risk-based pipeline route optimization for the persian gulf region scott byron
DESCRIPTION
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 - PowerPoint PPT PresentationTRANSCRIPT
Risk-Based Pipeline Route Optimization for the Persian Gulf Region
Scott ByronExxonMobil Corporation
GEOG 596A Peer ReviewOctober 1, 2009
Ras Laffan Industrial City,Qatar
Installation of offshore pipeline – IranCourtesy Iranian Offshore Engineering and Consulting Co.
Sand dunes in the UAECourt.: ExposedPlanet.com
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 PipelineCourtesy: 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
• Population growth, oil wealth increasing regional hydrocarbon consumption
• Pipelines needed to bring new reserves to market
• Nearly 80 year development history
Regional Overview
Oil FieldsPipelines
2000 Oil Consumption(barrels/1,000 people)
Key Map
0.14 – 0.3333.01 - 65.8765.88 - 98.7398.74 - 131.60
• Extreme desert environments
• Variable land uses
• Variable surface conditions & slope stability
• Limited agricultural area supports regional population
Regional Overview
Semi Desert
2000 Regional Land Use Key Map
ForestShrub/GrassesCropsDesert
Rock OutcropUrbanRivers
• Shallow water depths, high temperatures & salinity
• Variable seabed conditions
• Major commercial route, constrained by Strait of Hormuz
• Growing awareness of environmental issues
-1,788m -90m 2,863mMax depth
of Persian Gulf
0m
Persian Gulf RegionTopography & Bathymetry
Key Map
Hillshade courtesy Carla Wilson
Regional Overview
Methodology
Study Area Selection
• Centered on Persian Gulf markets
• Disk space use is a consideration
• Encompasses a variety of geographic zones
Hillshade courtesy Carla Wilson
-1,788m -90m 2,863mMax depth
of Persian Gulf
0m
Persian Gulf RegionTopography & Bathymetry
Key Map
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
Teamdiscussion
Literaturereview
Expertopinion
Potential risk factors
Formal risk analysis
High priority risk
factorsselected for
analysis
Select High PriorityRisk Factors
Completed In Progress
• 40+ risk factors identified
• Lack of expert input
• Expect 10 – 20 high priority risk factors
• Data availability a problem
Damage from shipping trafficDamage to benthic community
Damage to footings by wave actionCrosses habitat of endangered species
Release of toxic sedimentsDamage to coral reefs
Degredation of landscapeInterference with fisheriesCrosses protected areas
Crosses WetlandsDamage from landslides
Crosses active faultsRoute too close to seafloor obstructions
Seismic zonesCorrosive soils
Mechanically weak soils
Partial list of factors
Results of process:
Factor Identification
Gather Data
Internet search
Global or regional vector, raster, tif
& tabular dataw/ citations
Transformed & aligned
raster layer for each high priority risk
factor
Prepare Data
Tent. Completed In Progress
Workflow: Data Collection & Preparation
Is data useful?
Yes
NoProcessing steps• Conversion• Merge• Registration• Resampling• Set extent• Transform
T A U R U S M N T S .
ZA
GR
OS
MO
UN
TA
I NS
2000 population density data
Data Collection & Preparation
Data collection considerations:
1) Is the resolution sufficient?
2) Is the data outdated?
Too coarse?
1 km
Too old?
Data Collection & Preparation
3) Can the data be accurately registered & digitized?
4) Is the data complete?
Unregistered seismic hazard map
Good registration control points?
1 km
No marine data
Data collection considerations (cont’d):
Data Collection & Preparation
Data collection considerations (cont’d):
5) Is the data type suitable?
Point or polygon?
Coral Reefs Coral Reefs
6) Are value units known?
Calculations & reclassification
Shipping Traffic
Data Collection & Preparation
Data preparation considerations:
1) Raster resampling?
Which resolution?
1 km cells
300m cells
2) Combining marine & terrestrial datasets
+
=
Edge effects
Data Collection & Preparation
Data preparation considerations (cont’d):
3) How will the coastline be handled?
Northeast Bahrain Is.
Coastlines need to be aligned
Potential for data loss and gaps
Pending
Workflows: Weighting
Gather Opinions Determine Weights
In Progress
Two sets of factor
weights
Pair based comparisons
Literature review
Team discussion
Survey
Selection Frequency &
Degree of Importance
data for each high priority risk factor
Formal risk analysis
Simple indexing
One set of factor
weights
Literature described different weighting methods. Want to compare results.
Weighting
1) Simple Weighed Index
• High priority risk factors ordered by increasing risk
• Index values reflect Probability of Occurrence & Potential Impact scores In
cre
as
ing
ris
k
Index Factor
4 A
3 B
2 C
1 D
2) Pair Based Comparison
• All factors compared, one pair at a time
• Evaluating Brown & Peterson method (B&P), Analytical Hierarchy Process (AHP)
Factor C
Factor B
Factor C
Factor A
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 C
Factor C
Factor C
Factor A
Factor A
Factor B
=
<
>
Weighting
Literature described different weighting methods. Want to compare results.
Map algebra and reclassification
Pending
Workflow: Analysis Methodology
Generate Analysis Surfaces
Risk factor layers
Identify Pipeline Alignments
Three weight
sets
Three risk weighted analysis surfaces(SWI, B&P, AHP)
Three alternative pipeline alignments
(SWI Optimized, B&P Optimized, AHP Optimized)
Least-cost path analysis between
provided start and end points
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_AHPsupplement.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), 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
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_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
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-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
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