Risk-Based Pipeline Route Optimization
for the Persian Gulf Region
Scott Byron
ExxonMobil Corporation
GEOG 596A Peer Review
October 1, 2009
Ras Laffan Industrial City,
Qatar
Sand dunes in the UAE
Court.: ExposedPlanet.com
Installation of offshore pipeline – Iran
Courtesy Iranian Offshore Engineering and Consulting Co.
Presentation Overview
• Overview & Background
• Workflow diagrams
• Analysis factor
identification
methodology
• Data collection &
preparation
• Proposed Analysis
Courtesy: NASA
Project Overview
Project Objectives
• Identify three alternative
pipeline alignments using
common weighting
techniques
• Identify & weigh analysis
factors using risk
management approach
Qatar – Abu Dhabi – Oman Pipeline
Courtesy: Oil & Gas Journal
Business Drivers
• Increasing demand on Persian Gulf’s hydrocarbon
reserves
• Pipelines are most economic means of transport
• Growing awareness of the benefits of using GIS
during project planning
Project Constraints
• Must comply with company data restrictions
• Must incorporate ExxonMobil’s policies on safety
and risk management
Insights from Literature Review
• Many examples of terrestrial route optimization
• Documented cost and time savings
• Variable number of analysis factors
• Factors often determined through group
consensus
• Variety of weighting techniques
• Risks consideration implied, only one example is
risked based
Regional Overview
Regional Overview
• Population growth, oil
wealth increasing
regional hydrocarbon
consumption
• Pipelines needed to
bring new reserves to
market
• Nearly 80 year
development history
2000 Oil Consumption
(barrels/1,000 people)
0.14 – 0.33
33.01 - 65.87
65.88 - 98.73
98.74 - 131.60
Oil Fields
Pipelines
Key Map
Regional Overview
• Extreme desert
environments
• Variable land uses
• Variable surface
conditions & slope
stability
• Limited agricultural
area supports regional
population
2000 Regional Land Use
Forest
Shrub/Grasses
Crops
Desert
Semi Desert
Rock Outcrop
Urban
Rivers
Key Map
Regional Overview
• Shallow water depths,
high temperatures &
salinity
• Variable seabed
conditions
• Major commercial
route, constrained by
Strait of Hormuz
• Growing awareness of
environmental issues
Persian Gulf Region
Topography & Bathymetry
-1,788m
-90m
Max depth
of Persian Gulf
0m
Key Map
2,863m
Hillshade courtesy Carla Wilson
Methodology
Study Area Selection
• Centered on Persian
Gulf markets
• Disk space use is a
consideration
• Encompasses a variety
of geographic zones
Persian Gulf Region
Topography & Bathymetry
-1,788m
-90m
Max depth
of Persian Gulf
0m
Key Map
2,863m
Hillshade courtesy Carla Wilson
Projection System Considerations
• Analysis requires
consistent projection
• Distance measurements
are a priority
• Latitude suggests use of
conic projection system
• Chose equidistant
projection, optimized for
study area to minimize
distortion
Optimized equidistant conic
projection
Workflow: Factor Identification
Identify Potential Risk
Factors
Select High Priority
Risk Factors
Literature
review
Team
discussion
Potential risk
factors
Formal risk
analysis
High
priority risk
factors
selected for
analysis
Expert
opinion
Completed
In Progress
Factor Identification
Results of process:
• 40+ risk factors
identified
• Lack of expert input
• Expect 10 – 20 high
priority risk factors
• Data availability a
problem
Damage from shipping traffic
Damage to benthic community
Damage to footings by wave action
Crosses habitat of endangered species
Release of toxic sediments
Damage to coral reefs
Degredation of landscape
Interference with fisheries
Crosses protected areas
Crosses Wetlands
Damage from landslides
Crosses active faults
Route too close to seafloor obstructions
Seismic zones
Corrosive soils
Mechanically weak soils
Partial list of factors
Workflow: Data Collection & Preparation
Gather Data
Prepare Data
Internet
search
No
Is data
useful?
Yes
Processing steps
• Conversion
• Merge
• Registration
• Resampling
• Set extent
• Transform
Transformed
& aligned
raster layer
for each high
priority risk
factor
Global or regional
vector, raster, tif &
tabular data
w/ citations
Tent. Completed
In Progress
Data Collection & Preparation
Data collection considerations:
1) Is the resolution
sufficient?
2) Is the data
outdated?
TA U R U S
M N T S .
Z
A
G
R
O
S
M
1 km
Too coarse?
O
U
2000 population
density data
Too old?
N
T
A
IN
S
Data Collection & Preparation
Data collection considerations (cont’d):
3) Can the data be
accurately registered
& digitized?
Good
registration
control points?
4) Is the data
complete?
No marine data
1 km
Unregistered
seismic hazard map
Data Collection & Preparation
Data collection considerations (cont’d):
5) Is the data type
suitable?
Coral Reefs
Point or polygon?
6) Are value units
known?
Coral
ReefsTraffic
Shipping
Calculations &
reclassification
Data Collection & Preparation
Data preparation considerations:
1) Raster resampling?
2) Combining marine
& terrestrial datasets
+
=
300m cells
1 km cells
Which resolution?
Edge effects
Data Collection & Preparation
Data preparation considerations (cont’d):
3) How will the coastline
be handled?
Coastlines
need to be
aligned
Potential for data
loss and gaps
Northeast Bahrain Is.
Workflows: Weighting
Gather Opinions
Simple
indexing
Formal risk
analysis
Team
discussion
Literature
review
Survey
Determine Weights
Selection
Frequency &
Degree of
Importance
data for each
high priority
risk factor
In Progress
Pair based
comparisons
Pending
One set of
factor
weights
Two sets of
factor
weights
Weighting
Literature described different weighting methods.
Want to compare results.
1) Simple Weighed Index
Index Factor
• Index values reflect
Probability of Occurrence
& Potential Impact scores
Increasing
risk
• High priority risk factors
ordered by increasing risk
4
A
3
B
2
C
1
D
Weighting
Literature described different weighting methods.
Want to compare results.
2) Pair Based Comparison
• All factors compared, one
pair at a time
• Evaluating Brown &
Peterson method (B&P),
Analytical Hierarchy
Process (AHP)
Factor
A
Factor
C
Factor
C
>
Factor
B
<
Factor
A
=
Factor
B
Weighting
Literature described different weighting methods.
Want to compare results.
2) Pair Based Comparison
(Cont’d)
• B&P relies on Selection
Frequency, has no factor
categories
• AHP relies on Degree of
Importance, can use
factor categories
Factor
A
Factor
C
Factor
C
>
Factor
B
<
Factor
A
=
Factor
C
Workflow: Analysis Methodology
Generate Analysis
Surfaces
Risk factor
layers
Identify Pipeline
Alignments
Three
weight
sets
Least-cost path
analysis between
provided start
and end points
Map algebra and
reclassification
Three alternative
pipeline alignments
(SWI Optimized,
B&P Optimized,
AHP Optimized)
Three risk weighted
analysis surfaces
(SWI, B&P, AHP)
Pending
Questions?
References
Analysis Methodology
Berry, J. K. (2009, August 6). Applying AHP in Weighting GIS Model Criteria.
Retrieved from
http://www.innovativegis.com/basis/Supplements/BM_Sep_03/T39_3_AHPsupplem
ent.htm
Dey P.K. (2001). Integrated approach to project feasibility analysis: A case study.
Impact Assessment and Project Appraisal. 19(3), 235-245.
Dey P.K. and Gupta S.S. (2000). Decision-support system yields better pipeline
route. Oil and Gas Journal. 98(22), 68-73.
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..
References
Analysis Methodology (Cont’d)
Montemurro D., Barnett S., & Gale T. (1998). GIS-based process helps
TransCanada select best route for expansion line. Oil and Gas Journal. 96(25), 6371.
Saaty T.L., Vargas L.G., and Dellmann K. 2003. The allocation of intangible
resources: The analytic hierarchy process and linear programming. SocioEconomic 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_DIS
PLAY_bookid=1384&VerticalID=0
References
Pipelines (Cont’d)
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_KN
OVEL_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
References
Data (Cont’d)
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-consumptionper-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
World Database on Protected Areas. (2009, August 5). Annual Release 2009
Dataset. Retrieved from: http://www.wdpa.org/Default.aspx
References
Data (Cont’d)
World Wildlife Fund. (2009, August 21). Global Lakes and Wetlands Database.
Retrieved from: http://www.worldwildlife.org/science/data/item1877.html