sea Spill Index

0

100

200

300

400

500

600

700

800

900

1000

1100

1200

200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038203920402041204220432044

Spill Index [bbl]

Non Arctic Spills

Arctic Spills
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

5.17

Table 5.3

Summary of Life of Field Average Spill Indicators by Spill Source and Size

(App Table 5.1)

Chukchi Sea Chukchi Sea - Non Arctic

Spill Indicators

LOF Average

Spill Frequency 

per 10^3 years

Spill Frequency 

per 10^9 bbl 

produced

Spill Index [bbl]Spill Frequency 

per 10^3 years

Spill Frequency 

per 10^9 bbl 

produced

Spill Index [bbl]

Small and Medium Spills 18.750 0.675 8 26.111 0.940 11

50-999 bbl 57% 57% 2% 53% 53% 2%

8.735 0.314 58 14.808 0.533 95 Large Spills

1000-9999 bbl 26% 26% 13% 30% 30% 14%

5.578 0.201 399 8.593 0.309 574 Huge Spills

=>10000 bbl 17% 17% 86% 17% 17% 84%

14.313 0.515 458 23.401 0.842 669 Significant Spills

=>1000 bbl 43% 43% 98% 47% 47% 98%

33.063 1.190 465 49.512 1.782 680

All Spills

100% 100% 100% 100% 100% 100%

20.301 0.730 69 33.248 1.196 125

Pipeline Spills

61% 61% 15% 67% 67% 18%

7.362 0.265 9 8.668 0.312 10

Platform Spills

22% 22% 2% 18% 18% 2%

5.401 0.194 387 7.595 0.273 544

Well Spills

16% 16% 83% 15% 15% 80%

12.763 0.459 396 16.264 0.585 554

Platform and Well Spills

39% 39% 85% 33% 33% 82%

33.063 1.190 465 49.512 1.782 680

All Spills

100% 100% 100% 100% 100% 100%
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

5.18

Figure 5.14

Life of Field Spill Indicators – By Spill Size

(Appendix Figure 5.1)

Life of Field Average

0

10

20

30

40

50

Spill Frequency

per 1000 years

Huge Spills

=>10000 bbl

5.578 8.593

Large Spills

1000-9999 bbl

8.735 14.808

Small and Medium Spills

50-999 bbl

18.750 26.111

Chukchi Sea Chukchi Sea - Non Arctic

Life of Field Average

0.0

0.5

1.0

1.5

2.0

Spill Frequency

 per 10^9 bbl produced

Huge Spills

=>10000 bbl

0.201 0.309

Large Spills

1000-9999 bbl

0.314 0.533

Small and Medium Spills

50-999 bbl

0.675 0.940

Chukchi Sea Chukchi Sea - Non Arctic

Life of Field Average

0

100

200

300

400

500

600

700

Spill Index [bbl]

Huge Spills

=>10000 bbl

399 574

Large Spills

1000-9999 bbl

58 95

Small and Medium Spills

50-999 bbl

8 11

Chukchi Sea Chukchi Sea - Non Arctic
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

5.19

Figure 5.15

Life of Field Spill Indicators – By Source Composition

(Appendix Figure 5.2)

Life of Field Average

0

10

20

30

40

50

Spill Frequency

per 1000 years

Well Spills 5.401 7.595

Platform Spills 7.362 8.668

Pipeline Spills 20.301 33.248

Chukchi Sea Chukchi Sea - Non Arctic

Life of Field Average

0.0

0.5

1.0

1.5

2.0

Spill Frequency

 per 10^9 bbl produced

Well Spills 0.194 0.273

Platform Spills 0.265 0.312

Pipeline Spills 0.730 1.196

Chukchi Sea Chukchi Sea - Non Arctic

Life of Field Average

0

100

200

300

400

500

600

700

Spill Index [bbl]

Well Spills 387 544

Platform Spills 9 10

Pipeline Spills 69 125

Chukchi Sea Chukchi Sea - Non Arctic
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

5.20

5.4 Summary of Representative Oil Spill Occurrence Indicator Results

How do spill indicators for the Chukchi scenario and for its non-Arctic counterpart vary 

by spill size and location? Table 5.3 summarizes the Life of Field average spill indicator 

values by spill source and size. The following can be observed from Table 5.3. 

ß Spill frequency per year and per barrel-year decreases significantly with 

increasing spill size for all scenarios. 

ß The spill index increases significantly with spill size for both scenarios.

ß All non-Arctic scenario spill indicators are greater than their Arctic 

counterparts. Non-Arctic spill indicators are approximately 30% greater.

How do the spill indicators vary by facility type for representative scenarios? The 

contributions of spill indicators by facility have been summarized by representative 

scenario years, again, in Table 5.3 and also in Figure 5.15. Table 5.3 and Figure 5.15 give

the component contributions, in absolute value and percent, for each of the main facility 

types; namely, pipelines (P/L), platforms, and wells. The following may be noted from 

Table 5.3:

ß Pipelines contribute the most (61%) to the two spill frequency indicators. 

ß Platforms are next in relative contribution to spill frequencies (22%) and least

in contribution to spill index (2%). 

ß Wells are by far (at 83%) the highest contributors to spill index, while 

platforms and wells together are responsible for a 82% contribution to the spill 

index. 

ß It can be concluded that pipelines are likely to have the most, but smaller 

spills, while wells will have the least number, but largest spills. Platforms will 

be in between, with a tendency towards more spills than wells, but less or 

about the same number as platforms.

Figures 5.16 and 5.17 show relative contributions by facility and spill size to the 

maximum production year 2024 and Life of Field average spill indicators, respectively. 

Although Life of Field average absolute values are significantly smaller than the 

maximum production year values, the proportional contributions by spill facility source 

and spill size are almost identical. In Figures 5.16 and 5.17, “TOTAL” designates the 

sum of the spill indicators for all spill sizes and facility types. 
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

5.21

BY SPILL SOURCE BY SPILL SIZE

Figure 5.16

Chukchi Sea – Year 2024 – Spill Indicator Composition by Source and Spill Size

(Appendix Figure 4.1.17)

Year 2024

 Spill Frequency per 10^3 years

24%

58%

18%

P/L

Platforms

Wells TOTAL 50.847

Year 2024

 Spill Frequency per 10^9 bbl produced

24%

58%

18%

P/L

Platforms

Wells TOTAL 0.620

Year 2024

 Spill Index [bbl]

85%

2% 13%

P/L

Platforms

Wells TOTAL 785

Year 2024

 Spill Frequency per 10^3 years

56%

26%

18%

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

 =>10000 bbl

TOTAL 50.847

Year 2024

 Spill Frequency per 10^9 bbl produced

26%

56%

18%

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

 =>10000 bbl

TOTAL 0.620

Year 2024

 Spill Index [bbl]

2%

86%

12%

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

 =>10000 bbl

TOTAL 785
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

5.22

BY SPILL SOURCE BY SPILL SIZE

Figure 5.17

Chukchi Sea – Life of Field Average Spill Indicator Composition by Source and Spill Size

(Appendix Figure 4.1.18)

LOF Average

 Spill Frequency per 10^3 years

62%

16%

22%

P/L

Platforms

Wells TOTAL 33.063

LOF Average

 Spill Frequency per 10^9 bbl produced

62%

16%

22%

P/L

Platforms

Wells TOTAL 1.190

LOF Average

 Spill Frequency per 10^9 bbl produced

57%

26%

17%

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

 =>10000 bbl

TOTAL 1.190

LOF Average

 Spill Frequency per 10^3 years

57%

17%

26%

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

 =>10000 bbl

TOTAL 33.063

LOF Average

 Spill Index [bbl]

15%

2%

83%

P/L

Platforms

Wells TOTAL 465

LOF Average

 Spill Index [bbl]

2%

13%

85%

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

 =>10000 bbl

TOTAL 465
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

5.23

Figures 5.18, 5.19, and 5.20 show the Cumulative Distribution Functions (CDF) for the 

Chukchi Sea Life of Field average spill indicators. The variability of these indicators is 

fairly representative of the trends in variability for spill indicators for all sales and 

locations studied. Generally, the following can be observed from the figures:

ß The variance of the frequency spill indicators (Figures 5.18 and 5.19) 

decreases as spill size increases for pipelines and platforms. In other words, 

small and medium spills illustrate the largest variability; huge spills show the 

least variability for these facilities. 

ß The opposite occurs for wells.

ß The variability of the spill index (Figure 5.20) shows the opposite trend for 

pipelines and platforms. 

The Cumulative Distribution Functions contain extensive information on the statistical 

properties of the spill indicators. For example, from Figure 5.18, it can be seen, for all 

significant spills, that the Life of Field average mean (50%) value of 14 (spills per 1,000 

years) ranges between 23 and 7 at the upper and lower 95% confidence intervals. A 

similar percentage variation is shown for the Life of Field average spill frequency per 

barrel produced in Figure 5.19. The spill index variability shown in Figure 5.20 is 

proportionally higher. For example, in Figure 5.20, the mean value of the significant 

spills index of 450 per billion barrels produced ranges from 250 to 700.
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

5.24

Figure 5.18

Chukchi Sea Life of Field Average Spill Frequency – CDF

(Appendix Figure 4.1.14)

CDF LOF Average - Pipeline

0

10

20

30

40

50

60

70

80

90

100

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28

Spill Frequency per 1000 years

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - Platforms

0

10

20

30

40

50

60

70

80

90

100

0 2 4 6 8 10 12 14 16 18 20

Spill Frequency per 1000 years

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - Pipeline

0

10

20

30

40

50

60

70

80

90

100

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF LOF Average - Platforms

0

10

20

30

40

50

60

70

80

90

100

0 2 4 6 8 10 12 14 16 18 20

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

0 1 2 3 4 5 6

Spill Frequency per 1000 years

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - Platforms + Wells

0

10

20

30

40

50

60

70

80

90

100

0 2 4 6 8 10 12 14 16 18 20

Spill Frequency per 1000 years

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

0 1 2 3 4 5 6 7 8 9 10

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF LOF Average - Platforms + Wells

0

10

20

30

40

50

60

70

80

90

100

0 2 4 6 8 10 12 14 16 18 20 22 24 26

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF LOF Average - All

0

10

20

30

40

50

60

70

80

90

100

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40

Spill Frequency per 1000 years

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - All

0

10

20

30

40

50

60

70

80

90

100

0 5 10 15 20 25 30 35 40 45 50 55

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

5.25

Figure 5.19

Chukchi Sea Life of Field Average Spill Frequency per Barrel Produced – CDF

(Appendix Figure 4.1.15)

CDF LOF Average - Pipeline

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

Spill Frequency per 10^9 bbl Produced

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - Platforms

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

Spill Frequency per 10^9 bbl Produced

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - Pipeline

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4

Spill Frequency per 10^9 bbl Produced

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF LOF Average - Platforms

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Spill Frequency per 10^9 bbl Produced

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

0.00 0.05 0.10 0.15 0.20

Spill Frequency per 10^9 bbl Produced

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - Platforms + Wells

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7

Spill Frequency per 10^9 bbl Produced

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35

Spill Frequency per 10^9 bbl Produced

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF LOF Average - Platforms + Wells

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

Spill Frequency per 10^9 bbl Produced

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF LOF Average - All

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5

Spill Frequency per 10^9 bbl Produced

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - All

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8

Spill Frequency per 10^9 bbl Produced

CDF %

Significant Spills

=>1000 bbl

All Spills
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

5.26

Figure 5.20

Chukchi Sea Life of Field Average Spill Index (bbl) – CDF

(Appendix Figure 4.1.16)

CDF LOF Average - Pipeline

0

10

20

30

40

50

60

70

80

90

100

0 10 20 30 40 50 60 70 80 90 100 110 120

Spill Index [bbl]

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - Platforms

0

10

20

30

40

50

60

70

80

90

100

0 2 4 6 8 10 12 14 16 18 20

Spill Index [bbl]

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - Pipeline

0

10

20

30

40

50

60

70

80

90

100

0 10 20 30 40 50 60 70 80 90 100 110 120 130 140

Spill Index [bbl]

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF LOF Average - Platforms

0

10

20

30

40

50

60

70

80

90

100

0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30

Spill Index [bbl]

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

0 100 200 300 400 500 600 700 800 900

Spill Index [bbl]

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - Platforms + Wells

0

10

20

30

40

50

60

70

80

90

100

0 100 200 300 400 500 600 700 800 900

Spill Index [bbl]

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

0 100 200 300 400 500 600 700 800 900

Spill Index [bbl]

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF LOF Average - Platforms + Wells

0

10

20

30

40

50

60

70

80

90

100

0 100 200 300 400 500 600 700 800 900

Spill Index [bbl]

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF LOF Average - All

0

10

20

30

40

50

60

70

80

90

100

0 100 200 300 400 500 600 700 800 900 1000

Spill Index [bbl]

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF LOF Average - All

0

10

20

30

40

50

60

70

80

90

100

0 100 200 300 400 500 600 700 800 900 1000

Spill Index [bbl]

CDF %

Significant Spills

=>1000 bbl

All Spills
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

6.1

CHAPTER 6

CONCLUSIONS AND RECOMMENDATIONS

6.1 Conclusions

6.1.1 General Conclusions

Oil spill occurrence indicators were quantified for future offshore development scenarios 

in the Chukchi Sea in the area of MMS jurisdiction. The quantification included the 

consideration of the variability of historical and future scenario data, as well as that of 

Arctic effects in predicting oil spill occurrence indicators. Consideration of the variability 

of all input data yields both higher variability and a higher expected value of the spill 

occurrence indicators. The three types of spill occurrence indicators were: annual oil spill 

frequency, annual oil spill frequency per billion barrels produced, and annual spill index 

– and, additionally, the life of field averages for each of these three oil spill indicators 

were assessed.

6.1.2 Oil Spill Occurrence Indicators by Spill Size

How do spill indicators for the different scenarios and for their non-Arctic counterparts 

vary by spill size and source? Table 6.1 summarizes the Life of Field (LOF) average spill 

indicator values. Figure 6.1 illustrates these. The following can be observed from Table 

6.1.

ß Spill frequency per year and per barrel-year decreases significantly with 

increasing spill size for all scenarios. 

ß The spill index increases significantly with spill size for both scenarios.

ß All non-Arctic scenario spill indicators are greater than their Arctic 

counterparts. Non-Arctic spill indicators are approximately 30% greater.
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

6.2

Table 6.1

Summary of Life of Field Average Spill Indicators by Spill Source and Size

Chukchi Sea Chukchi Sea - Non Arctic

Spill Indicators

LOF Average

Spill Frequency 

per 10^3 years

Spill Frequency 

per 10^9 bbl 

produced

Spill Index [bbl]Spill Frequency 

per 10^3 years

Spill Frequency 

per 10^9 bbl 

produced

Spill Index [bbl]

Small and Medium Spills 18.750 0.675 8 26.111 0.940 11

50-999 bbl 57% 57% 2% 53% 53% 2%

8.735 0.314 58 14.808 0.533 95 Large Spills

1000-9999 bbl 26% 26% 13% 30% 30% 14%

5.578 0.201 399 8.593 0.309 574 Huge Spills

=>10000 bbl 17% 17% 86% 17% 17% 84%

14.313 0.515 458 23.401 0.842 669 Significant Spills

=>1000 bbl 43% 43% 98% 47% 47% 98%

33.063 1.190 465 49.512 1.782 680

All Spills

100% 100% 100% 100% 100% 100%

20.301 0.730 69 33.248 1.196 125

Pipeline Spills

61% 61% 15% 67% 67% 18%

7.362 0.265 9 8.668 0.312 10

Platform Spills

22% 22% 2% 18% 18% 2%

5.401 0.194 387 7.595 0.273 544

Well Spills

16% 16% 83% 15% 15% 80%

12.763 0.459 396 16.264 0.585 554

Platform and Well Spills

39% 39% 85% 33% 33% 82%

33.063 1.190 465 49.512 1.782 680

All Spills

100% 100% 100% 100% 100% 100%
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

6.3

Figure 6.1

Life of Field Spill Indicators – By Spill Size

Life of Field Average

0

10

20

30

40

50

Spill Frequency

per 1000 years

Huge Spills

=>10000 bbl

5.578 8.593

Large Spills

1000-9999 bbl

8.735 14.808

Small and Medium Spills

50-999 bbl

18.750 26.111

Chukchi Sea Chukchi Sea - Non Arctic

Life of Field Average

0.0

0.5

1.0

1.5

2.0

Spill Frequency

 per 10^9 bbl produced

Huge Spills

=>10000 bbl

0.201 0.309

Large Spills

1000-9999 bbl

0.314 0.533

Small and Medium Spills

50-999 bbl

0.675 0.940

Chukchi Sea Chukchi Sea - Non Arctic

Life of Field Average

0

100

200

300

400

500

600

700

Spill Index [bbl]

Huge Spills

=>10000 bbl

399 574

Large Spills

1000-9999 bbl

58 95

Small and Medium Spills

50-999 bbl

8 11

Chukchi Sea Chukchi Sea - Non Arctic
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

6.4

6.1.3 Oil Spill Occurrence Indicators by Spill Source

How do the spill indicators vary by spill source facility type for representative scenarios? 

The contributions of spill indicators by source facility have been summarized by Life of 

Field averages, in Table 6.1 and also in Figure 5.15. Table 6.1 and Figure 5.15 give the 

component contributions, in absolute value and percent, for each of the main facility 

types; namely, pipelines (P/L), platforms, and wells. The following may be noted from 

Table 6.1:

ß Pipelines contribute the most (61%) to the two spill frequency indicators. 

ß Platforms are next in relative contribution to spill frequencies (22%) and least

in contribution to spill index (2%). 

ß Wells are by far (at 83%) the highest contributors to spill index, while 

platforms and wells together are responsible for a 82% contribution to the spill 

index. 

ß It can be concluded that pipelines are likely to have the most, but smaller 

spills, while wells will have the least number, but largest spills. Platforms will 

be in between, with a tendency towards more spills than wells, but less or 

about the same number as platforms.

Figures 5.16 and 5.17 show relative contributions by facility and spill size to the 

maximum production year 2024 and Life of Field average spill indicators, respectively. 

Although Life of Field average spill indicator absolute values are significantly smaller 

than the maximum production year values, the proportional contributions by spill facility 

source and spill size are almost identical. 

6.1.4 Variability of Oil Spill Occurrence Indicators

Figures 5.18, 5.19, and 5.20 show the Cumulative Distribution Functions for each of the 

Chukchi Sea Life of Field average spill indicators by spill size and source. Generally, the 

following can be observed from the figures:

ß The variance of the frequency spill indicators (Figures 5.18 and 5.19) 

decreases as spill size increases for pipelines and platforms. In other words, 

small and medium spills illustrate the largest variability; huge spills show the 

least variability for these facilities. 

ß The opposite occurs for wells.

ß The variability of the spill index (Figure 5.20) shows the opposite trend for 

pipelines and platforms. 
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6.5

The Cumulative Distribution Functions contain extensive information on the statistical 

properties of the spill indicators. For example, from Figure 5.18, it can be seen, for all 

significant spills, that the Life of Field average mean (50%) value of 14 (spills per 1,000 

years) ranges between 23 and 7 at the upper and lower 95% confidence intervals. A 

similar percentage variation is shown for the Life of Field average spill frequency per 

barrel produced in Figure 5.19. The spill index variability shown in Figure 5.20 is 

proportionally higher. For example, in Figure 5.20, the mean value of the significant 

spills index of 450 per billion barrels produced ranges from 250 to 700. 

6.2 Conclusions on the Methodology and its Applicability

An analytical tool for the prediction of oil spill occurrence indicators for systems without 

history, such as future offshore oil production developments in the Chukchi Sea, has been 

developed based on the utilization of fault tree methodology. Although the results 

generated are voluminous, they are essentially transparent, simple, and easy to 

understand. The analytical tool developed is also quite transparent, very efficient in terms 

of computer time and input-output capability. In addition, the predictive model is setup so 

that any input variables can be entered as distributions. 

A wealth of information that can be utilized for the optimal planning and regulation of 

future developments is generated by the analytical tool. Key aspects of the analytical tool 

capability may be summarized as follows:

ß Ability to generate expected and mean values as well as their variability in 

rigorous numerical statistical format.

ß Use of verifiable input data based on MMS or other historical spill data and 

statistics.

ß Ability to independently vary the impacts of different causes on the spill 

occurrences as well as add new causes such as some of those that may be 

expected for the Arctic or other new environments.

ß Ability to generate spill occurrence indicator characteristics such as annual 

variations, facility contributions, spill size distributions, and life of field (Life of 

Field) averages. 

ß Ability to generate comparative spill occurrence indicators such as those of 

comparable scenarios in more temperate regions. The model developed provides a 

basis for estimating each Arctic effect’s importance through sensitivity analysis as 

well as propagation of uncertainties. 

ß Capability to quantify uncertainties rigorously, together with their measures of 

variability.
Chukchi Oil Spill Estimators Final Report – P2507

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6.6

6.3 Limitations of the Methodology and Results

During the work, a number of limitations in the input data, the scenarios, the application 

of the fault tree methodology, and finally the oil spill occurrence indicators themselves 

have been identified. These shortcomings are summarized in the following paragraphs.

Two categories of input data were used; namely the historical spill data and the Arctic 

effect data. Although a verifiable and optimal historical spill data set has been used, the 

following shortcomings may be noted:

ß Gulf of Mexico (OCS) historical data bases were provided by MMS for 

pipelines and facilities, and were used as a starting point for the fault tree 

analysis. Although these data are adequate, a broader population base would 

give more robust statistics. Unfortunately, data from a broader population 

base, such as the North Sea, do not contain the level of detail provided in the 

GOM data. 

ß The Arctic effects include modifications in causes associated with the 

historical data set as well as additions of spill causes unique to the Arctic 

environment. Quantification of existing causes for Arctic effects was done in a 

relative cursory way restricted to engineering judgment. 

ß Upheaval buckling effect assessments were included on the basis of an 

educated guess; no engineering analysis was carried out for the assessment of 

frequencies to be expected for these effects. 

ß A reproducible but relatively elementary analysis of gouging and scour effects 

was carried out. 

The scenarios are those developed for use in the MMS Alaska OCS Region 

Environmental Impact Statements for Oil and Gas Lease Sales. As estimated they appear 

reasonable and were incorporated in the form provided. 

ß The only shortcoming appears to be that the facility abandonment rate is 

significantly lower than the rate of decline in production.

The following comments can be made on limitations associated with the indicators that 

have been generated: 

ß The indicators have inherited the deficiencies of the input and scenario data 

noted above. 

ß The model generating the indicators is fundamentally a linear model which 

ignores the effects of scale, of time variations such as the learning and wearout curves (Bathtub curve), and production volume non-linear effects. 
Chukchi Oil Spill Estimators Final Report – P2507

MMS Contract No.: 1435-01-05-CT-39348

October, 2006

6.7

6.4 Recommendations

The following recommendations based on the work may be made:

ß Continue to utilize the Monte Carlo spill occurrence indicator model for new 

scenarios to support MMS needs, as it is currently the best predictive spill 

occurrence model available.

ß Utilize the oil spill occurrence indicator model to generate additional model 

validation information, including direct application to specific non-Arctic 

scenarios, such as GOM projects, which have an oil spill statistical history.

ß Utilize the oil spill occurrence indicator model in a sensitivity mode to 

identify the importance of different Arctic effect variables introduced to 

provide a prioritized list of those items having the highest potential impact on 

Arctic oil spills. 

ß Generalize the model so that it can be run both in an adjusted expected value 

and a distributed value (Monte Carlo) form with the intent that expected value 

form can be utilized without the Monte Carlo add-in for preliminary estimates 

and sensitivity analyses, while for more comprehensive rigorous studies, the 

Monte Carlo version can be used.
Chukchi Oil Spill Estimators R.1 Final Report – P2507

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October, 2006

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The Department of the Interior Mission

As the Nation's principal conservation agency, the Department of the Interior has responsibility for most of our 

nationally owned public lands and natural resources. This includes fostering sound use of our land and water 

resources; protecting our fish, wildlife, and biological diversity; preserving the environmental and cultural values of 

our national parks and historical places;and providing for the enjoyment of life through outdoor recreation. The 

Department assesses our energy and mineral resources and works to ensure that their development is in the best 

interests of all our people by encouraging stewardship and citizen participation in their care. The Department also 

has a major responsibility for American Indian reservation communities and for people who live in island territories 

under U.S. administration.

The Minerals Management Service Mission

As a bureau of the Department of the Interior, the Minerals Management Service's (MMS) primary responsibilities 

are to manage the mineral resources located on the Nation's Outer Continental Shelf (OCS), collect revenue from 

the Federal OCS and onshore Federal and Indian lands, and distribute those revenues.

Moreover, in working to meet its responsibilities, the Offshore Minerals Management Program administers the 

OCS competitive leasing program and oversees the safe and environmentally sound exploration and production of 

our Nation's offshore natural gas, oil and other mineral resources. The MMS Royalty Management Program

meets its responsibilities by ensuring the efficient, timely and accurate collection and disbursement of revenue from 

mineral leasing and production due to Indian tribes and allottees, States and the U.S. Treasury.

The MMS strives to fulfill its responsibilities through the general guiding principles of: (1) being responsive to the 

public's concerns and interests by maintaining a dialogue with all potentially affected parties and (2) carrying out its 

programs with an emphasis on working to enhance the quality of life for all Americans by lending MMS assistance 

and expertise to economic development and environmental protection.