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Case Study Using the Decision Analysis Process to Select a Remediation Strategy
for an Upstream Oil and Gas Facility
KENT BURKHOLDER, Decision Frameworks Inc.
JAMES ARMSTRONG, Komex International Limited
KEVIN BIGGAR, University of Alberta, Civil and Environmental Engineering
2
Case background
Flare pit plume
Residual free-phase hydrocarbon
Stable/downward dissolved hydrocarbon trend
Enriched iron & methane
Depleted DO & sulfate
l Interpretation:
Supporting evidence of natural attenuation
Liquid hydrocarbon source remaining
Monitoring Well
CPT-UVIF Hole
CPT-UVIF Well
Trees
Plume Edge
OldSource
Oil Edge
BH01
Hand-Auger Well
Seasonal Influences
No local receptors
No human land use
5
What is the most cost effective remediation method available that meets environmental guidelines?
Key questions the evaluation must answer:
l How does uncertainty in the plume size affect the decision?
l What is the probability that natural attenuation will work?
l Is it worth collecting new site information before deciding on a remediation method?
6
Remediation alternatives
1. Excavate contaminated soil and dispose off-site
2. Excavate contaminated soil and treat on-site
3. Combine liquid source pumping with natural attenuation
Note:
l Include ‘Penalty Function’ for not meeting goals
l For each alternative, develop and run model using both chance and range uncertainties
7
Collect input values and assess base case results
l Provide cost estimates using most likely (P50) values
l Assess outcomes due to range uncertainty (i.e., influence of range in estimated contaminated volumes)
l Structured assessment of input range sensitivities (i.e., compare to ‘gut feel’and ‘policy’-based estimates)
l Note that deterministic analysis does not assess chance uncertainty (i.e., probability of something happening or not)
8
Base cost estimate with sensitivities on key uncertainties
9
Decision tree models the order of decisions and uncertainty resolution
l Include chance uncertainties
What is the probability that the fluid does not pump?
What is the probability that the contaminant migrates?
10
Develop decision tree
l Include ‘Penalty Function’
What is the probability of being penalized?
What is the scale of each penalty type?
l Identify effect of penalty on subsequent decisions
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Structure of penalty function
12
Examine model results for insight
l What is best option using lowest ‘expected cost’ as the decision metric?
l What are the combined effects of the range and chance Uncertainties?
l How palatable are the individual outcomes?
Are there any potential outcomes that your company could not survive?
What is the chance of occurrence?
l Would resolving any of the key uncertainties today have the potential to change the remediation decision?
If so, is there an opportunity to collect more information today?
13
Decision tree results
14
Examine cumulative probability outcomes to determine the complete range of outcomes and their likelihood
15
Examine value of information for alternatives
l How might a pilot test affect a decision?
l What value does a pilot test add?
l How might a decision change?
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Examine the updated range of outcomes against the new, hybrid strategy that includes the pilot project
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Examine model results without discounting
l Change in probable cost outcomes
l Removing discounting affects lower end probability results
l Meaning of discounting on ‘real’ costs
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Discounting effect
19
Conclusions
l Decision analysis identifies key influences
l Probable outcomes are illustrated and ‘ranked’
l Value of additional information is objectively displayed
l Influence of changes are readily examined
l Clear image of project ‘value’
20
Acknowledgements
l CORONA Program partners:
CAPP, ConocoPhillips Canada, Devon Canada
Alberta Environment, COURSE, Environment Canada
Komex International Ltd., Maxxam Analytics
l Decision Frameworks Inc.
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