OCS Study MMS 2005-O61

FINAL REPORT

VOLUME I

Alternative Oil Spill Occurrence Estimators and their 

Variability for the Beaufort Sea – Fault Tree Method

MMS Contract Number 1435-01-04-PO-336507

January, 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 2005-O61

FINAL REPORT

VOLUME I

Alternative Oil Spill Occurrence Estimators and their 

Variability for the Beaufort Sea – Fault Tree Method

January, 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.

1435-01-04-PO-336507, 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. 
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.:1435-01-04-PO-336507

January, 2006

i

ABSTRACT

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

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

Beaufort Sea Offshore Continental Shelf (OCS) lease sale regions. 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 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: 

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 to <100 bbl

ß Medium (M): =100 to <1,000 bbl

ß Large (L): =1,000 to <10,000 bbl

ß Huge (H): = 10,000 bbl

Quantification was carried out for each future year for four different Beaufort Sea 

development scenarios, ranging in duration up to 38 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 

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 base data and in the

Arctic effects 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. 
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.:1435-01-04-PO-336507

January, 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 Debra M. Bridge, Contracting Officer

ß Warren Horowitz, Environmental Studies GIS Coordinator

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
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.:1435-01-04-PO-336507

January, 2006

iii

EXECUTIVE SUMMARY

A. Summary of Work Done

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

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

Beaufort and Chukchi Seas Offshore Continental Shelf (OCS) lease sale regions. 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. Three 

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

scenario, as well as for each 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

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

rounding up for any decimal ending in 5.

These indicators were quantified for the following spill sizes: 

ß Small (S): =50 to <100 bbl

ß Medium (M): =100 to <1,000 bbl

ß Large (L): =1,000 to <10,000 bbl

ß Huge (H): = 10,000 bbl

Quantification was carried out for each future year for four different Beaufort Sea 

exploration and development scenarios, ranging in duration up to 38 years. Three 

scenarios represented developments associated with three different sales (Sales 1, 2, and 

3), and the fourth was for a composite scenario: “Sale All”, consisting of composite

developments from all three sales. In addition, a comparative scenario for non-Arctic 

locations was formulated and analyzed for oil spill occurrence for the composite

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

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 

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.
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.:1435-01-04-PO-336507

January, 2006

iv

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 The variability in the results due to uncertainties in the input data is 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 development scenarios 

in the south Beaufort Sea in the area of MMS jurisdiction. The quantification included 

the consideration of the variability of historical data as well as the expected variability of 

Arctic effects on oil spill occurrence indicators. Consideration of the variability of all 

input data yields both higher variability and 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? Table1 summarizes the Life of Field (LOF) average spill 

indicator values. Figure 1 illustrates these for Sale 1, 2, and 3. The following can be 

observed from Table 1.

ß Each spill indicator for Sale 1, 2, and 3 is similar in value. The indicators are 

higher for the composite “Sale All” scenario.

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

spill size for all scenarios. 

ß The spill index increases dramatically with spill size for all scenarios.

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

counterparts. Non-Arctic spill indicators are approximately 40% greater.
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.:1435-01-04-PO-336507

January, 2006

v

Table 1

Summary of Average Spill Indicators for All Scenarios

SALE 1 SALE 2 SALE 3 SALE All SALE All

non Arctic

Spill Indicators

Life of Field

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]

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]

Spill 

Frequency 

per 10^3 

years

Spill 

Frequency 

per 

10^9 bbl 

produced

Spill 

Index 

[bbl]

Small and Medium Spills 9.404 0.612 4 9.586 0.674 4 11.320 0.714 5 26.204 0.667 11 38.900 0.990 15

50-999 bbl 56% 56% 1% 57% 57% 1% 57% 57% 1% 57% 57% 1% 58% 58% 1%

Large Spills 4.099 0.267 31 3.989 0.281 30 4.575 0.289 35 10.951 0.279 82 15.653 0.398 117

1000-9999 bbl 24% 24% 10% 24% 24% 10% 23% 23% 10% 24% 24% 10% 23% 23% 10%

Huge Spills 3.369 0.219 270 3.323 0.234 268 3.901 0.246 317 9.158 0.233 740 12.956 0.330 1048

=>10000 bbl 20% 20% 89% 20% 20% 89% 20% 20% 89% 20% 20% 89% 19% 19% 89%

Significant Spills 7.468 0.486 300 7.312 0.514 298 8.476 0.535 352 20.109 0.512 822 28.608 0.728 1165

=>1000 bbl 44% 44% 99% 43% 43% 99% 43% 43% 99% 43% 43% 99% 42% 42% 99%

16.872 1.098 304 16.897 1.188 302 19.796 1.249 357 46.313 1.178 833 67.508 1.718 1180 All Spills 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%

5.953 0.388 25 5.899 0.415 23 6.551 0.413 26 15.925 0.405 64 27.192 0.692 96 Pipeline Spills

35% 35% 8% 35% 35% 8% 33% 33% 7% 34% 34% 8% 40% 40% 8%

7.122 0.464 9 7.210 0.507 9 8.751 0.552 11 19.947 0.508 24 25.562 0.650 30 Platform Spills 42% 42% 3% 43% 43% 3% 44% 44% 3% 43% 43% 3% 38% 38% 3%

3.797 0.247 271 3.787 0.266 271 4.494 0.283 321 10.441 0.266 746 14.755 0.375 1054 Well Spills 23% 23% 89% 22% 22% 89% 23% 23% 90% 23% 23% 89% 22% 22% 89%

10.918 0.711 280 10.998 0.773 279 13.245 0.835 331 30.388 0.773 770 40.317 1.026 1084 Platform and Well Spills 65% 65% 92% 65% 65% 92% 67% 67% 93% 66% 66% 92% 60% 60% 92%

16.872 1.098 304 16.897 1.188 302 19.796 1.249 357 46.313 1.178 833 67.508 1.718 1180 All Spills 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

vi

Figure 1

Life of Field Spill Indicators – By Spill Size

Life of Field Average

0

10

20

30

40

50

60

70

Spill Frequency

per 1000 years

Huge Spills

=>10000 bbl

3.369 3.323 3.901 9.019 12.956

Large Spills

1000-9999 bbl

4.099 3.989 4.575 10.882 15.653

Small and Medium Spills

50-999 bbl

9.404 9.586 11.320 26.180 38.900

SALE 1 SALE 2 SALE 3 SALE All SALE All

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

0.219 0.234 0.246 0.229 0.330

Large Spills

1000-9999 bbl

0.267 0.281 0.289 0.277 0.398

Small and Medium Spills

50-999 bbl

0.612 0.674 0.714 0.666 0.990

SALE 1 SALE 2 SALE 3 SALE All SALE All

non Arctic

Life of Field Average

0

200

400

600

800

1000

1200

Spill Index [bbl]

Huge Spills

=>10000 bbl

270 268 317 721 1048

Large Spills

1000-9999 bbl

31 30 35 81 117

Small and Medium Spills

50-999 bbl

4 4 5 11 15

SALE 1 SALE 2 SALE 3 SALE All SALE All

non Arctic
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 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

representative scenario years, again, in Table 1 and also in Figure 2. 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 Platforms contribute the most (43%) to the two spill frequency indicators, but 

the least (3%) to the spill index. 

ß Pipelines are next in relative contribution to spill frequencies (34%) and 

intermediate in contribution to spill index (8%). 

ß Wells are by far (at 89%) the highest contributors to spill index. 

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

spills, while wells will have the least number, but largest spills. Pipelines 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 proportiona l 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 Beaufort 

Sea Sale All Life of Field average spill indicators by spill size and source. The variability 

of these indicators is fairly representative of the trends in variability for spill indicators 

for all scenarios modeled. 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. In other words, small and medium spills illustrate the 

largest variability; huge spills show the least variability for facilities. 

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

and platforms, but the opposite trend for wells. 
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

viii

Figure 2

Life of Field Spill Indicators – By Source Composition

Life of Field Average

0

10

20

30

40

50

60

70

Spill Frequency

per 1000 years

Well Spills 3.797 3.787 4.494 10.441 14.755

Platform Spills 7.122 7.210 8.751 19.947 25.562

Pipeline Spills 5.953 5.899 6.551 15.925 27.192

SALE 1 SALE 2 SALE 3 SALE All SALE All

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 0.247 0.266 0.283 0.266 0.375

Platform Spills 0.464 0.507 0.552 0.508 0.650

Pipeline Spills 0.388 0.415 0.413 0.405 0.692

SALE 1 SALE 2 SALE 3 SALE All

SALE All

non Arctic

Life of Field Average

0

200

400

600

800

1000

1200

Spill Index [bbl]

Well Spills 271 271 321 746 1054

Platform Spills 9 9 11 24 30

Pipeline Spills 25 23 26 64 96

SALE 1 SALE 2 SALE 3 SALE All SALE All

non Arctic
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

ix

BY SPILL SOURCE BY SPILL SIZE

Figure 3

Sale All – Year 2024 – Spill Indicator Composition by Source and Spill Size

Sale All- Year 2024

 Spill Frequency per 10^3 years

58%

23%

19%

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

 =>10000 bbl

TOTAL 90.976

Sale All - Year 2024

 Spill Frequency per 10^9 bbl produced

23%

58%

19%

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

 =>10000 bbl

TOTAL 1.149

Sale All - Year 2024

 Spill Index [bbl]

1%

89%

10%

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

 =>10000 bbl

TOTAL 1534

Sale All - Year 2024

 Spill Frequency per 10^3 years

44%

35%

21%

Pipelines

Platforms

Wells TOTAL 90.976

Sale All - Year 2024

 Spill Frequency per 10^9 bbl produced

44%

35%

21%

Pipelines

Platforms

Wells TOTAL 1.149

Sale All - Year 2024

 Spill Index [bbl]

89%

8%

Pipelines 3%

Platforms

Wells TOTAL 1534
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

x

BY SPILL SOURCE BY SPILL SIZE

Figure 4

Sale All – Life of Field Average Spill Indicator Composition by Source and Spill Size

Sale All - LOF Average

 Spill Frequency per 10^3 years

56%

20%

24%

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

 =>10000 bbl

TOTAL 46.313

Sale All - LOF Average

 Spill Frequency per 10^9 bbl produced

56%

24%

20%

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

 =>10000 bbl

TOTAL 1.178

Sale All - LOF Average

 Spill Index [bbl]

1%

89%

10%

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

 =>10000 bbl

TOTAL 833

Sale All - LOF Average

 Spill Frequency per 10^3 years

35%

43% 22%

Pipelines

Platforms

Wells TOTAL 46.313

Sale All - LOF Average

 Spill Frequency per 10^9 bbl produced

35%

22%

43%

Pipelines

Platforms

Wells TOTAL 1.178

Sale All - LOF Average

 Spill Index [bbl]

8%

3%

89%

Pipelines

Platforms

Wells TOTAL 833
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

xi

Figure 5

Life of Field Average Spill Frequency – Cumulative Distribution Functions – Sale All

CDF Sale All LOF Average - Pipeline

0

10

20

30

40

50

60

70

80

90

100

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Spill Frequency per 1000 years

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale All LOF Average - Pipeline

0

10

20

30

40

50

60

70

80

90

100

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All 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 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 Sale All 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 32 34 36 38 40

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All 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 11 12 13 14 15 16

Spill Frequency per 1000 years

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale All 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 11 12 13 14 15 16

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All LOF Average - Platforms + Wells

0

10

20

30

40

50

60

70

80

90

100

0 5 10 15 20 25 30 35 40 45 50

Spill Frequency per 1000 years

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale All LOF Average - Platforms + Wells

0

10

20

30

40

50

60

70

80

90

100

0 5 10 15 20 25 30 35 40 45 50

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All 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 60 65 70

Spill Frequency per 1000 years

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale All 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 60 65 70

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

xii

Figure 6

Life of Field Average Spill Frequency per Barrel Produced – Cumulative 

Distribution Functions – Sale All

CDF Sale All 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

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 Sale All 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

Spill Frequency per 10^9 bbl Produced

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All 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 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 Sale All 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 0.9 1.0

Spill Frequency per 10^9 bbl Produced

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4

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 Sale All LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4 0.5

Spill Frequency per 10^9 bbl Produced

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All 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 0.9 1.0 1.1 1.2 1.3 1.4

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 Sale All 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 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 Sale All 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 %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale All 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
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

xiii

Figure 7

Life of Field Average Spill Index (bbl) – Cumulative Distribution Functions – Sale All

CDF Sale All 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 Sale All 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 %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All LOF Average - Platforms

0

10

20

30

40

50

60

70

80

90

100

0 5 10 15 20 25 30 35 40 45 50 55 60

Spill Index [bbl]

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale All LOF Average - Platforms

0

10

20

30

40

50

60

70

80

90

100

0 5 10 15 20 25 30 35 40 45 50 55 60

Spill Index [bbl]

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

0 100 200 300 400 500 600 700 800 900 1000 1100 1200

Spill Index [bbl]

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale All LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

0 100 200 300 400 500 600 700 800 900 1000 1100 1200

Spill Index [bbl]

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All 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 1000 1100 1200

Spill Index [bbl]

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale All 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 1000 1100 1200

Spill Index [bbl]

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All LOF Average - All

0

10

20

30

40

50

60

70

80

90

100

0 100 200 300 400 500 600 700 800 900 100

0

110

0

120

0

130

0

140

0

Spill Index [bbl]

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale All LOF Average - All

0

10

20

30

40

50

60

70

80

90

100

0 100 200 300 400 500 600 700 800 900 100

0

110

0

120

0

130

0

140

0

Spill Index [bbl]

CDF %

Significant Spills

=>1000 bbl

All Spills
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

xiv

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

significant spills, that the Life of Field average mean (50%) value of 20 (spills per 1,000 

years) ranges between 30 and 12 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 800 per billion barrels produced ranges from 1,300 to 400 – a somewhat larger 

proportion of mean than that of the spill frequency indicators.

C. Conclusions on the Methodology and its Applicability

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

history 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 basic 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 spill causes, 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.
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

xv

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 and thaw settlement 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. There are two possible

shortcomings of the scenarios as follows:

ß Distributed values for the key quantities were not provided, thus precluding 

their incorporation as distributions in the Monte Carlo analysis.

ß The facility abandonment rate appears to be significantly lower than the rate 

of decline in production.

Generally, the fault tree methodology was limited primarily by the shortcomings in input 

data discussed above. 
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

xvi

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. 

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. These effects are incorporated to the extent that they are 

represented in spill databases used.

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. 

ß Develop an adjusted expected value oil spill occurrence indicator model as a 

user friendly software package, which can be used for the assessment of oil 

spill occurrence indicators and their characteristics for any designated

scenario. The software package should include the following:

ß Modular structure

ß User manual

ß Online help

ß Password protected parameters and algorithms

ß Extensive tabular and graphical outputs
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

xvii

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...................................................................................................1.2

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

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

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

1.5.1 General Technical Discussion..................................................................1.4

1.5.2 Spill Frequencies ......................................................................................1.5

1.5.3 Spill Volumes............................................................................................1.5

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

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

1.8 Outline of Report..................................................................................................1.9

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

2.1 Approaches to Historic al 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 Beaufort Sea Development Scenarios..................................................................3.4
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

xviii

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 Pipeline First Order Arctic Effects.........................................................4.10

4.3.2 Pipeline Second Order Arctic Effect Variations.....................................4.13

4.3.3 Arctic Pipeline Fault Tree Frequency Calculations...............................4.13

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

4.4.1 Platform First Order Arctic Effects........................................................4.21

4.4.2 Platform Second Order Arctic Effects....................................................4.21

4.4.3 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 Beaufort Sea Oil Spill Occurrence Indicators..................................5.3

5.3.1 Sale 1 Oil Spill Occurrence Indicators.....................................................5.3

5.3.2 Sale 2 Oil Spill Occurrence Indicators...................................................5.11

5.3.3 Sale 3 Oil Spill Occurrence Indicators...................................................5.11

5.3.4 Sale All Oil Spill Occurrence Indicators................................................5.11

5.3.5 Sale All Comparative Non-Arctic Indicator Assessment ........................5.18

5.4 Summary of Representative Oil Spill Occurrence Indicator Results .................5.18

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 .....................................6.11

6.3 Limitations of the Methodology and Results......................................................6.12

6.4 Recommendations...............................................................................................6.13

References................................................................................................................R.1
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

xix

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 – Beaufort Sea Sale 1

4.2 Arctic Spill Occurrence – Beaufort Sea Sale 2

4.3 Arctic Spill Occurrence – Beaufort Sea Sale 3

4.4 Arctic Spill Occurrence – Beaufort Sea Sale All

4.5 Arctic Spill Occurrence – Beaufort Sea Sale All Non-Arctic

5 Conclusions
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

xx

LIST OF TABLES

TABLE PAGE

2.1 GOM OCS Pipeline Spills 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 Historical Blowout Statistics...........................................................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 Beaufort Sea All Sales (2004 – 2038) ..................................................................3.6

3.3 Summary of Development Scenarios for Year 2020............................................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 Fault First Order Arctic Effect Summary.............................................4.11

4.5 Pipeline First and Second Order Arctic Effect Distribution Summary..............4.14

4.6 Arctic Pipeline Small Spill Frequencies.............................................................4.16

4.7 Arctic Pipeline Medium Spill Frequencies.........................................................4.17

4.8 Arctic Pipeline Large Spill Frequencies.............................................................4.18

4.9 Arctic Pipeline Huge Spill Frequencies..............................................................4.19

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

4.11 Platform First Order Arctic Effect Summary .....................................................4.22

4.12 Platform First and Second Order Arctic Effects Distribution Summary............4.23

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

4.14 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 Sale 1 Year 2016 – Monte Carlo Results..............................................................5.9

5.2 Composition of Spill Indicators – Sale 1 – Life of Field Average .....................5.12

5.3 Summary of Average Spill Indicators for All Scenarios....................................5.21

6.1 Summary of Average Spill Indicators for All Scenarios......................................6.2
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

xxi

LIST OF FIGURES

FIGURE PAGE

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

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

3.1 Beaufort Sea Lease Areas.....................................................................................3.3

3.2 Beaufort Sea Possible Facility Plan......................................................................3.5

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 Sale 1 Spill Frequency per 1,000 Years................................................................5.4

5.3 Sale 1 Spill Frequency per 109 Barrels Produced.................................................5.4

5.4 Sale 1 Spill Index..................................................................................................5.5

5.5 Sale 1 Indicators – Pipeline – Spill Frequency per 1,000 Years..........................5.6

5.6 Sale 1 Indicators – Platforms – Spill Frequency per 1,000 Years........................5.7

5.7 Sale 1 Indicators – Wells – Spill Frequency per 1,000 Years..............................5.8

5.8 Sale 1 Spill Indicator Distributions – Year 2016 – Spill Frequency per 1,000 Years...5.10

5.9 Sale 1 Life of Field Average Spill Frequency....................................................5.13

5.10 Sale 1 Life of Field Average Spills per Barrel Produced ...................................5.14

5.11 Sale 2 Spill Indicators.........................................................................................5.15

5.12 Sale 3 Spill Indicators.........................................................................................5.16

5.13 Sale All Spill Indicators......................................................................................5.17

5.14 Beaufort Sea Sale All Spill Frequency – Arctic and Non-Arctic .......................5.19

5.15 Beaufort Sea Sale All Spill Frequency per 109 Barrels Produced – Arctic andNon-Arctic ..5.19

5.16 Beaufort Sea Sale All Spill Index – Arctic and Non-Arctic ...............................5.20

5.17 Life of Field Spill Indicators –By Spill Size ......................................................5.22

5.18 Life of Field Spill Indicators – By Source Composition....................................5.24

5.19 Sale All – Year 2024 – Spill Indicator Composition by Source and Spill Size ....5.25

5.20 Sale All – Life of Field Average Spill Indicator Composition by Source and Spill Size.5.26

5.21 Life of Field Average Spill Frequency – CDF – Sale All ..................................5.28

5.22 Life of Field Average Spill Frequency per Barrel Produced – CDF – Sale All....5.29

5.23 Life of Field Average Spill Index (bbl) – CDF – Sale All .................................5.30

6.1 Life of Field Spill Indicators – By Spill Size .......................................................6.3

6.2 Life of Field Spill Indicators – By Spill Source Composition..............................6.5

6.3 Sale All – Year 2024 – Spill Indicator Composition by Source and Spill Size ....6.6

6.4 Sale All – Life of Field Average Spill Indicator Composition by Source and Spill Size...6.7

6.5 Life of Field Average Spill Frequency –Cumulative Distribution Functions – Sale All.....6.8

6.6 Life of Field Average Spill Frequency per Barrel Produced – Cumulative

Distribution Functions – Sale All .........................................................................6.9

6.7 Life of Field Average Spill Index (bbl) –Cumulative Distribution Functions – Sale All...6.10
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

xxii

GLOSSARY OF TERMS AND ACRONYMS

Acute Risk Risk that has an immediate adverse effect due to a single accident 

such as an oil blowout.

ALARP As Low as Reasonably Practicable

API American Petroleum Institute

ARM Availability, Reliability and Maintainability

BOP Blowout Preventer

CDF Cumulative Distribution Frequency

Chronic Risk Risk that has an adverse effect only after long-term or repeated 

occurrences.

Consequence The direct effect of an accidental event.

DJU Drilling Jack-Up

ESD Emergency Shutdown

ESDV Emergency Shutdown Valve

FPSO Floating Production and Storage Operation

GBS Gravity Base Structure

GOM Gulf of Mexico

H2S Hydrogen Sulfide

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

leakage of natural gas from a pressurized vessel.

HSE Health and Safety Executive (United Kingdom)

HT High Temperature

HTHP High Temperature, High Pressure

LFL Lower Flammability Limit

LOF Life of Field

MAOP Maximum Allowable Operating Pressure. The highest pressure at 

which a pipeline or vessel can be operated considering design and 

regulatory conditions.

MMS Minerals Management Service, Department of the Interior

Monte Carlo A numerical method for evaluating algebraic combinations of

statistical distributions.

MSL Mean Sea Level

NOP Normal Operating Pressure. The highest pressure at which a

pipeline or vessel can be operated considering design conditions.
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

xxiii

NPD Norwegian Petroleum Directorate

OCS Offshore Continental Shelf

OIM Offshore Installation Manager

QRA Quantitative Risk Assessment

Risk A compound measure of the probability and magnitude of adverse 

effect.

ROV Remotely Operated Vehicle

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

SPM Single Point Mooring

SSIV Sub-Sea Isolation Valve

SSSV Subsurface Safety Valve

UFL Upper Flammability Limit

UKCS UK Continental Shelf
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.:1435-01-04-PO-336507

January, 2006

1.1

CHAPTER 1

INTRODUCTION

1.1 General Introduction

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

predictions for National Environmental Protection Act assessments for all parts of their 

area of jurisdiction, ranging from the shore through shallow water, to deeper water.

Although land to 3 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 2000

to 2002, a study was carried out by Bercha International Inc. [12] * (OCS Study MMS

2002-047) 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, the most preferable and accepted being 

fault trees [7, 10, 11, 14, 15, 18, 23, 26, 45, 51, 65], and their combination with numerical 

distribution methods such as Monte Carlo simulation [1]. 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. Because variability information for the non-Arctic data was not available at 

the time of the previous study [12], the resultant spill occurrence probabilities only 

reflected the variability associated with Arctic effects. The shortcoming in the estimate of 

the variability and consequently, in most cases, also in the expected value, was noted in 

the previous study [12] and tabled for future consideration. In 2004, following internal 

discussions and discussions with stakeholders, the present study – which is to include 

both the variability of the non-Arctic database used as a starting point and the variability 

of Arctic effects – was initiated. 

 

*

 Numbers in square brackets refer to citations listed in the “References” section of this report.
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.:1435-01-04-PO-336507

January, 2006

1.2

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 deeper lease tracts which could be offered in the 

upcoming Beaufort Sea sales.

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

Beaufort Sea developments associated with spills of different size categories.

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

assess their variability.

• 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 

non-Arctic factors.

1.3 Study Area Definition

The geographical study area is the offshore continental shelf in the U.S. Beaufort 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 present to Year 

2038. 

1.4 General Background

The final report, dated August 2002 [12], described the methodology and results of

applying the fault tree method to the evaluation of oil spill occurrence estimators for the 

Beaufort and Chukchi Seas. The focus of this report was on the 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. These variances were numerically incorporated 

through the use of Monte Carlo simulation for the fault tree model numerical predictions. 
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.:1435-01-04-PO-336507

January, 2006

1.3

CHUKCHISEA

BEAUFORTSEA

U.S.A.

CANADA

180°

130°

70°

Figure 1.1

Study Area Map

STUDY AREA REPRESENTED AS:SHOWS OFFSHORE FROM LANDFALL T0 600-METER ISOBATH, APPROXIMATELY
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.:1435-01-04-PO-336507

January, 2006

1.4

The lack of variance of non-Arctic effects was clearly identified in the final report as a 

possible limitation, but justified because the focus of the work was on the Arctic spill 

causes. Recent discussions with stakeholders from the North Slope indicate a strong 

interest in extending the study to include not only effects of variations in the Arctic 

parameters, but also of variations in non-Arctic parameters. During meetings and

discussions at the Information Transfer Meeting #9 in Anchorage (March 2003), the 

matter of including variability of non-Arctic effects was discussed between the contractor 

and Minerals Management Service (MMS) as well as stakeholder representatives.

Following these meetings, as well as further discussion, proposal preparation and

submission, and contract award, the present study was initiated in 2004.

1.5 Technical Approaches

1.5.1 General Technical Discussion

Uncertainties in the results of oil spill occurrence predictions generated in the subject

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

occurrence model. In the original study, 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. The uncertainty 

and occurrence model chosen was a numerical one which incorporates the maximum and 

minimum bounds of the input parameters. Thus the principal source of uncertainty in the 

occurrence results is that caused by uncertainties in the input parameters themselves. As 

noted earlier, the uncertainties from the Arctic input parameters were quantified;

however, only discrete values of the non-Arctic input parameters were used. 

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 precise sources of the data are described in detail in Chapter 2 of this report.
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.:1435-01-04-PO-336507

January, 2006

1.5

1.5.2 Spill Frequencies

There are two main approaches, as follows, for evaluating the variance in the in the spill 

frequencies:

• First Order Approaches – A high level approach based on the incorporation of 

Arctic effects in direct proportion to historical data variability.

• Second Order Approaches – A more detailed approach in which Arctic effects 

and their variances are directly incorporated into the analysis.

The two approaches can be applied in a complementary manner, as explained in Section 

4.3.

1.5.3 Spill Volumes

In regard to the second general area, the volume distributions, a frequency distribution of 

the likely spill volumes in each spill size category was developed from the spill data 

records. This frequency distribution was then transformed to a cumulative distribution 

function and combined with the appropriate spill frequency to provide a distribution of 

the spill index (product of spill frequency and spill volume), which includes both Arctic 

and non-Arctic variability. The computation of the spill index through the multiplication 

of two probability densities was carried out using the Monte Carlo method.

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) Beaufort Sea scenario updates 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.
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.:1435-01-04-PO-336507

January, 2006

1.6

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 non-Arctic 

effects, new spill size categories (>1000bbl), and life-of-field 

(LOF) results.

b) Model runs for all (four) Beaufort Sea scenarios.

c) Model runs as required for other (e.g., non-Arctic) scenarios.

Task 5: Reporting

a) Progress Report #1 following completion of Tasks 1 and 2.

b) Draft Final Report and Final Report.

1.7 Work Organization

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

extensive numerical analysis. Although the assimilation of historical and future scenario 

data is of indisputable 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 several 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, and huge spills, defined as follows:
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.:1435-01-04-PO-336507

January, 2006

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 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 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

Development Well D.

Beaufort Sea

All Sales

Production Well

Exploration Well D.

Historical Data Analysis

Beaufort Sea

All Sales Non Arctic

Beaufort Sea

Sale 3

Platform

Beaufort Sea

Sale 2

Beaufort Sea

Sale 1

Facility
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.:1435-01-04-PO-336507

January, 2006

1.8

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

For those spills of 10,000 bbl or more, the term ‘huge spill’ has been introduced to permit 

unique designation of each spill category by one letter, rather than the more customary 

terminology of ‘very large’ which would require two letters. 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.

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

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

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

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 extended beyond the 

60-meter isobath. 

A total of five different future development scenarios were defined for the Beaufort Sea, 

termed Sales 1, 2, and 3, Sale All (which is the composite of the three sales), and nonArctic (a hypothetical scenario). Each scenario was described for each year in its

development history, as far as the year 2038 for the longest duration scenarios. In

addition, the hypothetical non-Arctic scenario was developed for comparative purposes 

on the assumption that it was located 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 combinations considered, four Arctic 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)
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.:1435-01-04-PO-336507

January, 2006

1.9

ß Life of Field Indices

The total number of spill indicator quantifications conducted was approximately 60,000, 

as detailed in Section 5.1.

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 

scenarios to be utilized, Chapter 4 deals with 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. Because Chapter 2, on historical 

data, is restricted to the data actually utilized in the present computations, Appendix 1

will be of interest to readers wanting a more comprehensive view of oil spill occurrence 

statistics including those from other parts of the world. Appendix 2 gives details of the 

fault tree analysis. Appendix 3 gives details on the future development scenarios utilized 

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.
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

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) Gulf of Mexico (GOM) Offshore Continental Shelf (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. 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 31 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, 31 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 90% confidence interval value. The high and low values were 

obtained by multiplying the Historical value by the high and low factors respectively. 

These factors were obtained from the total population database to correspond to the upper 

and lower 90% confidence interval data points. 
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

2.2

Table 2.1

GOM OCS Pipeline Spills Statistics Summary (1972-1999)

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" 15 81,847 18.3270

Small 50-99 bbl 6 187,183 3.2054

Medium 100 - 999 bbl 12 187,183 6.4108

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 5 81,847 6.1090

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 31 records have both MIN_WATER_DEPTH and MAX_WATER_DEPTH set to "0".

**Exposure comes from an analysis of PPL_MASTERS database as published on Feb 15, 2001.

 Ratio for <10"/>10"=1.287
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

2.3

Table 2.2

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

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 1 119 1 1

TOTALS 31 7 11 10 3 18 13
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

2.4

Table 2.3

Distribution and Frequency of Historical Spills – Pipeline

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 16.67 3 1.6027 7.69 1 0.5342

External 5.56 1 0.5342

Internal 11.11 2 1.0685 7.69 1 0.5342

THIRD PARTY IMPACT 38.89 7 3.7397 69.23 9 4.8081

Anchor Impact 33.33 6 3.2054 30.77 4 2.1369

Jackup Rig or Spud Barge 7.69 1 0.5342

Trawl/Fishing Net 5.56 1 0.5342 30.77 4 2.1369

OPERATION IMPACT 16.67 3 1.6027 7.69 1 0.5342

Rig Anchoring 5.56 1 0.5342

Work Boat Anchoring 11.11 2 1.0685 7.69 1 0.5342

MECHANICAL 11.11 2 1.0685

Connection Failure 5.56 1 0.5342

Material Failure 5.56 1 0.5342

NATURAL HAZARD 11.11 2 1.0685 15.38 2 1.0685

Mud Slide 11.11 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 5.56 1 0.5342

TOTALS 100.00 18

187183

9.6163 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

Low

Factor

High

Factor Historical Low Mode High

By Diameter, By Spill Size

< 10” Small 0 2.57 3.7974 0 1.6329 9.7592

Medium 0 2.57 6.6454 0 2.8575 17.0786

Large 0 2.57 3.7974 0 1.6329 9.7592

Huge 0 2.57 0.9493 0 0.4082 2.4398

= 10" Small 0 2.57 2.4436 0 1.0507 6.2800

Medium 0 2.57 6.1090 0 2.6269 15.7001

Large 0 2.57 7.3308 0 3.1522 18.8401

Huge 0 2.57 2.4436 0 1.0507 6.2800
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

2.5

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. The 

platform spill data are given with 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 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 usually 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. The number of 

production wells given in each scenario was distributed equally among the production 

platforms specified (by MMS) for this study.

2.4 Oil Well Blowout Data

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

exploratory and development wells, and the process of producing oil from production 

wells [69]. The basis for the non-Arctic historical oil well blowout statistics, a number of 

sources were reviewed including the North Star and Liberty oil development project 

reports [52], and the cumulative distribution function for oil blowout releases [59], as 

well as the book by Per Holland 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.
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

2.6

Table 2.5

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

(1972-1999)

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)

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

Low

Factor

High

Factor Historical Low Mode High

Small and Medium Spills

50-999 bbl spill per 10^4well-year 0 2.88 1.5036 0.0000 0.1804 4.3303

Large and Huge Spills

>=1000 bbl spill per 10^4well-year 0 2.88 0.2506 0.0000 0.0301 0.7217
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

2.7

Table 2.8

Summary of North Sea and Gulf of Mexico

(Holland, 1997)

Well Type Unit Low

90% CI Average

High

90% 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) Small and Medium Spills 50-999 bbl Large Spills 1000-9999 bbl

Small, Medium, and Large Spills50-9999 bblSpills 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
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

2.8

Table 2.10

Well Blowout Historical Spill Probability and Size Variability

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
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

2.9

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

LP = Length of pipeline (km)

? = Gouge orientation (degrees) from pipeline centerline
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

2.10

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 0.8, gives a frequency of 5.23 x 10-6/km-yr. 

For the purposes of the analysis, 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, an 

analogous process was carried out with a reduced gouge flux of 1.5 gouges/km-yr. For 

deep water (= 30 m) no gouging is expected.

2.5.3 Strudel Scour

When fresh water collecting on top of the ice sheet 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.
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

2.11

Table 2.11

Summary of Pipeline Unique Arctic Effect Inputs

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 0.00004 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
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

2.12

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 for the case of upheaval buckling, writers are not aware of any method 

for defensibly calculating the probability of pipeline failures from thaw settlement.

Accordingly, resort is again made to the percentage of a known phenomenon approach 

and thaw settlement has been assumed to occur at a rate equal to 10% of that associated 

with strudel scour. The resultant distribution is shown in Table 2.11. Like upheaval

buckling, thaw settlement is expected to be independent of water depth.

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%. 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. 
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

2.13

Table 2.12

Summary of Platform Unique Arctic Effect Inputs

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.
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 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
Beaufort Oil Spill Estimators 3.1 Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

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 offshore oil and gas 

development scenarios need to include the following characteristics:

ß Water depth range, particularly 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 have been 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 Beaufort Sea Lease Areas 

shown in Figure 3.1.
Beaufort Oil Spill Estimators 3.2 Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 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
Beaufort Oil Spill Estimators 3.3 Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006
Beaufort Oil Spill Estimators 3.4 Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

3.2 Beaufort 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. The 

obvious way to approach this, at least for an initial scenario, is to sketch a map of the 

possible geographic configuration of the facilities. Such a map, based on the composite 

Beaufort Sea (All Sale) scenario is shown in Figure 3.2. The facility quantities and 

locations shown are hypothetical, and not based on any operator’s plan. This location 

map also shows the four water depth zones – shallow, medium, deep, and very deep. As 

can be seen, no facilities are predicted in the very deep region. The details of the 

development scenarios, given in Appendix 2, were generated by Alaska MMS personnel 

for three different Beaufort Sea Lease Sale alternatives, Sales 1, 2, and 3, and for a 

composite of all sales. 

Table 3.2 summarizes the complete Beaufort Sea composite (Sale All) scenario including 

its temporal development from 2004 to Year 2038, 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 by water depth 

zone were estimated and distributed as shown in Table 3.2:

ß Exploration wells drilled – annual

ß Delineation wells drilled – annual

ß Production platforms – annual increment and cumulative number

ß Production/service wells – annual increment and cumulative number

ß Pipeline quantities 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 can be made 

available through the 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. The 

important aspect of the information in Table 3.2, however, is the distribution of the 

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

depth.

Similar tables were developed for Lease Sales 1, 2, and 3. These are given in detail in 

Appendix 2. Peak production for the composite scenario occurs in Year 2020.

Accordingly, Table 3.3 summarizes the quantities of facilities and their distribution by 

water depth for Year 2020, the maximum production year of the composite (Sale All)

scenario.
Beaufort Oil Spill Estimators 3.5 Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

Figure 3.2: Beaufort Sea Possible  Facility PlanLegendWater Depth Pipelines Shallow < 10” Medium =10” Deep Very Deep
Beaufort Oil Spill Estimators 3.6 Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

Table 3.2

Beaufort Sea All Sales (2004 – 2038)

Production In-use Pipeline Length [miles]

Platforms

Production

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

Water

Depth

Exploration

Wells

Delineation

Wells

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

Production

MMbbl

Shallow 1

Medium

Deep

2004

Total 1

Shallow 1

Medium

Deep

2005

Total 1

Shallow 1 2

Medium

Deep

2006

Total 1 2

Shallow 2

Medium

Deep

2007

Total 2

Shallow 1 2

Medium 1

Deep

2008

Total 2 2

Shallow 2 1 1 3 3

Medium 1

Deep

2009

Total 1 2 1 1 3 3

Shallow 1 1 10 13 10 10 10 10 7.9

Medium 1 2

Deep

2010

Total 2 2 1 10 13 10 10 10 10 7.9

Shallow 1 2 13 26 10 10 15.7

Medium

Deep

2011

Total 1 2 13 26 10 10 15.7

Shallow 1 3 13 39 10 20 10 20 23.6

Medium 2

Deep 1

2012

Total 3 1 3 13 39 10 20 10 20 23.6

Shallow 3 20 59 10 30 10 30 39.4

Medium 1 3

Deep 1

2013

Total 2 3 3 20 59 10 30 10 30 39.4

Shallow 3 10 69 30 30 44.4

Medium 4 1 1 3 3

Deep

2014

Total 4 1 4 13 72 30 30 44.4

Shallow 3 69 10 40 10 40 42.1

Medium 2 1 10 13 10 10 10 10 13.2

Deep 1

2015

Total 1 2 4 10 82 20 50 20 50 55.3

Shallow 3 69 40 40 37.5

Medium 1 2 13 26 10 10 22.0

Deep

2016

Total 1 5 13 95 50 50 59.5

Shallow 3 69 10 50 10 50 31.0

Medium 1 3 13 39 5 5 15 25 20 30 43.5

Deep 1

2017

Total 1 1 6 13 108 5 5 25 75 30 80 74.5

Shallow 3 69 50 50 25.5

Medium 1 4 24 63 5 25 30 50.6

Deep 1

2018

Total 1 1 7 24 132 5 75 80 76.1

Shallow 3 69 15 65 15 65 21.1

Medium 1 5 24 87 5 10 15 40 20 50 81.4

Deep

2019

Total 1 8 24 156 5 10 30 105 35 115 102.5

Shallow 3 69 65 65 17.4

Medium 5 20 107 10 40 50 86.1

Deep

2020

Total 8 20 176 10 105 115 103.5
Beaufort Oil Spill Estimators 3.7 Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

Table 3.2 - continued

Production In-use Pipeline Length [miles]

Platforms

Production

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

Water

Depth

Exploration

Wells

Delineation

Wells

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

Productio n

MMbbl

Shallow 3 69 65 65 14.4

Medium 5 20 127 10 40 50 83.5

Deep

2021

Total 8 20 196 10 105 115 97.9

Shallow 3 69 65 65 11.9

Medium 5 10 137 10 40 50 81.2

Deep

2022

Total 8 10 206 10 105 115 93.1

Shallow 3 69 65 65 9.8

Medium 5 137 10 40 50 75.8

Deep

2023

Total 8 206 10 105 115 85.6

Shallow 3 69 65 65 8.1

Medium 5 137 10 40 50 71.1

Deep

2024

Total 8 206 10 105 115 79.2

Shallow -1 2 -23 46 -10 55 -10 55 5.1

Medium 5 137 10 40 50 62.4

Deep

2025

Total -1 7 -23 183 10 -10 95 -10 105 67.5

Shallow 2 46 55 55 4.2

Medium 5 137 10 40 50 54.8

Deep

2026

Total 7 183 10 95 105 59.0

Shallow -1 1 -23 23 -10 45 -10 45 1.9

Medium 5 137 10 40 50 48.0

Deep

2027

Total -1 6 -23 160 10 -10 85 -10 95 49.9

Shallow -1 -23 -15 30 -15 30

Medium 5 137 10 40 50 42.2

Deep

2028

Total -1 5 -23 137 10 -15 70 -15 80 42.2

Shallow 30 30

Medium 5 137 10 40 50 37.0

Deep

2029

Total 5 137 10 70 80 37.0

Shallow -10 20 -10 20

Medium 5 137 10 40 50 32.4

Deep

2030

Total 5 137 10 -10 60 -10 70 32.4

Shallow 20 20

Medium 5 137 10 40 50 28.5

Deep

2031

Total 5 137 10 60 70 28.5

Shallow 20 20

Medium 5 137 10 40 50 25.0

Deep

2032

Total 5 137 10 60 70 25.0

Shallow 20 20

Medium 5 137 10 40 50 21.9

Deep

2033

Total 5 137 10 60 70 21.9

Shallow 20 20

Medium -1 4 -23 114 10 -10 30 -10 40 17.0

Deep

2034

Total -1 4 -23 114 10 -10 50 -10 60 17.0

Shallow 20 20

Medium 4 114 10 30 40 14.9

Deep

2035

Total 4 114 10 50 60 14.9

Shallow -5 15 -5 15

Medium -2 2 -46 68 -5 5 -10 20 -15 25 13.1

Deep

2036

Total -2 2 -46 68 -5 5 -15 35 -20 40 8.3

Shallow 15 15

Medium 2 68 5 20 25 7.3

Deep

2037

Total 2 68 5 35 40 7.3

Shallow 15 15

Medium 2 68 5 20 25 6.5

Deep

2038

Total 2 68 5 35 40 6.5
Beaufort Oil Spill Estimators 3.8 Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

Table 3.3

Summary of Development Scenarios for Year 20201

Production In-use Pipeline Length [miles]

Platforms

Production

Wells

Prod. / 

Serv.

Wells Sale Year Sum<10" Sum >=10" Sum All Water

Depth

Exploration

Wells

Delineation

Wells

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

Production

[MMbbl]

Shallow 2 46 30 30 10.1

Medium 1 23 10 10 18.9

Deep 1 2020

Total 3 69 40 40 29.0

Shallow 1 23 20 20 7.3

Medium 2 46 5 15 20 28.6

Deep 2 2020

Total 3 69 5 35 40 35.9

Shallow 15 15

Medium 2 20 38 5 15 20 38.6

Deep 3 2020

Total 2 20 38 5 30 35 38.6

Shallow 3 69 65 65 17.4

Medium 5 20 107 10 40 50 86.1

Deep ALL 2020

Total 8 20 176 10 105 115 103.5

 

1

 Year 2020 is the maximum production year for All Sale scenario.
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

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 spill statistics for non-Arctic regions to predictive 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.
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

4.2

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
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

4.3

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 ≤
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

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.
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

4.5

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 (4.4)

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 4.4. 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.
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

4.6

Figure 4.3

Monte Carlo Technique Schematic
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

4.7

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 (4.3)

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 4.3. 

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, average, and high values at 90% 

confidence intervals are given in Tables 4.1, 4.2, and 4.3, for pipelines, platforms, and 

wells respectively.
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

4.8

Table 4.1

Pipeline Spill Frequency Triangular Distribution Properties

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

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
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

4.9

Table 4.3

Well Blowout Frequency Triangular Distribution Properties

Frequencies

EVENT FREQUENCY

UNIT

Historical Low Mode High Expected 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 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 DRILLING 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
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

4.10

4.2.5 Approaches to Assessment of Arctic Spill Frequency Variability

There are two basic approaches to the assessment of the variability of non-Arctic spill 

rates, and consequently the Arctic spill rates, using the fault tree method. The first 

method utilizes the historical variability of the non-Arctic base data and distributes it in 

direct proportion throughout the Arctic fault tree. This method is a relatively high level, 

approximate method, and is called the First Order Approach. In this method, the nonArctic variable distribution is multiplied by a point value to obtain the Arctic variable 

distribution. The second method consists of systematically perturbing the variability of all 

the causal events, plus that of the Arctic unique effects. This method is more detailed and 

specific, and is termed the Second Order Approach. In the Second Order Approach, the 

non-Arctic variable distribution is multiplied by an adjustment or correction distribution 

to obtain the Arctic variable distribution. The First Order Approach, when used

individually, did not adequately represent trends in the variability of the Arctic effects. 

The Second Order Approach, if not used in conjunction with the First Order Approach, 

resulted in arbitrary mean or expected values, because it was not tied directly to any real 

historical data. The optimal approach was to use the two methods, with the First Order 

Approach utilized to give the initial level of first order variability, and the Second Order 

Approach utilized to better reflect Arctic effects on the variability of causal events. In 

what follows, the discussion is based on the use of both methods in a complimentary 

fashion. 

4.3 Pipeline Fault Tree Analysis

4.3.1 Pipeline First Order Arctic Effects

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 in 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.
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

4.11

Table 4.4

Pipeline First Order Arctic Effect Summary

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.
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

4.12

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 Beaufort Sea. 

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 relatively 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 4.1. The frequency increments 

in this table are given as both the “expected” values and the “mode” values. 

The mode values are the mode values given in Table 2.9. The median values, 

however, are those calculated using the Monte Carlo method with the low, 

mode, and high values from Table 2.9, as inputs to the Monte Carlo. The

expected or median 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. 
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

4.13

4.3.2 Pipeline Second Order Arctic Effect Variations

The second order effects are incorporated 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 the first order effect reduction as its mode, with appropriate second 

order perturbations for the upper and lower 90% confidence interval bounds. Table 4.5 

summarizes these second order effect distributions. For the Arctic modified effects, given 

in the top of the table, the secondary distribution is simply the first order effect frequency 

change used as the mode of the distribution, and 90% upper and lower confidence 

interval changes given under the Min and Max column. 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.

4.3.3 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 = 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 3, 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 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 

4.8. 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 4.375 for shallow water, to 4.004 for medium depth water, and to 2.636 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. 
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

4.14

Table 4.5

Pipeline First and Second Order Arctic Effect Distribution Summary

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
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

4.15

Figure 4.4

Large Spill Frequencies for Pipeline

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

S 0.215 0.415 S 1.790 3.456

M 0.215 0.415 M 1.757 3.393

D 0.215 0.415 D 1.725 3.330

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

Dia<10" Dia>=10" P/L Size

All Values per 100000 km-year H 5.172 9.985 Historical Frequency

S 4.375 6.870 Shallow Water Depth Frequency

M 4.004 6.476 Medium Water Depth Frequency

D 2.636 5.086 Deep Water Depth Frequency

Dia<10" Dia>=10" Dia<10" Dia>=10"

H 0.398 0.768 H 0.000 0.000 H

S 0.287 0.553 S 0.000 0.000 S

M 0.287 0.553 M 0.000 0.000 M

D 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

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 1.693 1.693

0.398 0.768 M 0.000 0.000 M 1.347 1.347

0.406 0.784 D 0.000 0.000 D 0.003 0.003

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 0.001 0.001

M 0.199 0.384 M 0.000 0.000 M 0.001 0.001

D 0.199 0.384 D 0.000 0.000 D 0.001 0.001

Dia<10" Dia>=10"

H 0.000 0.000

S 0.339 0.339

M 0.269 0.269

D 0.001 0.001

Thaw Settlement

Other

NATURAL HAZARD

Mud Slide

Storm/ Hurricane

UNKNOWN ARCTIC

Ice Gouging Upheaval Buckling

Strudel Scour
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

4.16

Table 4.6

Arctic Pipeline Small Spill Frequencies

SMALL SPILLS 50-99 bbl

PipelinesDiameter <10" PipelinesDiameter =10"

Shallow Medium Deep Shallow Medium Deep

CAUSE 

CLASSIFICATION

HISTORICAL 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 16.67 0.862 (0.396) 0.466 12.70 (0.396) 0.466 13.00 (0.396) 0.466 14.38 0.555 (0.255) 0.300 11.91 (0.255) 0.300 12.33 (0.255) 0.300 14.38

External 5.56 0.287 (0.132) 0.155 4.23 (0.132) 0.155 4.33 (0.132) 0.155 4.79 0.185 (0.085) 0.100 3.97 (0.085) 0.100 4.11 (0.085) 0.100 4.79

Internal 11.11 0.575 (0.264) 0.311 8.47 (0.264) 0.311 8.67 (0.264) 0.311 9.58 0.370 (0.170) 0.200 7.94 (0.170) 0.200 8.22 (0.170) 0.200 9.58

THIRD PARTY 

IMPACT 38.89 2.011 (1.006) 1.006 27.40 (1.012) 1.000 27.87 (1.017) 0.994 30.64 1.294 (0.647) 0.647 25.69 (0.651) 0.643 26.44 (0.655) 0.640 30.64

Anchor Impact 33.33 1.724 (0.862) 0.862 23.48 (0.862) 0.862 24.03 (0.862) 0.862 26.58 1.109 (0.555) 0.555 22.02 (0.555) 0.555 22.80 (0.555) 0.555 26.57

Jackup Rig or 

Spud Barge

Trawl/Fishing Net 5.56 0.287 (0.144) 0.144 3.91 (0.150) 0.138 3.84 (0.155) 0.132 4.07 0.185 (0.092) 0.092 3.67 (0.096) 0.089 3.64 (0.100) 0.085 4.07

OPERATION 

IMPACT 16.67 0.862 (0.241) 0.621 16.92 (0.241) 0.621 17.32 (0.241) 0.621 19.15 0.555 (0.155) 0.400 15.86 (0.155) 0.400 16.43 (0.155) 0.400 19.15

Rig Anchoring 5.56 0.287 (0.080) 0.207 5.64 (0.080) 0.207 5.77 (0.080) 0.207 6.38 0.185 (0.052) 0.133 5.29 (0.052) 0.133 5.48 (0.052) 0.133 6.38

Work Boat 

Anchoring

11.11 0.575 (0.161) 0.414 11.28 (0.161) 0.414 11.54 (0.161) 0.414 12.77 0.370 (0.103) 0.266 10.58 (0.103) 0.266 10.95 (0.103) 0.266 12.76

MECHANICAL 11.11 0.575 0.575 15.66 0.575 16.02 0.575 17.72 0.370 0.370 14.68 0.370 15.20 0.370 17.72

Connection Failure 5.56 0.287 0.287 7.83 0.287 8.01 0.287 8.86 0.185 0.185 7.34 0.185 7.60 0.185 8.86

Material Failure 5.56 0.287 0.287 7.83 0.287 8.01 0.287 8.86 0.185 0.185 7.34 0.185 7.60 0.185 8.86

NATURAL 

HAZARD 11.11 0.575 (0.299) 0.275 7.50 (0.287) 0.287 8.01 (0.275) 0.299 9.23 0.370 (0.193) 0.177 7.04 (0.185) 0.185 7.60 (0.177) 0.193 9.23

Mud Slide 11.11 0.575 (0.299) 0.275 7.50 (0.287) 0.287 8.01 (0.275) 0.299 9.23 0.370 (0.193) 0.177 7.04 (0.185) 0.185 7.60 (0.177) 0.193 9.23

Storm/ Hurricane

ARCTIC 0.440 0.440 12.00 0.350 0.350 9.77 0.001 0.001 0.02 0.440 0.440 17.48 0.350 0.350 14.40 0.001 0.001 0.04

Ice Gouging 0.3495 0.3495 9.52 0.2796 0.2796 7.80 0.3495 0.3495 13.87 0.2796 0.2796 11.49

Strudel Scour 0.0021 0.0021 0.06 0.0021 0.0021 0.09

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 0.0002 0.0002 0.01 0.0002 0.0002 0.01 0.0002 0.0002 0.01 0.0002 0.0002 0.01 0.0002 0.0002 0.01 0.0002 0.0002 0.01

Other 0.0881 0.0881 2.40 0.0701 0.0701 1.95 0.0002 0.0002 0.00 0.0881 0.0881 3.50 0.0701 0.0701 2.88 0.0002 0.0002 0.01

UNKNOWN 5.56 0.287 0.287 7.83 0.287 8.01 0.287 8.86 0.185 0.185 7.34 0.185 7.60 0.185 8.86

TOTALS 100.00 5.172 (1.501) 3.671 100.00 (1.585) 3.587 100.00 (1.929) 3.243 100.00 3.328 (0.809) 2.519 100.00 (0.895) 2.433 100.00 (1.241) 2.087 100.00
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

4.17

Table 4.7

Arctic Pipeline Medium Spill Frequencies

MEDIUM SPILLS 100-999 bbl

PipelinesDiameter <10" PipelinesDiameter=10"

Shallow Medium Deep Shallow Medium Deep

CAUSE

CLASSIFICATION

HISTORICAL 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 16.67 1.509 (0.692) 0.816 12.69 (0.692) 0.816 12.99 (0.692) 0.816 14.38 1.387 (0.637) 0.750 12.55 (0.637) 0.750 12.88 (0.637) 0.750 14.38

External 5.56 0.503 (0.231) 0.272 4.23 (0.231) 0.272 4.33 (0.231) 0.272 4.79 0.462 (0.212) 0.250 4.18 (0.212) 0.250 4.29 (0.212) 0.250 4.79

Internal 11.11 1.006 (0.462) 0.544 8.46 (0.462) 0.544 8.66 (0.462) 0.544 9.58 0.924 (0.424) 0.500 8.37 (0.424) 0.500 8.58 (0.424) 0.500 9.58

THIRD PARTY 

IMPACT

38.89 3.520 (1.760) 1.760 27.36 (1.770) 1.749 27.85 (1.781) 1.739 30.64 3.236 (1.618) 1.618 27.08 (1.627) 1.608 27.61 (1.637) 1.599 30.64

Anchor Impact 33.33 3.017 (1.509) 1.509 23.45 (1.509) 1.509 24.01 (1.509) 1.509 26.58 2.773 (1.387) 1.387 23.21 (1.387) 1.387 23.80 (1.387) 1.387 26.58

Jackup Rig or Spud 

Barge

Trawl/Fishing Net 5.56 0.503 (0.251) 0.251 3.91 (0.262) 0.241 3.84 (0.272) 0.231 4.07 0.462 (0.231) 0.231 3.87 (0.241) 0.222 3.80 (0.250) 0.212 4.07

OPERATION 

IMPACT 16.67 1.509 (0.422) 1.087 16.90 (0.422) 1.087 17.30 (0.422) 1.087 19.15 1.387 (0.388) 0.999 16.72 (0.388) 0.999 17.15 (0.388) 0.999 19.15

Rig Anchoring 5.56 0.503 (0.141) 0.362 5.63 (0.141) 0.362 5.77 (0.141) 0.362 6.38 0.462 (0.129) 0.333 5.57 (0.129) 0.333 5.72 (0.129) 0.333 6.38

Work Boat Anchoring 11.11 1.006 (0.281) 0.725 11.27 (0.281) 0.725 11.53 (0.281) 0.725 12.77 0.924 (0.258) 0.666 11.15 (0.258) 0.666 11.43 (0.258) 0.666 12.77

MECHANICAL 11.11 1.006 1.006 15.64 1.006 16.01 1.006 17.72 0.924 0.924 15.47 0.924 15.87 0.924 17.72

Connection Failure 5.56 0.503 0.503 7.82 0.503 8.00 0.503 8.86 0.462 0.462 7.74 0.462 7.93 0.462 8.86

Material Failure 5.56 0.503 0.503 7.82 0.503 8.00 0.503 8.86 0.462 0.462 7.74 0.462 7.93 0.462 8.86

NATURAL HAZARD 11.11 1.006 (0.524) 0.482 7.49 (0.503) 0.503 8.00 (0.482) 0.524 9.23 0.924 (0.481) 0.443 7.42 (0.462) 0.462 7.93 (0.443) 0.481 9.23

Mud Slide 11.11 1.006 (0.524) 0.482 7.49 (0.503) 0.503 8.00 (0.482) 0.524 9.23 0.924 (0.481) 0.443 7.42 (0.462) 0.462 7.93 (0.443) 0.481 9.23

Storm/ Hurricane

ARCTIC 0.778 0.778 12.10 0.619 0.619 9.86 0.001 0.001 0.03 0.778 0.778 13.03 0.619 0.619 10.63 0.001 0.001 0.03

Ice Gouging 0.6178 0.6178 9.61 0.4943 0.4943 7.87 0.6178 0.6178 10.34 0.4943 0.4943 8.48

Strudel Scour 0.0038 0.0038 0.06 0.0038 0.0038 0.06

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 0.0004 0.0004 0.01 0.0004 0.0004 0.01 0.0004 0.0004 0.01 0.0004 0.0004 0.01 0.0004 0.0004 0.01 0.0004 0.0004 0.01

Other 0.1557 0.1557 2.42 0.1238 0.1238 1.97 0.0003 0.0003 0.01 0.1557 0.1557 2.61 0.1238 0.1238 2.13 0.0003 0.0003 0.01

UNKNOWN 5.56 0.503 0.503 7.82 0.503 8.00 0.503 8.86 0.462 0.462 7.74 0.462 7.93 0.462 8.86

TOTALS 100.00 9.051 (2.619) 6.432 100.00 (2.768) 6.283 100.00 (3.375) 5.676 100.00 8.320 (2.345) 5.975 100.00 (2.495) 5.826 100.00 (3.103) 5.218 100.00
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

4.18

Table 4.8

Arctic Pipeline Large Spill Frequencies

LARGE SPILLS 1000-9999 bbl

PipelinesDiameter <10" PipelinesDiameter =10"

Shallow Medium Deep Shallow Medium Deep

CAUSE 

CLASSIFICATION

HISTORICAL 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 8.16 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 8.16 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 40.92 (1.823) 1.757 43.89 (1.855) 1.725 65.44 6.912 (3.456) 3.456 50.31 (3.520) 3.393 52.38 (3.582) 3.330 65.48

Anchor Impact 30.77 1.591 (0.796) 0.796 18.19 (0.796) 0.796 19.87 (0.796) 0.796 30.18 3.072 (1.536) 1.536 22.36 (1.536) 1.536 23.72 (1.536) 1.536 30.20

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 27.71 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 10.87 0.768 (0.215) 0.553 8.05 (0.215) 0.553 8.54 (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 10.87 0.768 (0.215) 0.553 8.05 (0.215) 0.553 8.54 (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 15.40 1.536 (0.784) 0.752 10.95 (0.768) 0.768 11.86 (0.752) 0.784 15.41

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 1.693 1.693 38.70 1.347 1.347 33.64 0.003 0.003 0.12 1.693 1.693 24.64 1.347 1.347 20.80 0.003 0.003 0.06

Ice Gouging 1.3438 1.3438 30.72 1.0750 1.0750 26.85 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 0.0008 0.0008 0.02 0.0008 0.0008 0.02 0.0008 0.0008 0.03 0.0008 0.0008 0.01 0.0008 0.0008 0.01 0.0008 0.0008 0.02

Other 0.3386 0.3386 7.74 0.2694 0.2694 6.73 0.0006 0.0006 0.02 0.3386 0.3386 4.93 0.2694 0.2694 4.16 0.000 6 0.0006 0.01

UNKNOWN

TOTALS 100.00 5.172 (0.797) 4.375 100.00 (1.168) 4.004 100.00 (2.536) 2.636 100.00 9.985 (3.114) 6.870 100.00 (3.508) 6.476 100.00 (4.898) 5.086 100.00
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

4.19

Table 4.9

Arctic Pipeline Huge Spill Frequencies

HUGE SPILLS =>10000 bbl

PipelinesDiameter <10" PipelinesDiameter=10"

Shallow Medium Deep Shallow Medium Deep CAUSE 

CLASSIFICATION

HISTORICAL 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 8.16 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 8.16 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 39.11 (0.456) 0.439 42.19 (0.464) 0.431 65.43 2.304 (1.152) 1.152 52.37 (1.173) 1.131 54.19 (1.194) 1.110 65.48

Anchor Impact 30.77 0.398 (0.199) 0.199 17.38 (0.199) 0.199 19.10 (0.199) 0.199 30.18 1.024 (0.512) 0.512 23.28 (0.512) 0.512 24.54 (0.512) 0.512 30.20

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 7.54 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 17.38 (0.207) 0.191 18.31 (0.215) 0.183 27.71 1.024 (0.512) 0.512 23.28 (0.533) 0.491 23.52 (0.554) 0.470 27.73

OPERATION 

IMPACT 7.69 0.099 (0.028) 0.072 6.26 (0.028) 0.072 6.88 (0.028) 0.072 10.87 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 10.87 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 15.40 0.512 (0.261) 0.251 11.40 (0.256) 0.256 12.27 (0.251) 0.261 15.41

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 7.86

Storm/ Hurricane 7.69 0.099 (0.050) 0.050 4.35 (0.050) 0.050 4.78 (0.050) 0.050 7.54 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 41.42 0.377 0.377 36.21 0.001 0.001 0.13 0.474 0.474 21.55 0.377 0.377 18.07 0.001 0.001 0.05

Ice Gouging 0.3762 0.3762 32.87 0.3010 0.3010 28.90 0.3762 0.3762 17.10 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 0.0002 0.0002 0.02 0.0002 0.0002 0.02 0.0002 0.0002 0.03 0.0002 0.0002 0.01 0.0002 0.0002 0.01 0.0002 0.0002 0.01

Other 0.0948 0.0948 8.28 0.0754 0.0754 7.24 0.0002 0.0002 0.03 0.0948 0.0948 4.31 0.0754 0.0754 3.61 0.0002 0.0002 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 (1.128) 2.200 100.00 (1.241) 2.087 100.00 (1.633) 1.695 100.00
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

4.20

Table 4.10

Arctic Pipeline Spill Frequencies Expected Value Summary

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 4.375 4.004 2.636 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
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

4.21

4.4 Platform Fault Tree Analysis

4.4.1 Platform First Order Arctic Effects

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 30 to 50% 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 

percent. 

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. 

4.4.2 Platform Second Order Arctic Effects

Changes in frequency distribution attributable to Arctic effects were calculated using the 

second order 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.

4.4.3 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 greater than 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.
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

4.22

 Table 4.11

Platform First Order Arctic Effect Summary

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 above.
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

4.23

Table 4.12

Platform First and Second Order Arctic Effects Distribution Summary

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
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

4.24

Figure 4.5

Spill Frequencies Platform Fault Tree 

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.
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

4.25

Table 4.13

Platform Small and Medium Spill Frequencies

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
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

4.26

Table 4.14

Platform Large and Huge Spill Frequencies

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
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

4.27

Table 4.15

Arctic Platforms Spill Frequency Expected Value Summary

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 1.703 1.828

LARGE AND HUGE SPILLS

=1000 bbl .359 .274 .288 .309
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

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 or second 

order 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. 
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

4.29

Table 4.16

Well Fault Tree Analysis Arctic Effect Summary

Historical Expected Frequency 

Change % Reason 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 

logis tics 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 

logistics support in shallow water.
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

4.30

Table 4.17

Arctic Well Blowout Frequencies

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
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

4.31

Table 4.18

Summary of Spill Size Distribution Parameters

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 150000 68349 150000 200000 250000 200000 
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

5.1

CHAPTER 5

OIL SPILL OCCURRENCE INDICATOR QUANTIFICATION

5.1 Definition of Oil Spill Occurrence Indicators

Three 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 indicator.

The spill indicators defined above are subdivided as follows for this study:

ß By scenario (five scenarios).

ß By water depth (three ranges).

ß By facility type (six types).

ß By spill size (four sizes).

ß By year (average of 35 years).

There are a total of five scenarios that are four Arctic scenarios – Sales 1, 2, and 3, and 

their composite (Sale All) – and the fifth scenario, the non-Arctic version of Sale All. The 

five scenarios are shown in Figure 5.1. 

The above combinations translate into 360 sets of spill indicators, for a total of 1,080

individual indicators. Given that these are calculated for each year, this gives 43,740

indicators. In this chapter, we will try to summarize only the salient results of the 

indicators; the appendices give the full calculation printouts for the Monte Carlo results 

used in 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 deals with 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.
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

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 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 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

Development Well D.

Beaufort Sea

All Sales

Production Well

Exploration Well D.

Historical Data Analysis

Beaufort Sea

All Sales Non Arctic

Beaufort Sea

Sale 3

Platform

Beaufort Sea

Sale 2

Beaufort Sea

Sale 1

Facility
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

5.3

5.3 Summary of Beaufort Sea Oil Spill Occurrence Indicators

5.3.1 Sale 1 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 2033 as

described in Appendix 3. Further, each of the indicators has been subdivided into three 

segments for each year, those corresponding to spills < 1,000 bbl (small and medium), 

spills = 1,000 < 10,000 bbl (large), and spills =10,000 bbl (huge). It should be noted that 

the spill frequency associated with each spill size is only the increment shown in each of 

the bars. Thus, for example, for the year 2020, small and medium spills are

approximately 18.0 per thousand years. Next, in that year, large spills are approximately 

6.0 per thousand years, as shown in the second bar increment (i.e., 24.0 – 18.0 = 6.0). 

Finally, the top increment corresponds to huge spills, and is approximately 4.0 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. Clearly, the spill index is dominated by 

the huge spills, which have an average spill size of 15,000 bbl. The spills per barrel 

produced continue to rise to the peak production year of 2016, 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 for Sale 1 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 each lease sale or development scenario, a Monte 

Carlo analysis was carried out for each year, with the distributed inputs described earlier. 

For Lease Sale 1, 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 (2016). 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 40% probability that a spill frequency will 

be no more than 0.28 per billion barrels produced.
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

5.4

Sale 1 - Spill Frequency

0

4

8

12

16

20

24

28

32

20042005200620072008200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038

Spill Frequency per 1000 years

Huge Spills

=>10000 bbl

Large Spills

1000-9999 bbl

Small and Medium Spills

50-999 bbl

Sale 1 - Spill Frequency per 109 bbl Produced

0.0

0.4

0.8

1.2

1.6

2.0

2.4

2.8

3.2

3.6

20042005200620072008200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038

Spill Frequency per 10

9 bbl Produced

Huge Spills

=>10000 bbl

Large Spills

1000-9999 bbl

Small and Medium Spills

50-999 bbl

Figure 5.2

Sale 1 Spill Frequency per 1,000 Years

Figure 5.3

Sale 1 Spill Frequency per 109 Barrels Produced
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

5.5

Sale 1 - Spill Index

0

50

100

150

200

250

300

350

400

450

500

550

20042005200620072008200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038

Spill Index [bbl]

Huge Spills

=>10000 bbl

Large Spills

1000-9999 bbl

Small and Medium Spills

50-999 bbl

Figure 5.4

Sale 1 Spill Index 
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

5.6

Sale 1 - Spill Frequency - P/L

0

4

8

12

16

20

24

28

32

20042005200620072008200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038

Spill Frequency per 1000 years

Huge Spills

=>10000 bbl

Large Spills

1000-9999 bbl

Small and Medium Spills

50-999 bbl

Sale 1 - Spill Frequency per 109 bbl Produced - P/L

0.0

0.4

0.8

1.2

1.6

2.0

2.4

2.8

3.2

3.6

20042005200620072008200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038

Spill Frequency per 10

9 bbl produced

Huge Spills

=>10000 bbl

Large Spills

1000-9999 bbl

Small and Medium Spills

50-999 bbl

Sale 1 - Spill Index - P/L

0

5 0

100

150

200

250

300

350

400

450

500

550

20042005200620072008200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038

Spill Index [bbl]

Huge Spills

=>10000 bbl

Large Spills

1000-9999 bbl

Small and Medium Spills

50-999 bbl

Figure 5.5

Sale 1 Indicators – Pipeline – Spill Frequency per 1,000 Years
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

5.7

Sale 1 - Spill Frequency - Platforms

0

4

8

12

16

20

24

28

32

20042005200620072008200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038

Spill Frequency per 1000 years

Large and Huge Spills

=>1000 bbl

Small and Medium Spills

50-999 bbl

Sale 1 - Spill Frequency per 109 bbl Produced - Platforms

0.0

0.4

0.8

1.2

1.6

2.0

2.4

2.8

3.2

3.6

20042005200620072008200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038

Spill Frequency per 10

9 bbl produced

Large and Huge Spills

=>1000 bbl

Small and Medium Spills

50-999 bbl

Sale 1 - Spill Index - Platforms

0

5 0

100

150

200

250

300

350

400

450

500

550

20042005200620072008200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038

Spill Index [bbl]

Large and Huge Spills

=>1000 bbl

Small and Medium Spills

50-999 bbl

Figure 5.6

Sale 1 Indicators – Platforms – Spill Frequency per 1,000 Years
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

5.8

Sale 1 - Spill Frequency - Wells

0

4

8

12

16

20

24

28

32

20042005200620072008200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038

Spill Frequency per 1000 years

Huge Spills

=>10000 bbl

Large Spills

1000-9999 bbl

Small and Medium Spills

50-999 bbl

Sale 1 - Spill Frequency per 10 9 bbl Produced - Wells

0.0

0.4

0.8

1.2

1.6

2.0

2.4

2.8

3.2

3.6

20042005200620072008200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038

Spill Frequency per 10

9 bbl produced

Huge Spills

=>10000 bbl

Large Spills

1000-9999 bbl

Small and Medium Spills

50-999 bbl

Sale 1 - Spill Index - Wells

0

5 0

100

150

200

250

300

350

400

450

500

550

20042005200620072008200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038

Spill Index [bbl]

Huge Spills

=>10000 bbl

Large Spills

1000-9999 bbl

Small and Medium Spills

50-999 bbl

Figure 5.7

Sale 1 Indicators – Wells – Spill Frequency per 1,000 Years
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

5.9

Table 5.1

Sale 1 Year 2016 – Monte Carlo Results

SALE 1

Year 2016

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 = 17.50 7.45 5.90 13.35 30.85 0.40 0.17 0.13 0.30 0.70 7.58 54.14 453.92 508.06 515.64

Std Deviation = 6.85 2.38 1.38 3.12 7.58 0.16 0.05 0.03 0.07 0.17 5.09 25.33 166.83 168.75 168.83

Variance = 46.991 5.654 1.903 9.706 57.430 0.024 0.003 0.001 0.005 0.030 25.875 641.728 27830.730 28477.370 28504.210

Skewness = 0.57 0.49 0.18 0.25 0.45 0.57 0.49 0.18 0.25 0.45 1.51 0.75 0.47 0.47 0.47

Kurtosis = 2.81 2.93 2.83 2.90 2.82 2.81 2.93 2.83 2.90 2.82 5.90 3.49 3.15 3.18 3.17

Mode = 14.87 6.40 6.33 11.98 33.42 0.61 0.15 0.16 0.27 0.76 3.99 38.10 336.73 403.87 238.43

Minimum = 3.665 1.394 2.076 4.074 12.206 0.084 0.032 0.047 0.093 0.279 0 0.048 -5.653 57.627 89.063 100.160

5% Perc = 8.076 3.992 3.705 8.488 19.551 0.184 0.091 0.085 0.194 0.446 5 1.930 19.473 203.555 254.737 261.714

10% Perc = 9.265 4.598 4.127 9.457 21.641 0.212 0.105 0.094 0.216 0.494 1

0 2.578 24.401 247.551 300.820 308.648

15% Perc = 10.270 5.022 4.439 10.087 22.946 0.234 0.115 0.101 0.230 0.524 1

5

3.060 28.576 280.502 332.078 339.452

20% Perc = 11.235 5.354 4.707 10.666 24.124 0.257 0.122 0.107 0.244 0.551 2

0 3.527 31.871 309.260 359.667 367.135

25% Perc = 12.128 5.670 4.941 11.157 25.226 0.277 0.129 0.113 0.255 0.576 2

5 3.959 35.321 334.223 386.799 393.868

30% Perc = 12.989 5.971 5.116 11.576 26.248 0.297 0.136 0.117 0.264 0.599 3

0 4.390 38.345 355.170 410.086 418.341

35% Perc = 13.921 6.282 5.311 11.995 27.182 0.318 0.143 0.121 0.274 0.621 3

5 4.842 41.377 378.285 431.522 439.141

40% Perc = 14.716 6.555 5.506 12.425 28.082 0.336 0.150 0.126 0.284 0.641 4

0 5.303 44.483 400.053 452.817 460.282

45% Perc = 15.575 6.863 5.681 12.802 28.931 0.356 0.157 0.130 0.292 0.661 4

5 5.786 47.460 420.241 475.868 483.356

50% Perc = 16.524 7.166 5.858 13.237 29.860 0.377 0.164 0.134 0.302 0.682 5

0 6.233 50.572 440.511 495.134 503.779

55% Perc = 17.509 7.483 6.045 13.634 31.058 0.400 0.171 0.138 0.311 0.709 5

5 6.822 53.834 460.705 516.303 524.229

60% Perc = 18.530 7.825 6.241 13.987 32.172 0.423 0.179 0.142 0.319 0.735 6

0 7.465 57.228 482.578 537.060 545.385

65% Perc = 19.589 8.174 6.404 14.414 33.330 0.447 0.187 0.146 0.329 0.761 6

5

8.144 60.767 505.826 561.518 568.816

70% Perc = 20.739 8.559 6.598 14.840 34.578 0.473 0.195 0.151 0.339 0.789 7

0

8.864 65.029 532.804 587.964 596.134

75% Perc = 22.154 9.023 6.828 15.352 35.978 0.506 0.206 0.156 0.350 0.821 7

5 9.854 69.273 559.280 615.176 621.757

80% Perc = 23.441 9.480 7.073 15.948 37.394 0.535 0.216 0.161 0.364 0.854 8

0 10.915 74.410 591.103 646.552 653.645

85% Perc = 24.998 10.051 7.342 16.611 39.225 0.571 0.229 0.168 0.379 0.896 8

5 12.365 80.256 628.854 685.742 693.119

90% Perc = 27.201 10.754 7.710 17.483 41.113 0.621 0.246 0.176 0.399 0.939 9

0 14.407 88.387 676.355 732.058 740.066

95% Perc = 30.205 11.653 8.247 18.771 44.481 0.690 0.266 0.188 0.429 1.016 9

5 17.787 102.136 746.994 804.537 811.342

Maximum = 45.353 17.402 10.734 24.254 58.144 1.035 0.397 0.245 0.554 1.327 #

# 34.668 159.414 1141.096 1187.318 1190.433

5.9
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

5.10

 Spill Frequency - CDF Sale 1 Year 2016

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 %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

 Spill Frequency - CDF Sale 1 Year 2016

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

 Spill Frequency per bbl Produced - CDF Sale 1 Year 2016

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

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 Sale 1 Year 2016

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

Spill Frequency per 10^9 bbl Produced

CDF %

Significant Spills

=>1000 bbl

All Spills

 Spill Index - CDF Sale 1 Year 2016

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

 Spill Index - CDF Sale 1 Year 2016

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

Figure 5.8

Sale 1 Spill Indicator Distributions – Year 2016 – Spill Frequency per 1,000 Years
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

5.11

In other words, there is a 40% chance that large and huge spills will occur at a rate of 

0.28 per billion or less. Conversely, there is a 60% chance that the small and medium 

spill rate will be greater than 0.28 per billion. 

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 (3.992) is 55% of the mean (7.166); the upper bound (11.653), 160% 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 variabiltiy of

frequency per billion barrels produced.

5.3.2 Sale 2 Oil Spill Occurrence Indicators

Figure 5.11 summarizes the three oil spill occurrence indicators for Sale 2. The primary 

difference is one of scheduling with some differences in magnitude of the indicators, 

although they are not substantially different from those of Sale 1. 

5.3.3 Sale 3 Oil Spill Occurrence Indicators

Figure 5.12 summarizes all three of the Sale 3 oil spill occurrence indicators. Again, 

these are not substantially different from the Sale 1 and 2 indicators.

5.3.4 Sale All Oil Spill Occurrence Indicators

The oil spill occurrence indicators for the composite or total of all three Beaufort Sea 

Sale development scenarios are summarized in Figure 5.13. As one would expect, the 

absolute values of spill frequencies are significantly higher than any of the sales, 

essentially because they are the sum, through the Monte Carlo iteration process, of the 

three sales spill frequencies. Spills per barrel produced tend to be the same as those of the 

individual sales. Finally, the spill index, which is the product of the frequency and 

average spill size, as one would expect, is significantly higher for the composite scenario, 

roughly three times the average value for the three sales. Naturally, the spill by facility 

breakdowns, the Monte Carlo results, and all the details of the calculations for the 

composite scenario as well as each individual sale scenario are given in Appendix 3.
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

5.12

Table 5.2

Composition of Spill Indicators – Sale 1 – Life of Field Average

Spill Source Spill Size

Pipelines 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

Sale 1 - Life of Field Average

Spill Frequency per 10^3 years

Spill Source

Sale 1 - Life of Field Average

Spill Frequency per 10^3 years

Small and Medium Spills

50-999 bbl 2.892 49% 6.090 86% 0.422 11% 6.512 60% 9.404 56% Pipelines 2.892 31% 2.318 57% 0.744 22% 3.062 41% 5.953 35%

Large Spills

1000-9999 bbl 2.318 39% 0.516 7% 1.265 33% 1.781 16% 4.099 24% Platforms 6.090 65% 0.516 13% 0.516 15% 1.031 14% 7.122 42%

Huge Spills

 =>10000 bbl 0.744 12% 0.516 7% 2.110 56% 2.626 24% 3.369 20% Wells 0.422 4% 1.265 31% 2.110 63% 3.375 45% 3.797 23%

Significant Spills

=>1000 bbl 3.062 51% 1.031 14% 3.375 89% 4.406 40% 7.468 44% Platformsand Wells 6.512 69% 1.781 43% 2.626 78% 4.406 59% 10.918 65%

All Spills 5.953 100% 7.122 100% 3.797 100% 10.918 100% 16.872 100% All 9.404 100% 4.099 100% 3.369 100% 7.468 100% 16.872 100%

Sale 1 - Life of Field Average

Spill Frequency per 10^9 bbl produced

Sale 1 - Life of Field Average

Spill Frequency per 10^9 bbl produced

Small and Medium Spills

50-999 bbl 0.188 49% 0.397 86% 0.027 11% 0.424 60% 0.612 56% Pipelines 0.188 31% 0.151 57% 0.048 22% 0.199 41% 0.388 35%

Large Spills

1000-9999 bbl 0.151 39% 0.034 7% 0.082 33% 0.116 16% 0.267 24% Platforms 0.397 65% 0.034 13% 0.034 15% 0.067 14% 0.464 42%

Huge Spills

 =>10000 bbl 0.048 12% 0.034 7% 0.137 56% 0.171 24% 0.219 20% Wells 0.027 4% 0.082 31% 0.137 63% 0.220 45% 0.247 23%

Significant Spills

=>1000 bbl 0.199 51% 0.067 14% 0.220 89% 0.287 40% 0.486 44% Platformsand Wells 0.424 69% 0.116 43% 0.171 78% 0.287 59% 0.711 65%

All Spills 0.388 100% 0.464 100% 0.247 100% 0.711 100% 1.098 100% All 0.612 100% 0.267 100% 0.219 100% 0.486 100% 1.098 100%

Sale 1 - Life of Field Average

Spill Index [bbl]

Sale 1 - Life of Field Average

Spill Index [bbl]

Small and Medium Spills

50-999 bbl 1 5% 3 32% 0 0% 3 1% 4 1% Pipelines 1 27% 12 39% 12 4% 24 8% 25 8%

Large Spills

1000-9999 bbl 12 49% 3 34% 16 6% 19 7% 31 10% Platforms 3 67% 3 10% 3 1% 6 2% 9 3%

Huge Spills

 =>10000 bbl 12 47% 3 34% 255 94% 258 92% 270 89% Wells 0 5% 16 51% 255 95% 271 90% 271 89%

Significant Spills

=>1000 bbl 24 95% 6 68% 271 100% 277 99% 300 99% Platformsand Wells 3 73% 19 61% 258 96% 277 92% 280 92%

All Spills 25 100% 9 100% 271 100% 280 100% 304 100% All 4 100% 31 100% 270 100% 300 100% 304 100%

5.12
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

5.13

Figure 5.9

Sale 1 Life of Field Average Spill Frequency

CDF Sale 1 LOF Average - Pipeline

0

10

20

30

40

50

60

70

80

90

100

0 1 2 3 4 5 6 7 8 9 10 11 12

Spill Frequency per 1000 years

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale 1 LOF Average - Pipeline

0

10

20

30

40

50

60

70

80

90

100

0 1 2 3 4 5 6 7 8 9 10 11 12

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale 1 LOF Average - Platforms

0

10

20

30

40

50

60

70

80

90

100

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

Spill Frequency per 1000 years

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale 1 LOF Average - Platforms

0

10

20

30

40

50

60

70

80

90

100

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale 1 LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

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

Spill Frequency per 1000 years

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale 1 LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

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

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale 1 LOF Average - Platforms + Wells

0

10

20

30

40

50

60

70

80

90

100

0 2 4 6 8 10 12 14 16 1 8 2 0

Spill Frequency per 1000 years

CDF %

Small and Medium

Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale 1 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 %

Significant Spills

=>1000 bbl

All Spills

CDF Sale 1 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

Spill Frequency per 1000 years

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale 1 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

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

5.14

Figure 5.10

Sale 1 Life of Field Average Spills per Barrel Produced

CDF Sale 1 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

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 Sale 1 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

Spill Frequency per 10^9 bbl Produced

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale 1 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 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 Sale 1 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 0.9 1.0

Spill Frequency per 10^9 bbl Produced

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale 1 LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4 0.5

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 Sale 1 LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4 0.5

Spill Frequency per 10^9 bbl Produced

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale 1 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 0.9 1.0 1.1 1.2

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 Sale 1 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 0.9 1.0 1.1 1.2

Spill Frequency per 10^9 bbl Produced

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale 1 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

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 Sale 1 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

Spill Frequency per 10^9 bbl Produced

CDF %

Significant Spills

=>1000 bbl

All Spills
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

5.15

Figure 5.11

Sale 2 Spill Indicators

Sale 2 - Spill Frequency

0

4

8

12

16

20

24

28

32

20042005200620072008200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038

Spill Frequency per 1000 years

Huge Spills

=>10000 bbl

Large Spills

1000-9999 bbl

Small and Medium Spills

50-999 bbl

Sale 2 - Spill Frequency per 109 bbl Produced

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.0

2.2

2.4

2.6

2.8

3.0

3.2

3.4

3.6

3.8

20042005200620072008200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038

Spill Frequency per 10

9 bbl Produced

Huge Spills

=>10000 bbl

Large Spills

1000-9999 bbl

Small and Medium Spills

50-999 bbl

Sale 2 - Spill Index

0

5 0

100

150

200

250

300

350

400

450

500

550

20042005200620072008200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038

Spill Index [bbl]

Huge Spills

=>10000 bbl

Large Spills

1000-9999 bbl

Small and Medium Spills

50-999 bbl
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

5.16

Figure 5.12

Sale 3 Spill Indicators

Sale 3 - Spill Frequency

0

2

4

6

8

10

12

14

16

18

20

22

24

26

28

30

20042005200620072008200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038

Spill Frequency per 1000 years

Huge Spills

=>10000 bbl

Large Spills

1000-9999 bbl

Small and Medium Spills

50-999 bbl

Sale 3 - Spill Frequency per 109 bbl Produced

0.0

0.4

0.8

1.2

1.6

2.0

2.4

2.8

3.2

3.6

4.0

4.4

4.8

20042005200620072008200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038

Spill Frequency per 10

9 bbl Produced

Huge Spills

=>10000 bbl

Large Spills

1000-9999 bbl

Small and Medium Spills

50-999 bbl

Sale 3 - Spill Index

0

5 0

100

150

200

250

300

350

400

450

500

550

20042005200620072008200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038

Spill Index [bbl]

Huge Spills

=>10000 bbl

Large Spills

1000-9999 bbl

Small and Medium Spills

50-999 bbl
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

5.17

Figure 5.13

Sale All Spill Indicators

Sale All - Spill Frequency

0

10

20

30

40

50

60

70

80

90

100

20042005200620072008200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038

Spill Frequency per 1000 years

Huge Spills

=>10000 bbl

Large Spills

1000-9999 bbl

Small and Medium Spills

50-999 bbl

Sale All - 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

20042005200620072008200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038

Spill Frequency per 10

9 bbl Produced

Huge Spills

=>10000 bbl

Large Spills

1000-9999 bbl

Small and Medium Spills

50-999 bbl

Sale All - Spill Index

0

100

200

300

400

500

600

700

800

900

1000

1100

1200

1300

1400

1500

1600

20042005200620072008200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038

Spill Index [bbl]

Huge Spills

=>10000 bbl

Large Spills

1000-9999 bbl

Small and Medium Spills

50-999 bbl
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

5.18

5.3.5 Sale All Comparative Non-Arctic Indicator Assessment

To give an idea of the effect of the frequency variations introduced in Chapter 4, the 

composite (Sale All) Beaufort 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 composite scenario would behave as if they were in the Gulf of Mexico 

environment rather than in the Arctic environment. Figures 5.14, 5.15, and 5.16 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 30%. The spills per barrel 

produced are also significantly reduced, as can be seen in Figure 5.15. However, the spill 

index, because of the disproportionate effect of large spills, shows only a reduction of 

approximately 40%. What the comparison shows is that the Arctic development scenarios 

can be expected to have a lower oil spill occurrence than similar development scenarios 

in the GOM.

5.4 Summary of Representative Oil Spill Occurrence Indicator Results

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

vary by spill size and location? Table 5.3 summarizes the Life of Field average spill 

indicator values for representative years. Figure 5.17 illustrates these. The following can 

be observed from Table 5.3. 

ß Each spill indicator for Sale 1, 2, and 3 is similar in value. The indicators are 

higher for the composite “Sale All” scenario.

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

increasing spill size for all scenarios. 

ß The spill index increases dramatically with spill size for all scenarios.

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

counterparts. Non-Arctic spill indicators are approximately 40% greater.
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

5.19

Figure 5.14

Beaufort Sea Sale All Spill Frequency – Arctic and Non-Arctic

Figure 5.15

Beaufort Sea Sale All Spill Frequency per 109 Barrels Produced –

Arctic and Non-Arctic 

Beaufort Sea Sale All Spill Frequency

0

10

20

30

40

50

60

70

80

90

100

110

120

130

140

20042005200620072008200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038

Spill Frequency per 1000 years

Non Arctic Spills

Arctic Spills

Beaufort Sea Sale All 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

20042005200620072008200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038

Spill Frequency per 10^9 bbl produced

Non Arctic Spills

Arctic Spills
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

5.20

Figure 5.16

Beaufort Sea Sale All Spill Index – Arctic and Non-Arctic

Beaufort Sea Sale All Spill Index

0

200

400

600

800

1000

1200

1400

1600

1800

2000

2200

20042005200620072008200920102011201220132014201520162017201820192020202120222023202420252026202720282029203020312032203320342035203620372038

Spill Index [bbl]

Non Arctic Spills

Arctic Spills
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

5.21

Table 5.3

Summary of Average Spill Indicators for All Scenarios

SALE 1 SALE 2 SALE 3 SALE All SALE All

non Arctic

Spill Indicators

Life of Field

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]

Spill Frequency per 10^3 years

Spill Frequen cy per 10^9 bbl 

produced

Spill Index [bbl]

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

Small and Medium Spills 9.404 0.612 4 9.586 0.674 4 11.320 0.714 5 26.204 0.667 11 38.900 0.990 15

50-999 bbl 56% 56% 1% 57% 57% 1% 57% 57% 1% 57% 57% 1% 58% 58% 1%

Large Spills 4.099 0.267 31 3.989 0.281 30 4.575 0.289 35 10.951 0.279 82 15.653 0.398 117

1000-9999 bbl 24% 24% 10% 24% 24% 10% 23% 23% 10% 24% 24% 10% 23% 23% 10%

Huge Spills 3.369 0.219 270 3.323 0.234 268 3.901 0.246 317 9.158 0.233 740 12.956 0.330 1048

=>10000 bbl 20% 20% 89% 20% 20% 89% 20% 20% 89% 20% 20% 89% 19% 19% 89%

Significant Spills 7.468 0.486 300 7.312 0.514 298 8.476 0.535 352 20.109 0.512 822 28.608 0.728 1165

=>1000 bbl 44% 44% 99% 43% 43% 99% 43% 43% 99% 43% 43% 99% 42% 42% 99%

16.872 1.098 304 16.897 1.188 302 19.796 1.249 357 46.313 1.178 833 67.508 1.718 1180 All Spills 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%

5.953 0.388 25 5.899 0.415 23 6.551 0.413 26 15.925 0.405 64 27.192 0.692 96 Pipeline Spills

35% 35% 8% 35% 35% 8% 33% 33% 7% 34% 34% 8% 40% 40% 8%

7.122 0.464 9 7.210 0.507 9 8.751 0.552 11 19.947 0.508 24 25.562 0.650 30 Platform Spills 42% 42% 3% 43% 43% 3% 44% 44% 3% 43% 43% 3% 38% 38% 3%

3.797 0.247 271 3.787 0.266 271 4.494 0.283 321 10.441 0.266 746 14.755 0.375 1054 Well Spills 23% 23% 89% 22% 22% 89% 23% 23% 90% 23% 23% 89% 22% 22% 89%

10.918 0.711 280 10.998 0.773 279 13.245 0.835 331 30.388 0.773 770 40.317 1.026 1084 Platform and Well Spills 65% 65% 92% 65% 65% 92% 67% 67% 93% 66% 66% 92% 60% 60% 92%

16.872 1.098 304 16.897 1.188 302 19.796 1.249 357 46.313 1.178 833 67.508 1.718 1180 All Spills

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

5.21
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

5.22

Figure 5.17

Life of Field Spill Indicators – By Spill Size

Life of Field Average

0

2

4

6

8

10

12

14

16

18

20

Spill Frequency

per 1000 years

Huge Spills

=>10000 bbl

3.369 3.323 3.901

Large Spills

1000-9999 bbl

4.099 3.989 4.575

Small and Medium Spills

50-999 bbl

9.404 9.586 11.320

SALE 1 SALE 2 SALE 3

Life of Field Average

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

Spill Frequency

 per 10^9 bbl produced

Huge Spills

=>10000 bbl

0.219 0.234 0.246

Large Spills

1000-9999 bbl

0.267 0.281 0.289

Small and Medium Spills

50-999 bbl

0.612 0.674 0.714

SALE 1 SALE 2 SALE 3

Life of Field Average

0

50

100

150

200

250

300

350

400

Spill Index [bbl]

Huge Spills

=>10000 bbl

270 268 317

Large Spills

1000-9999 bbl

31 30 35

Small and Medium Spills

50-999 bbl

4 4 5

SALE 1 SALE 2 SALE 3
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

5.23

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 5.18. Table 5.3 and Figure 5.18 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 Platforms contribute the most (43%) to the two spill frequency indicators, but 

the least (3%) to the spill index. 

ß Pipelines are next in relative contribution to spill frequencies (34%) and 

intermediate in contribution to spill index (8%). 

ß Wells are by far (at 89%) the highest contributors to spill index, while 

platforms and wells together are responsible for a 92% contribution to the spill 

index. 

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

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

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

about the same number as platforms.

Figures 5.19 and 5.20 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. 
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

5.24

Figure 5.18

Life of Field Spill Indicators – By Source Composition

Life of Field Average

0

10

20

30

40

50

60

70

Spill Frequency

per 1000 years

Well Spills 3.797 3.787 4.494 10.441 14.755

Platform Spills 7.122 7.210 8.751 19.947 25.562

Pipeline Spills 5.953 5.899 6.551 15.925 27.192

SALE 1 SALE 2 SALE 3 SALE All SALE All

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 0.247 0.266 0.283 0.266 0.375

Platform Spills 0.464 0.507 0.552 0.508 0.650

Pipeline Spills 0.388 0.415 0.413 0.405 0.692

SALE 1 SALE 2 SALE 3 SALE All

SALE All

non Arctic

Life of Field Average

0

200

400

600

800

1000

1200

Spill Index [bbl]

Well Spills 271 271 321 746 1054

Platform Spills 9 9 11 24 30

Pipeline Spills 25 23 26 64 96

SALE 1 SALE 2 SALE 3 SALE All SALE All

non Arctic
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

5.25

BY SPILL SOURCE BY SPILL SIZE

Figure 5.19

Sale All – Year 2024 – Spill Indicator Composition by Source and Spill Size

Sale All- Year 2024

 Spill Frequency per 10^3 years

58%

23%

19%

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

 =>10000 bbl

TOTAL 90.976

Sale All - Year 2024

 Spill Frequency per 10^9 bbl produced

23%

58%

19%

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

 =>10000 bbl

TOTAL 1.149

Sale All - Year 2024

 Spill Index [bbl]

1%

89%

10%

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

 =>10000 bbl

TOTAL 1534

Sale All - Year 2024

 Spill Frequency per 10^3 years

44%

35%

21%

Pipelines

Platforms

Wells TOTAL 90.976

Sale All - Year 2024

 Spill Frequency per 10^9 bbl produced

44%

35%

21%

Pipelines

Platforms

Wells TOTAL 1.149

Sale All - Year 2024

 Spill Index [bbl]

89%

8%

Pipelines 3%

Platforms

Wells TOTAL 1534
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

5.26

BY SPILL SOURCE BY SPILL SIZE

Figure 5.20

Sale All – Life of Field Average Spill Indicator Composition by Source and Spill Size

Sale All - LOF Average

 Spill Frequency per 10^3 years

56%

20%

24%

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

 =>10000 bbl

TOTAL 46.313

Sale All - LOF Average

 Spill Frequency per 10^9 bbl produced

56%

24%

20%

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

 =>10000 bbl

TOTAL 1.178

Sale All - LOF Average

 Spill Index [bbl]

1%

89%

10%

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

 =>10000 bbl

TOTAL 833

Sale All - LOF Average

 Spill Frequency per 10^3 years

35%

43% 22%

Pipelines

Platforms

Wells TOTAL 46.313

Sale All - LOF Average

 Spill Frequency per 10^9 bbl produced

35%

22%

43%

Pipelines

Platforms

Wells TOTAL 1.178

Sale All - LOF Average

 Spill Index [bbl]

8%

3%

89%

Pipelines

Platforms

Wells TOTAL 833
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

5.27

Figures 5.21, 5.22, and 5.23 show the CDFs for the Beaufort Sea Sale All 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 5.21 and 5.22) 

decreases as spill size increases. In other words, small and medium spills 

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

facilities. 

ß The variability of the spill index (Figure 5.23) shows the same trend for 

pipelines and platforms, but the opposite trend for wells. 

From Figure 5.21, it can be seen, for significant spills, that the Life of Field average mean 

value of 20 (spills per 1,000 years) ranges between 30 and 12 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 5.22. The spill index variability 

shown in Figure 5.23 is proportionally higher. For example, in Figure 5.23, the mean 

value of the significant spills index of 800 per billion barrels produced ranges from 1,300 

to 400– a somewhat larger proportion of mean than that of the spill frequency indicators.
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

5.28

Figure 5.21

Life of Field Average Spill Frequency – CDF – Sale All

CDF Sale All LOF Average - Pipeline

0

10

20

30

40

50

60

70

80

90

100

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Spill Frequency per 1000 years

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale All LOF Average - Pipeline

0

10

20

30

40

50

60

70

80

90

100

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All 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 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 Sale All 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 32 34 36 38 40

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All 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 11 12 13 14 15 16

Spill Frequency per 1000 years

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale All 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 11 12 13 14 15 16

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All LOF Average - Platforms + Wells

0

10

20

30

40

50

60

70

80

90

100

0 5 10 15 20 25 30 35 40 45 50

Spill Frequency per 1000 years

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale All LOF Average - Platforms + Wells

0

10

20

30

40

50

60

70

80

90

100

0 5 10 15 20 25 30 35 40 45 50

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All 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 60 65 70

Spill Frequency per 1000 years

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale All 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 60 65 70

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

5.29

Figure 5.22

Life of Field Average Spill Frequency per Barrel Produced – CDF – Sale All

CDF Sale All 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

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 Sale All 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

Spill Frequency per 10^9 bbl Produced

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All 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 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 Sale All 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 0.9 1.0

Spill Frequency per 10^9 bbl Produced

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4

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 Sale All LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4 0.5

Spill Frequency per 10^9 bbl Produced

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All 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 0.9 1.0 1.1 1.2 1.3 1.4

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 Sale All 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 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 Sale All 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 %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale All 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
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

5.30

Figure 5.23

Life of Field Average Spill Index (bbl) – CDF – Sale All

CDF Sale All 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 Sale All 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 %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All LOF Average - Platforms

0

10

20

30

40

50

60

70

80

90

100

0 5 10 15 20 25 30 35 40 45 50 55 60

Spill Index [bbl]

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale All LOF Average - Platforms

0

10

20

30

40

50

60

70

80

90

100

0 5 10 15 20 25 30 35 40 45 50 55 60

Spill Index [bbl]

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

0 100 200 300 400 500 600 700 800 900 1000 1100 1200

Spill Index [bbl]

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale All LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

0 100 200 300 400 500 600 700 800 900 1000 1100 1200

Spill Index [bbl]

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All 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 1000 1100 1200

Spill Index [bbl]

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale All 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 1000 1100 1200

Spill Index [bbl]

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All LOF Average - All

0

10

20

30

40

50

60

70

80

90

100

0 100 200 300 400 500 600 700 800 900 100

0

110

0

120

0

130

0

140

0

Spill Index [bbl]

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale All LOF Average - All

0

10

20

30

40

50

60

70

80

90

100

0 100 200 300 400 500 600 700 800 900 100

0

110

0

120

0

130

0

140

0

Spill Index [bbl]

CDF %

Significant Spills

=>1000 bbl

All Spills
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 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 south Beaufort Sea in the area of MMS jurisdiction. The quantification included 

the consideration of the variability of historical data as well as the expected variability of 

Arctic effects on oil spill occurrence indicators. Consideration of the variability of all 

input data yields both higher variability and 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.

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 for Sale 1, 2, and 3. The following can be 

observed from Table 6.1.

ß Each spill indicator for Sale 1, 2, and 3 is similar in value. The indicators are 

higher for the composite “Sale All” scenario.

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

spill size for all scenarios. 

ß The spill index increases dramatically with spill size for all scenarios.

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

counterparts. Non-Arctic spill indicators are approximately 40% greater.
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

6.2

Table 6.1

Summary of Average Spill Indicators for All Scenarios

SALE 1 SALE 2 SALE 3 SALE All SALE All

non Arctic

Spill Indicators

Life of Field 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]

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]

Spill Frequency per 10^3 years

Spill Frequency per 10^9 bbl 

produced

Small and Medium Spills 9.404 0.612 4 9.586 0.674 4 11.320 0.714 5 26.204 0.667 11 38.900 0.990 15

50-999 bbl 56% 56% 1% 57% 57% 1% 57% 57% 1% 57% 57% 1% 58% 58% 1%

Large Spills 4.099 0.267 31 3.989 0.281 30 4.575 0.289 35 10.951 0.279 82 15.653 0.398 117

1000-9999 bbl 24% 24% 10% 24% 24% 10% 23% 23% 10% 24% 24% 10% 23% 23% 10%

Huge Spills 3.369 0.219 270 3.323 0.234 268 3.901 0.246 317 9.158 0.233 740 12.956 0.330 1048

=>10000 bbl 20% 20% 89% 20% 20% 89% 20% 20% 89% 20% 20% 89% 19% 19% 89%

Significant Spills 7.468 0.486 300 7.312 0.514 298 8.476 0.535 352 20.109 0.512 822 28.608 0.728 1165

=>1000 bbl 44% 44% 99% 43% 43% 99% 43% 43% 99% 43% 43% 99% 42% 42% 99%

16.872 1.098 304 16.897 1.188 302 19.796 1.249 357 46.313 1.178 833 67.508 1.718 1180 All Spills 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100% 100%

5.953 0.388 25 5.899 0.415 23 6.551 0.413 26 15.925 0.405 64 27.192 0.692 96 Pipeline Spills

35% 35% 8% 35% 35% 8% 33% 33% 7% 34% 34% 8% 40% 40% 8%

7.122 0.464 9 7.210 0.507 9 8.751 0.552 11 19.947 0.508 24 25.562 0.650 30 Platform Spills 42% 42% 3% 43% 43% 3% 44% 44% 3% 43% 43% 3% 38% 38% 3%

3.797 0.247 271 3.787 0.266 271 4.494 0.283 321 10.441 0.266 746 14.755 0.375 1054 Well Spills 23% 23% 89% 22% 22% 89% 23% 23% 90% 23% 23% 89% 22% 22% 89%

10.918 0.711 280 10.998 0.773 279 13.245 0.835 331 30.388 0.773 770 40.317 1.026 1084 Platform and Well Spills 65% 65% 92% 65% 65% 92% 67% 67% 93% 66% 66% 92% 60% 60% 92%

16.872 1.098 304 16.897 1.188 302 19.796 1.249 357 46.313 1.178 833 67.508 1.718 1180 All Spills

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

6.2
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

6.3

Figure 6.1

Life of Field Spill Indicators – By Spill Size

Life of Field Average

0

10

20

30

40

50

60

70

Spill Frequency

per 1000 years

Huge Spills

=>10000 bbl

3.369 3.323 3.901 9.019 12.956

Large Spills

1000-9999 bbl

4.099 3.989 4.575 10.882 15.653

Small and Medium Spills

50-999 bbl

9.404 9.586 11.320 26.180 38.900

SALE 1 SALE 2 SALE 3 SALE All SALE All

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

0.219 0.234 0.246 0.229 0.330

Large Spills

1000-9999 bbl

0.267 0.281 0.289 0.277 0.398

Small and Medium Spills

50-999 bbl

0.612 0.674 0.714 0.666 0.990

SALE 1 SALE 2 SALE 3 SALE All SALE All

non Arctic

Life of Field Average

0

200

400

600

800

1000

1200

Spill Index [bbl]

Huge Spills

=>10000 bbl

270 268 317 721 1048

Large Spills

1000-9999 bbl

31 30 35 81 117

Small and Medium Spills

50-999 bbl

4 4 5 11 15

SALE 1 SALE 2 SALE 3 SALE All SALE All

non Arctic
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 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 

representative scenario years, again, in Table 6.1 and also in Figure 6.2. Table 6.1 and 

Figure 6.2 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 6.1:

ß Platforms contribute the most (43%) to the two spill frequency indicators, but 

the least (3%) to the spill index. 

ß Pipelines are next in relative contribution to spill frequencies (34%) and 

intermediate in contribution to spill index (8%). 

ß Wells are by far (at 89%) the highest contributors to spill index. 

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

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

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

about the same number as platforms.

Figures 6.3 and 6.4 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. 

6.1.4 Variability of Oil Spill Occurrence Indicators

Figures 6.5, 6.6, and 6.7 show the Cumulative Distribution Functions for each of the 

Beaufort Sea Sale All Life of Field average spill indicators by spill size and source. The 

variability of these indicators is fairly representative of the trends in variability for spill 

indicators for all scenarios modeled. Generally, the following can be observed from the 

figures:

ß The variance of the frequency spill indicators (Figures 6.5 and 6.6) decreases 

as spill size increases. In other words, small and medium spills illustrate the 

largest variability; huge spills show the least variability for facilities. 

ß The variability of the spill index (Figure 6.7) shows the same trend for 

pipelines and platforms, but the opposite trend for wells. 
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

6.5

Figure 6.2

Life of Field Spill Indicators – By Source Composition

Life of Field Average

0

10

20

30

40

50

60

70

Spill Frequency

per 1000 years

Well Spills 3.797 3.787 4.494 10.441 14.755

Platform Spills 7.122 7.210 8.751 19.947 25.562

Pipeline Spills 5.953 5.899 6.551 15.925 27.192

SALE 1 SALE 2 SALE 3 SALE All SALE All

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 0.247 0.266 0.283 0.266 0.375

Platform Spills 0.464 0.507 0.552 0.508 0.650

Pipeline Spills 0.388 0.415 0.413 0.405 0.692

SALE 1 SALE 2 SALE 3 SALE All

SALE All

non Arctic

Life of Field Average

0

200

400

600

800

1000

1200

Spill Index [bbl]

Well Spills 271 271 321 746 1054

Platform Spills 9 9 11 24 30

Pipeline Spills 25 23 26 64 96

SALE 1 SALE 2 SALE 3 SALE All SALE All

non Arctic
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

6.6

BY SPILL SOURCE BY SPILL SIZE

Figure 6.3

Sale All – Year 2024 – Spill Indicator Composition by Source and Spill Size

Sale All- Year 2024

 Spill Frequency per 10^3 years

58%

23%

19%

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

 =>10000 bbl

TOTAL 90.976

Sale All - Year 2024

 Spill Frequency per 10^9 bbl produced

23%

58%

19%

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

 =>10000 bbl

TOTAL 1.149

Sale All - Year 2024

 Spill Index [bbl]

1%

89%

10%

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

 =>10000 bbl

TOTAL 1534

Sale All - Year 2024

 Spill Frequency per 10^3 years

44%

35%

21%

Pipelines

Platforms

Wells TOTAL 90.976

Sale All - Year 2024

 Spill Frequency per 10^9 bbl produced

44%

35%

21%

Pipelines

Platforms

Wells TOTAL 1.149

Sale All - Year 2024

 Spill Index [bbl]

89%

8%

Pipelines 3%

Platforms

Wells TOTAL 1534
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

6.7

BY SPILL SOURCE BY SPILL SIZE

Figure 6.4

Sale All – Life of Field Average Spill Indicator Composition by Source and Spill Size

Sale All - LOF Average

 Spill Frequency per 10^3 years

56%

20%

24%

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

 =>10000 bbl

TOTAL 46.313

Sale All - LOF Average

 Spill Frequency per 10^9 bbl produced

56%

24%

20%

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

 =>10000 bbl

TOTAL 1.178

Sale All - LOF Average

 Spill Index [bbl]

1%

89%

10%

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

 =>10000 bbl

TOTAL 833

Sale All - LOF Average

 Spill Frequency per 10^3 years

35%

43% 22%

Pipelines

Platforms

Wells TOTAL 46.313

Sale All - LOF Average

 Spill Frequency per 10^9 bbl produced

35%

22%

43%

Pipelines

Platforms

Wells TOTAL 1.178

Sale All - LOF Average

 Spill Index [bbl]

8%

3%

89%

Pipelines

Platforms

Wells TOTAL 833
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

6.8

Figure 6.5

Life of Field Average Spill Frequency – Cumulative Distribution Functions – Sale All

CDF Sale All LOF Average - Pipeline

0

10

20

30

40

50

60

70

80

90

100

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Spill Frequency per 1000 years

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale All LOF Average - Pipeline

0

10

20

30

40

50

60

70

80

90

100

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All 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 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 Sale All 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 32 34 36 38 40

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All 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 11 12 13 14 15 16

Spill Frequency per 1000 years

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale All 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 11 12 13 14 15 16

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All LOF Average - Platforms + Wells

0

10

20

30

40

50

60

70

80

90

100

0 5 10 15 20 25 30 35 40 45 50

Spill Frequency per 1000 years

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale All LOF Average - Platforms + Wells

0

10

20

30

40

50

60

70

80

90

100

0 5 10 15 20 25 30 35 40 45 50

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All 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 60 65 70

Spill Frequency per 1000 years

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale All 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 60 65 70

Spill Frequency per 1000 years

CDF %

Significant Spills

=>1000 bbl

All Spills
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

6.9

Figure 6.6

Life of Field Average Spill Frequency per Barre l Produced – Cumulative 

Distribution Functions – Sale All

CDF Sale All 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

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 Sale All 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

Spill Frequency per 10^9 bbl Produced

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All 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 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 Sale All 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 0.9 1.0

Spill Frequency per 10^9 bbl Produced

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4

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 Sale All LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

0.0 0.1 0.2 0.3 0.4 0.5

Spill Frequency per 10^9 bbl Produced

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All 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 0.9 1.0 1.1 1.2 1.3 1.4

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 Sale All 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 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 Sale All 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 %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale All 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
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

6.10

Figure 6.7

Life of Field Average Spill Index (bbl) – Cumulative Distribution Functions – Sale All

CDF Sale All 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 Sale All 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 %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All LOF Average - Platforms

0

10

20

30

40

50

60

70

80

90

100

0 5 10 15 20 25 30 35 40 45 50 55 60

Spill Index [bbl]

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale All LOF Average - Platforms

0

10

20

30

40

50

60

70

80

90

100

0 5 10 15 20 25 30 35 40 45 50 55 60

Spill Index [bbl]

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

0 100 200 300 400 500 600 700 800 900 1000 1100 1200

Spill Index [bbl]

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale All LOF Average - Wells

0

10

20

30

40

50

60

70

80

90

100

0 100 200 300 400 500 600 700 800 900 1000 1100 1200

Spill Index [bbl]

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All 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 1000 1100 1200

Spill Index [bbl]

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale All 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 1000 1100 1200

Spill Index [bbl]

CDF %

Significant Spills

=>1000 bbl

All Spills

CDF Sale All LOF Average - All

0

10

20

30

40

50

60

70

80

90

100

0 100 200 300 400 500 600 700 800 900 100

0

110

0

120

0

130

0

140

0

Spill Index [bbl]

CDF %

Small and Medium Spills

50-999 bbl

Large Spills

1000-9999 bbl

Huge Spills

=>10000 bbl

CDF Sale All LOF Average - All

0

10

20

30

40

50

60

70

80

90

100

0 100 200 300 400 500 600 700 800 900 100

0

110

0

120

0

130

0

140

0

Spill Index [bbl]

CDF %

Significant Spills

=>1000 bbl

All Spills
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

6.11

The Cumulative Distribution Functions contain extensive information on the statistical 

properties of the spill indicators. For example, from Figure 6.5, it can be seen, for 

significant spills, that the Life of Field average mean (50%) value of 20 (spills per 1,000 

years) ranges between 30 and 12 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 6.6. The spill index variability shown in Figure 6.7 is

proportionally higher. For example, in Figure 6.7, the mean value of the significant spills 

index of 800 per billion barrels produced ranges from 1,300 to 400 – a somewhat larger 

proportion of mean than that of the spill frequency indicators.

6.2. Conclusions on the Methodology and its Applicability

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

history 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 basic 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 spill causes, 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.
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

6.12

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 and thaw settlement 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. There are two possible

shortcomings of the scenarios as follows:

ß Distributed values for the key quantities were not provided, thus precluding 

their incorporation as distributions in the Monte Carlo analysis.

ß The facility abandonment rate appears to be significantly lower than the rate 

of decline in production.

Generally, the fault tree methodology was limited primarily by the shortcomings in input 

data discussed above. 
Beaufort Oil Spill Estimators Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

6.13

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. 

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. These effects are incorporated to the extent that they are 

represented in spill databases used.

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. 

ß Develop an adjusted expected value oil spill occurrence indicator model as a 

user friendly software package, which can be used for the assessment of oil 

spill occurrence indicators and their characteristics for any designated

scenario. The software package should include the following:

ß Modular structure

ß User manual

ß Online help

ß Password protected parameters and algorithms

ß Extensive tabular and graphical outputs
Beaufort Oil Spill Estimators R.1 Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

REFERENCES

1. AIChE, "Guidelines for Chemical Process Quantitative Risk Analysis", 2

nd Edition, Center 

for Chemical Process Safety, NY, 2000.

2. Anderson, Cheryl McMahon, and Robert P. LaBelle, "Update of Comparative Occurrence 

Rates for Offshore Oil Spills", Spill Science & Technology Bulletin, Vol. 6., No. 5/6, pp. 

303-321, 2000.

3. Beaumont, S., “Refinery Construction in Arctic Weather Conditions – Some Construction, 

Inspection, and Corrosion Concerns”, in Material Performance, Vol. 26:8, pp 53-56, 01 

August 1987. 

4. Bercha F.G., "Special Problems in Pipeline Risk Assessment", Proceedings of IPC 2000, 

International Pipeline Conference, Calgary, AB, October 1-5, 2000.

5. Bercha, F.G., A.C. Churcher, and M. Cerovšek, “Escape, Evacuation, and Rescue Modeling 

for Frontier Offshore Installations”, Offshore Technology Conference, Houston, Texas, 

USA, 2000.

6. Bercha, F.G., and M. Cerovšek, Large Arctic Offshore Project Risk Analysis” Proceeding 

of Russian Arctic Offshore Conference, St. Petersburg, Russia, 1997.

7. Bercha, F.G., "Fault Trees for Everyday Risk Analysis", Proceedings of Canadian Society 

for Chemical Engineering, Risk Analysis Seminar, Edmonton, 1990.

8. Bercha, F.G., and Associates (Alberta) Limited, "Ice Scour Methodology Study", Final 

Report to Gulf Canada Resources, Calgary, AB, March 1986.

9. Bercha, F.G., “Application of Risk Analysis to Offshore Drilling and Risk Mitigation,” 

Proceedings, Risk Analysis Seminar, Royal Commission of the Ocean Ranger Marine 

Disaster, Toronto, 1984.

10. Bercha, F.G., "Probabilities of Blowouts in the Canadian Arctic", North Sea Offshore 

Conference, Stavanger, Norway, 1978.

11. Bercha, F.G., and Associates Limited, “Probabilties of Blowouts in Canadian Arctic

Waters”, Final Report, Fisheries and Environment Canada, Report #EPS 3-EC-78-12, 

October 1978.

12. Bercha International Inc., “Alternative Oil Spill Occurrence Estimators for the Beaufort and 

Chukchi Seas – Fault Tree Method”, Volumes I and II, OCS Study MMS 2002-047, Final 

Report to US Department of the Interior, Minerals Management Service, Alaska Outer 

Continental Shelf Region, August 2002..

13. Brighton Webs Ltd., “BW D-Calc 1.0 Distribution Calculator”, www.brightonwebs.co.uk/distributions/, 22 July 2005.

14. Doelp, L.C., G.K. Lee, R.E Linney, and R.W. Ormsby, “Quantitative Fault Tree Analysis: 

Gate-by-Gate Method”, in Plant/Operations Progress, 4(3) 227-238, 1984.

15. Energy Resources Conservation Board of Alberta, “GASRISK – A Model to Estimate Risk 

to Public Safety for Uncontrolled Sour Gas Releases”, Volume 6, April 1990.
Beaufort Oil Spill Estimators R.2 Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

16. E&P Forum, Quantitative Risk Assessment (QRA) Data Sheet Directory, The Oil Industry 

International Exploration and Production Forum, 25-28 Old Burlington Street, London, 

1996.

17. Fairweather E&P Services, Inc., "Historical Blowout Study, North Slope, Alaska", Study 

for BP-Amoco Exploration (Alaska), Anchorage, AK, June 2000.

18. Fussell, J.B., “How to Hand Calculate System Reliability and Safety Characteristics”, in 

IEEE Transactions on Reliability, R-24(3), 169-174, 1975.

19. Gadd, P.E., G. Hearon, C.B. Leidersdorf, W.G. McDougal, J. Ellsworth, and D. Thomas, 

"Slope Armor Design and Construction Northstar Production Island", in Proceedings,

Volume 1, 16th International Conference on Port and Ocean Engineering under Arctic 

Conditions (POAC), Ottawa, ON, August 12-17, 2001.

20. Goff, R., J. Hammond, and A.C. Nogueira, "Northstar Sub Sea Pipeline Design of

Metallurgy, Weldability, and Supporting Full Scale Bending Tests", in Proceedings,

Volume 1, 16th International Conference on Port and Ocean Engineering under Arctic 

Conditions (POAC), Ottawa, ON, August 12-17, 2001.

21. Gulf Canada, "Analysis of Accidents in Offshore Operations Where Hydrocarbons Were 

Lost", Report by the Houston Technical Services Center of Gulf Research and 

Development Company for Gulf Canada Resources, Inc., Calgary, AB, 1981.

22. Hart Crowser Inc., "Estimation of Oil Spill Risk From Alaska North Slope, Trans-Alaskan 

Pipeline, and Arctic Canada Oil Spill Data Sets", OCS Study MMS 2000-007, Study for US 

Department of the Interior, Minerals Management Service, Alaska Outer Continental Shelf 

Region, Anchorage, AK, April 2000.

23. Henley, E.J., and H. Kumamoto, “Reliability Engineering and Risk Assessment”, PrinticeHall, Englewood Cliffs, NJ, (ISBN 0-13-772251-6), 1981.

24. Hnatiuk, J., and K.D. Brown, "Sea Bottom Scouring in the Canadian Beaufort Sea", 9th 

Annual OTC, Houston, TX, May 2-5, 1983.

25. Holand, Per, Offshore Blowouts, Causes and Control, Gulf Publishing, Houston, Texas, 

USA, 1997.

26. Hoyland, A., and M. Rausand, “System Reliability Theory: Models and Statistical

Methods”, John Wiley and Sons, New York, NY, 1994.

27. Hunt, D.M., K.R. McClusky, R. Shirley, and R. Spitzenberger, "Facility Engineering for 

Arctic Conditions", in Proceedings, Volume 1, 16th International Conference on Port and 

Ocean Engineering under Arctic Conditions (POAC), Ottawa, ON, August 12-17, 2001.

28. Kato, S., and N.J. Adams, "Quantitative Assessment of Blowout Data as It Relates to 

Pollution Potential", SPE 23289, First International Conference on Health, Safety and 

Environment, the Netherlands, November 10-14, 1991.

29. Lanan, G.A., and J.O. Ennis, "Northstar Offshore Arctic Pipeline Project", in Proceedings, 

Volume 1, 16th International Conference on Port and Ocean Engineering under Arctic 

Conditions (POAC), Ottawa, ON, August 12-17, 2001.
Beaufort Oil Spill Estimators R.3 Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

30. Leidersdorf, C.B., G.E. Hearon, R.C. Hollar, P.E. Gadd, and T.C. Sullivan, "Ice Gouge and 

Strudel Scour Data for the Northstar Pipelines", in Proceedings, Volume 1, 16th

International Conference on Port and Ocean Engineering under Arctic Conditions (POAC), 

Ottawa, ON, August 12-17, 2001.

31. Lowrance, W.W., "Of Acceptable Risk", Kaufmann Inc., 1976.

32. Masterson, D.M., A.B. Christopherson, and J.W. Pickering, "Sheet Pile Design for

Offshore Gravel Islands", in Proceedings, Volume 1, 16th International Conference on Port 

and Ocean Engineering under Arctic Conditions (POAC), Ottawa, ON, August 12-17, 

2001.

33. Miller, D.L., "Hypersaline Permafrost under a Lagoon of the Arctic Ocean", in

Proceedings, Volume 1, 16th International Conference on Port and Ocean Engineering 

under Arctic Conditions (POAC), Ottawa, ON, August 12-17, 2001.

34. MMS (Minerals Management Service), "Accidents Associated with Oil and Gas

Operations: Outer Continental Shelf 1956-1990", OCS Report MMS 92-0058, 1992.

35. MMS (Minerals Management Service), "Federal Offshore Statistics: 1995. Leasing,

exploration, production and revenues to December 31, 1995", US Department of the 

Interior, Mineral Management Service, Operations and Safety Management, OCS Report 

MMS 97-0007, 1997.

36. MMS (US Department of the Interior, Minerals Management Service, Alaska OCS

Region), "Alaska Outer Continental Shelf - Beaufort Sea Planning Area Oil and Gas Lease 

Sale 144 - Final Environmental Impact Statement", Vol. II, OCS EIS/EA MMS 96-0012, 

May 1996.

37. MMS (US Department of the Interior, Minerals Management Service, Alaska OCS

Region), "Alaska Outer Continental Shelf - Beaufort Sea Planning Area Oil and Gas Lease 

Sale 170 - Final Environmental Impact Statement", OCS EIS/EA MMS 98-0007, February 

1998.

38. MMS (US Department of the Interior, Minerals Management Service, Alaska OCS

Region), "Alaska Outer Continental Shelf - Chukchi Sea Oil & Gas Lease Sale 126 - Final 

Environmental Impact Statement", Vol. II, OCS EIS/EA MMS 90-0095, Anchorage, AK, 

January 1991.

39. MMS (US Department of the Interior, Minerals Management Service, Alaska OCS

Region), "Undiscovered Oil and Gas Resources, Alaska Federal Offshore", OCS

Monograph MMS 98-0054, Anchorage, AK, 1998.

40. MMS (US Department of the Interior, Minerals Management Service, Gulf of Mexico OCS 

Region), "Investigation of Shell Offshore Inc., Hobbit Pipeline Leak Ship Shoal Block 281, 

January 24, 1990, Gulf of Mexico, Offshore Louisiana", OCS Report MMS 91-0025, New 

Orleans, March 1991.

41. MMS (US Department of the Interior, Minerals Management Service, Gulf of Mexico OCS 

Region), "Investigation of the Exxon Company USA Pipeline Leak /Eugene Island Block 

314, May 6, 1990, Gulf of Mexico, Offshore Louisiana", OCS Report MMS 91-0066, New 

Orleans, November 1991.
Beaufort Oil Spill Estimators R.4 Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

42. MMS (US Department of the Interior, Minerals Management Service, Gulf of Mexico OCS 

Regional Office), "Investigation of Chevron Pipe Line Company Pipeline Leak, South Pass 

Block 38, September 29, 1998, Gulf of Mexico Off the Louisiana Coast", OCS Report 

MMS 99-0053, New Orleans, September 1999.

43. MMS (US Department of the Interior, Minerals Management Service, Gulf of Mexico OCS 

Regional Office), "Investigation of Shell Offshore Inc., Hobbit Pipeline Leak, Ship Shoal 

Block 281, November 16, 1994, Gulf of Mexico, Off the Louisiana Coast", OCS Report 

MMS 97-0031, New Orleans, August 1997.

44. MMS (US Department of the Interior, Minerals Management Service, Gulf of Mexico OCS 

Regional Office), "Investigation of Shell Pipe Line Corporation Pipeline Leak South Pass 

Block 65 December 30, 1986, Gulf of Mexico off the Louisiana Coast", OCS Report MMS 

87-0114, December 1987.

45. Modarres, M., M. Kaminsky, and V. Krisvtsov, "Reliability Engineering and Risk

Analysis", Marcel Deker Inc., 1999.

46. O'Connor, M.J, and Associates Ltd., Preliminary Ice Keel/Seabed Interaction Study", Final 

Report to GCRI, March 1984.

47. Offshore Technology Research Center, "Comparative Risk Analysis for Deepwater

Production Systems", Final Project Report for Minerals Management Service, January

2001.

48. OPL, “Field Development Concepts of the World”, 1990.

49. Owen, L., D. Blanchet, and P. Flones, "The Northstar Project - Year-Round Production in 

the Alaskan Beaufort Sea", in Proceedings, Volume 1, 16th International Conference on 

Port and Ocean Engineering under Arctic Conditions (POAC), Ottawa, ON, August 12-17, 

2001.

50. Paulin, M.J., D. Nixon, G.A. Lanan, and B. McShane, "Environmental Loadings &

Geotechnical Considerations for the Northstar Offshore Pipelines", in Proceedings, Volume 

1, 16th International Conference on Port and Ocean Engineering under Arctic Conditions 

(POAC), Ottawa, ON, August 12-17, 2001.

51. Roberts, N.H., W.E. Veseley, D.F. Haasl, and F.F. Goldberg, “Fault Tree Handbook”, 

NUREG-0492, US Nuclear Regulatory Commission, Washington, DC, 1985.

52. S.L. Ross Environmental Research Ltd., "Blowout and Spill Probability Assessment for the 

Northstar and Liberty Oil Development Projects in the Alaska North Slope", Report to BP 

Exploration (Alaska), Inc., November 1998.

53. Ross, S.L., c.W. Ross, F. Lepine, and K.E. Langtry, “Ixtoc I Oil Blowout”, Environment 

Canada E.P.S. Spill Technology Newsletter, pp. 245-256, July-August 1979.

54. S.L. Ross Environmental Research Ltd., "Blowout and Spill Probability Assessment for the 

Sable Offshore Energy Project", Report to Mobil Oil Canada Properties, November 1995.

55. S.L. Ross Environmental Research Ltd., "Contingency Plans to Monitor and Clean Up 

Large Spills from SOEP Offshore Facilities", Prepared for Sable Offshore Energy Project, 

Halifax, NS, March 31, 1998.
Beaufort Oil Spill Estimators R.5 Final Report – P2407

MMS Contract No.: 1435-01-04-PO-336507

January, 2006

56. S.L. Ross Environmental Research Ltd., "Large Oil Spills and Blowouts from Exploration 

Drilling on Georges Bank: An Analysis of their Probability, Behaviour, Control and

Environmental Effects", Chevron Canada Resources and Texaco Canada Petroleum Inc., 

submitted to the Georges Bank Review Panel, January 1999.

57. S.L. Ross Environmental Research Ltd., "Oil Spills Associated with the Terra Nova

Development Project off Newfoundland: Risk Assessment; Spill Fate, Behaviour and

Impact; Countermeasures; and Contingency Planning", Report to Petro-Canada Inc.,

December 1996. 

58. S.L. Ross Environmental Research Ltd., "Panuke/Cohasset Field Development Project:

Risk, Behaviour and Effects of Oil Spills", Report to IONA Resources Ltd. and Nova 

Scotia Resources Ltd., July 1989.

59. ScanPower A.S., "Blowout Frequency Assessment of Northstar", Report to BP Exploration 

(Alaska), Report No. 27.83.01/R1, Kjeller, Norway, July 2, 2001.

60. Sefton, A.D., “The Development of the U.K. Safety Case Regime: A Shift in Responsibility 

from Government to Industry”, Offshore Technology Conference, Houston, USA, 1994.

61. Shared Services Drilling, "A Review of Alaska North Slope Blowouts, 1974-1997", June 

30, 1998.

62. Sharples, B.P.M., J.J. Stiff, D.W. Kalinowski and W.G. Tidmarsh, "Statistical Risk

Methodology: Application for Pollution Risks from Canadian Georges Bank Drilling

Program", 21st Annual Offshore Technology Conference, Houston, TX, May 1-4, 1989.

63. Southwest Research Institute, "New Methods for Rapid Leak Detection in Offshore

Pipelines", Final Report to Minerals management Service, US Department of the Interior, 

SwRI Project No. 04-4558, April 1992.

64. System Safety and Reliability Committee, Santa Barbara County, Energy Division, “Risk 

Matrix Guidelines”, 1998.

65. U.S. Nuclear Regulatory Commission, "Reactor Safety Study", WASH-1400, NUREG75/014, Appendix I – IV, October 1975.

66. Upstream Technology Group, "Analysis of Strudel Scours and Ice Gouges for the Liberty 

Development Pipeline", Final Draft, no date.

67. Weeks, W.F., P.W. Barnes, D.M. Rearic, and E. Reimnitz, "Some Probabilistic Aspects of 

Ice Gouging on the Alaskan Shelf of the Beaufort Sea", US Army Cold Regions Research 

and Engineering Laboratory, June 7, 1983.

68. Weeks, W.F., P.W. Barnes, D.M. Rearic, and E. Reimnitz, "Statistical Aspects of Ice 

Gouging on the Alaskan Shelf of the Beaufort Sea", US Army Cold Regions Research and 

Engineering Laboratory, 1982.

69. Wylie, W.W., and A.B. Visram, "Drilling Kick Statistics", Proceedings, IADC/SPE

Drilling Conference, Houston, TX, February 27-March 2, 1980.
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.