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

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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

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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?

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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

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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)

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Base cost estimate with sensitivities on key uncertainties

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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?

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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

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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?

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Decision tree results

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Examine cumulative probability outcomes to determine the complete range of outcomes and their likelihood

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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

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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’

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Acknowledgements

l CORONA Program partners:

­ CAPP, ConocoPhillips Canada, Devon Canada

­ Alberta Environment, COURSE, Environment Canada

­ Komex International Ltd., Maxxam Analytics

l Decision Frameworks Inc.