Risk-Based Pipeline Route Optimization for the Persian Gulf Region

Scott ByronExxonMobil Exploration Co. &

Master’s Candidate, Penn State University MGIS Program

2010 ESRI Petroleum Users Group ConferenceFebruary 23, 2010

Presentation Overview

• Project overview

• Analysis methodology

• Results & Conclusion

Courtesy: NASA

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Project Overview

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Project Objectives

• Proof of concept

• Create risk maps by Identifying & weighting analysis risk factors

• Test system against existing pipelines

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Qatar – Abu Dhabi – Oman PipelineCourtesy: Oil & Gas Journal

• New pipelines will encounter high-risk environments

• People can easily perceive risks

• Risk management improves project performance

• Must apply internal safety & risk management policies

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Why Focus on Risk?

0m

~90m (Approx. depth of Persian Gulf)

2,863m-1,788m

Key Map

The Persian Gulf region topography & bathymetry

• Availability of experts

• No marine examples

• Reliance on public data

• Expectation that low risk path will equate to shortest, lowest cost path

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Constraints

0m

~90m (Approx. depth of Persian Gulf)

2,863m-1,788m

Key Map

The Persian Gulf region topography & bathymetry

Analysis Methodology

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• 36 risk factors identified

• 19 – terrestrial, 11 – marine, 6 - both

• Divided into 4 categories

Risk Factor Identification

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Construction10 risks

Operation13 risks

Socio-Economic7 risks

Environmental6 risks

Risk Categories

Formal Risk Analysis

• Probability of Occurrence & Potential Impact scores combined for Risk Score

• High priority risks have Risk Score >= 3.0

• High priority risks used in weighting methods

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Risk Scores

Risk Count

= High Priority Risks

1 2 3 1 2 3

1 1.5 2.5 3.5 1 4 8 6

2 2.0 3.0 4.0 2 2 2 6

3 2.5 3.5 4.5 3 2 3 3

Potential Impact

Pro

bab

ility

of

Occ

urr

ence

1 2 3 1 2 3

1 1.5 2.5 3.5 1 4 8 6

2 2.0 3.0 4.0 2 2 2 6

3 2.5 3.5 4.5 3 2 3 3

Potential Impact

Pro

bab

ility

of

Occ

urr

ence

Weighting MethodologySimple Weighted Index

• Factors evaluated independently

• Evaluated 21 risks

Incr

ea

sin

gri

sk

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Index Factor

4.5 A

4.0 B

3.5 C

3.0 D

• Evaluating Brown & Peterson method, Analytical Hierarchy Process

• Factors compared to each other

• Data collected via survey

• Fewer risks evaluated

Factor C

Factor B

Factor C

Factor A

Factor A

Factor B

<

<

>

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Weighting MethodologyPair-Based Comparison Overview

Factor A

Factor B> Factor

C>

• Captures selection frequency

• Is row factor riskier than column factor?

• No factor categories

• Simple calculation of weights

A B C D

A 8 5 2

B 2 5 6

C 5 5 4

D 8 4 6

15 17 16 12

30 30 30 30

0.500 0.567 0.533 0.400Weight

Factors

Fa

cto

rs

Column Sums

Max. selection #

Factor ‘s column sumMaximum selection #

= Weight

Frequency matrix for 10 respondents

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Weighting MethodologyBrown & Peterson Method

• Captures Degree of importance (How much riskier?) on scale of 1 – 7 (similar – significantly riskier)

• Weights categories

• Uses matrix similar to BP method

• Weights categories

• Complex weight calculation

Analysis Problem

Category 1 Category 2

Factor A

Factor B

Factor C

Factor D

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Weighting MethodologyAnalytical Hierarchy Process

Weighting

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Weighting MethodologyAnalytical Hierarchy Process

A B C D

A 3 5 1

B 0.333 0.25 0.143

C 0.2 4 0.2

D 1 7 4

Factors

Fa

cto

rs

1. Sum each column2. Divide all cell values by column sum3. Sun each row4. Divide all row sums by smallest row

sum 5. Divide by combined row sums6. Multiply by Category weights, repeat

steps 4 & 5

FactorC

Weight = 6.1

FactorA

Weight = 4.28

Analysis Problem

Category 1Weight = 1.00

Category 2Weight = 1.5

FactorD

Weight = 4.52

FactorB

Weight = 1.00

Steps

Results

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Top High Priority Risks

Seismic

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Commercial Shipping

Landslide

Steep Slope (>5%)

Crossings Reefs & Spill Windows

Low High Low High Low High

High risk areas River, road, rail or pipe Spill response window (2 day)

Coral reefs

• Further loss of ocean – land distinction

• Exaggerated risk variation

Final Risk Surfaces

Simple Weighted Index Brown & Peterson Analytical Hierarchy Process

0 0.424 0 0.466 0 0.514

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• Land riskier than ocean due to higher number of land risks

• Zagros has highest risk

• Less ocean – land distinction

• Zagros is riskiest

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ValidationIGAT 4 Pipeline

• Land oil pipeline

• Crosses mountains, active earthquake area

• ~$1 billion

Key Map

The IGAT 4 pipeline, Iran

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ValidationIGAT 4 Pipeline

• SWI shortest, has greater slope variability

• BP, AHP have best match

• Key risks: seismic, slope, landslide, crossings

Alignments on BP Risk Map

Key Map

CriteriaIGAT 4

PipelineStraight-

lineSWI

AlignmentBP

AlignmentAHP

Alignment

Length (km) 635 547 620 696 694

Length of pipeline (km) within seismic risk environment (peak horizontal acceleration)

1.6 - 2.4 cm/s 2 164 1 92 245 238

2.4 - 3.2 cm/s 2 264 211 370 301 2893.2 - 4.0 cm/s 2 206 215 158 150 158

> 4.0 cm/s 2 0 120 0 0 0Length of pipeline by slope categories (km)

< 5% (preferred) 400 265 469 573 566

5 - 15% 182 214 123 108 113

15 - 30% 53 68 28 15 1530% + 4 6 0 0 0

Number of crossingsPipelines 3 8 5 4 4

Rivers 3 7 2 2 8

Roads 34 18 35 38 37

Number of urban areas crossed 3 1 1 1 1

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ValidationIGAT 4 Pipeline

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ValidationDolphin Pipeline

• Marine gas pipeline

• Crosses highly developed area

• $3.5 billion

Key Map

The Dolphin Pipeline, Qatar - UAE

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ValidationDolphin Pipeline

• SWI has best match

• BP, AHP similar, but route southward

• Key risks: commercial shipping, pipeline crossings, coral reefs & spill windows

Alignments on SWI Risk Map

Key Map

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ValidationDolphin Pipeline

CriteriaDolphin Pipeline

Straight-line

SWI Alignment

BP Alignment

AHP Alignment

Length (km) 364 346 361 470 469

Length of pipeline (km) within low seismic risk environment (peak horizontal ground

acceleration of 1.6 - 2.4 cm/s2)

197 191 190 111 111

Length of pipeline within spill window (km) 15 11 10 15 15

Length of pipeline within commercial shipping threat zone (km)

Moderate 203 135 89 46 46Low 160 208 270 314 313

Number of pipeline crossings 15 19 18 11 11Number of coral reefs crossed 2 2 2 1 1Number of urban areas crossed 1 1 0 1 1

Conclusion

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Learnings

• Risk approach is valid

• Lowest risk path: pair-based• Shortest path: SWI

• Data quality impacts results

• Finer resolution needed

• Reevaluate some factors for coverage and weight

Questions?

Dubai, UAE

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Appendix

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List of Risk FactorsHigh Priority Risk Factors Analyzed by all Weighting Methods

Category RiskProbability of Occurrence

Potential Impact

Risk Score/SWI Weight

BP Weight

AHP Weight

Socio-Economic Contamination of water supply 1 3 3.5 0.565 3.364

Operational Corrosion from sea spray 3 2 3.5 0.130 1.260

Construction Cost of building over high slopes 3 3 4.5 0.556 4.137

Construction Cost of excessive river, rail, pipeline or road crossings 2 3 4.0 0.417 2.668

Construction Cost of urban construction 3 3 4.5 0.685 5.628

Operational Damage from commercial ship traffic (anchors and collisions) 2 3 4.0 0.870 6.000

Operational Damage from seismic activity 3 3 4.5 0.269 10.833

Operational Damage from shifting sand dunes 1 3 3.5 0.185 1.860

Operational Damage from unstable Sabkha surface 1 3 3.5 0.444 1.433

Environmental Damage to coral reefs 3 2 3.5 0.574 2.416

Operational Damage to footings from wave activity 2 3 4.0 0.157 4.930

Environmental Damage to forest environment 2 3 4.0 0.750 1.000

Socio-Economic Impact to agriculture (limited use on Right of Way) 2 3 4.0 0.389 2.022

Socio-Economic Pollution of populated areas 1 3 3.5 0.611 3.974

Construction Route too close to existing oil infrastructure 3 2 3.5 0.389 2.665

Construction Shallow or surface bedrock requires blasting 1 3 3.5 0.407 2.522

Environmental Spill pollutes environmentally sensitive area - assumes pipeline failure 2 3 4.0 0.407 2.507Operational Threat from landslides (high slope) 1 3 3.5 0.676 6.747

Additional High Priority Risk Factors Analyzed by SWI Weighting MethodEnvironmental Damage to wetlands 2 2 3.0 -- --

Environmental Damage to shrub/grassland environment 2 2 3.0 -- --

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List of Risk Factors (Con’t)

Additional Unweighted Risks

Category RiskProbability of Occurrence

Potential Impact Risk Score

Operational Damage due to objects dropped from platforms/supply ships 2 1 2.0Socio-Economic Damage to historical or archaeological sites 1 2 2.5Environmental Degradation of landscape 1 1 1.5Construction Excessive span lengths 1 2 2.5Operational Hydrodynamic instability from seafloor currents 1 2 2.5Operational Internal pressure variability from extreme external temperatures 3 1 2.5Construction Limited availability of power 1 1 1.5Socio-Economic Minimize degradation of recreation/tourist areas 2 1 2.0Socio-Economic Minimize interference with fisheries 3 1 2.5Socio-Economic Repositioning of utilities due to utility congestion 1 1 1.5Construction Route crosses lake 1 2 2.5Construction Route too close to military installations 1 1 1.5Construction ROW width - insufficient width for construction equipment 1 2 2.5Operational ROW width - Insufficient maintenance corridor 1 2 2.5Operational ROW width - limited access to pipeline 1 2 2.5Operational ROW width - Unable to expand pipeline 1 2 2.5

Applying AHP in Weighting GIS Model Criteria. Retrieved from http://www.innovativegis.com/basis/Supplements/BM_Sep_03/T39_3_AHPsupplement.htm

Brown T.C., & Peterson G.L. (2009). An enquiry into the method of paired comparison: Reliability; scaling; and thurstone's law of comparative judgment. USDA Forest Service - General Technical Report RMRS-GTR. (216 RMRS-GTR), 1-98. http://www.fs.fed.us/rm/pubs/rmrs_gtr216.pdf

Longley, P. A., Goodchild, M. F., MaGuire, D. J. & Rhind, D. W. (2005). Geographic Information Systems and Science, 2nd Ed.. London: John Wiley& Sons, Ltd..

Resources

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Montemurro D., Barnett S., & Gale T. (1998). GIS-based process helps TransCanada select best route for expansion line. Oil and Gas Journal. 96(25), 63-71.

Saaty T.L., Vargas L.G., and Dellmann K. 2003. The allocation of intangible resources: The analytic hierarchy process and linear programming. Socio-Economic Planning Sciences. 37 (3):169-184.

Pipelines

Braestrup, Mikael W. Design and Installation of Marine Pipelines.. Blackwell Publishing. Online version available at:http://knovel.com.ezaccess.libraries.psu.edu/web/portal/browse/display?_EXT_KNOVEL_DISPLAY_bookid=1384&VerticalID=0

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Resources (Con’t)

Guo, Boyun; Song, Shanhong; Chacko, Jacob; Ghalambor, Ali Offshore Pipelines. Elsevier. Online version available at:http://knovel.com.ezaccess.libraries.psu.edu/web/portal/browse/display?_EXT_KNOVEL_DISPLAY_bookid=1258&VerticalID=0

Data

Global Seismic Hazard Program. (2009 August 27). Middle East Hazard Map. Retrieved from: http://www.seismo.ethz.ch/GSHAP/

National Center for Ecological Analysis and Synthesis. (2009, August 2). Commercial Activity (Shipping) Dataset. Retrieved from: http://www.nceas.ucsb.edu/GlobalMarine/impacts

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Resources (Con’t)

NationMaster.com. (2009, September 22). Oil Consumption (per Capita) (Most Recent) by Country. Retrieved from: http://www.nationmaster.com/graph/ene_oil_con_percap-energy-oil-consumption-per-capita

Tupper, M., Tewfik, A., Tan, M.K., Tan, S.L., The, L.H., Radius, N.J., & Abdullah, S. (2009, September 2) ReefBase: A Global Information System on Coral Reefs [Online]. Retrieved from: http://www.reefbase.org

United Nations Environmental Program. (2009, August 18). Global Environment Outlook (GEO) Data Portal. Retrieved from: http://geodata.grid.unep.ch/

United States Geological Survey. (2009, September 2). Earthquake Hazards Program: Epicenters Database. Retrieved from: http://neic.usgs.gov/neis/epic/epic_rect.html

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Resources (Con’t)

World Database on Protected Areas. (2009, August 5). Annual Release 2009 Dataset. Retrieved from: http://www.wdpa.org/Default.aspx

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Resources (Con’t)