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Risk of large oil spills: A statistical analysis in the aftermath of Deep Water Horizon
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Risk of large oil spills: A statistical analysis in the aftermath of Deep Water Horizon

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Petrissa ECKLE, Peter BURGHERR, Edouard MICHAUX

Petrissa ECKLE, Peter BURGHERR, Edouard MICHAUX

Paul Scherrer Institute, Switzerland;

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Risk of large oil spills: A statistical analysis in the aftermath of Deep Water Horizon Risk of large oil spills: A statistical analysis in the aftermath of Deep Water Horizon Presentation Transcript

  • Wir schaffen Wissen – heute für morgen Risk of large oil spills – A statistical analysis in the aftermath of Deepwater Horizon Petrissa Eckle, Peter Burgherr, Edouard Michaux Paul Scherrer Institute, SwitzerlandIDRC, Davos, August 28, 2012
  • Deepwater Horizon/ Macondo, Gulf of Mexico 2010― Largest accidental oil spill so far― 11 workers killed, 17 injured in explosion― Uninhibited flow for 3 months― 680‘000 t of oil spilled― 14 billion USD in immediate cleanup costs― 30 billion in total so far― Environmental and economic consequences will only become clear over coming yearsIDRC, Davos, August 28, 2012 2
  • Deepwater Horizon/ Macondo, Gulf of Mexico 2010Questions to be answered―Outlier or not?―How much do such single events contribute to total?―Higher risk from drilling than other activities (e.g. tanker spills?)IDRC, Davos, August 28, 2012 3
  • Context Comparative risk assessment of energy supply optionsIDRC, Davos, August 28, 2012
  • Comparative Risk Assessment Energy Systems Analysis Economy Environment Social Risk of severe accidents, terrorism and critical infrastructure protection Risk indicators: Average fatalities per year Maximum historical accident Expected fatalities per year Exceedance at frequency F Expected fatalities in frequency F accident FatalitiesIDRC, Davos, August 28, 2012
  • Requirements - approach Data based where possible – combine with modeling where necessary – Historical data: Accident database ENSAD (mainly fossil fuels) - comprehensive global coverage of energy related accidents since 1970 – Input from probabilistic models: Nuclear power – Hybrid & expert judgment: New renewables, hydro power, CCS Complete energy chains – resource extraction to waste Exploration Extraction Transport Refining Transport Power/Heating Plant Waste Treatment & Disposal Focus on severe accidents (≥ 5 fatalities, 10 injured, 10.000 t oil spilled..) Top down: start with generic risk distributions – refine where possible Core risk indicators: - impact on human life: fatalities, injured - impact on the environment: oil spills, land contamination (e.g. radiological for nuclear)IDRC, Davos, August 28, 2012 6
  • Deepwater Horizon/ Macondo, Gulf of Mexico 2010Questions to be answered―Outlier or not?―How much do such single events contribute to total?―Higher risk from drilling than other activities (e.g. tanker spills?)IDRC, Davos, August 28, 2012 7
  • Breakdown of sources 4 infrastructure categories: - Ship spills - Storage/refinery - Pipeline - Exploration/production Number of spills: 1213 Total of oil spilled: 9.8 mio tons Pipelines Storage/Refinery Pipelines Storage/Refinery 870‘000 t 750‘000 t 188 113 Exploration & production 24 Exploration & production 2.2 mio t Ship Ship 888 6.0 mio tAccidental spills > 200 tons, 1974-2010IDRC, Davos, August 28, 2012 8
  • Breakdown of sources Goal: Quantify probability of spills as a function of spill amount ► expected return frequency of spill of size x How often can we expect an event like the Deepwater Horizon accident? Number of spills: 1213 Total of oil spilled: 9.8 mio tons Pipelines Storage/Refinery Pipelines Storage/Refinery 870‘000 t 750‘000 t 188 113 Exploration & production 24 Exploration & production 2.2 mio t Ship Ship 888 6.0 mio tAccidental spills > 200 tons, 1974-2010IDRC, Davos, August 28, 2012 9
  • DistributionsRISK = Frequency x Severity Number of accidents per year Spill amount per accident – Mean frequency & trends – Fat tailed distribution – Rare, independent events – Measure tail thickness Poisson ► Model: Poisson ► Model: – Empirical distribution – Generalized Pareto (GPD)IDRC, Davos, August 28, 2012
  • Risk: Frequency vs. severity Data Fit: Generalized Pareto (FN-curve = 1-empirical CDF*) (1 – CDF*) Spill amount [tons] *CDF: Cumulated density functionIDRC, Davos, August 28, 2012 11
  • FrequencyIDRC, Davos, August 28, 2012 12
  • Results: Ship Spills 1974 - 1980 1981-1990 1991-2000 2001-2010 Spill amount [tons]IDRC, Davos, August 28, 2012 15
  • Results: Ship Spills 1974 - 1980 10 per year 1981-1990 1991-2000 2001-2010 0.6 per year Spill amount [tons]IDRC, Davos, August 28, 2012 16
  • Results: Overview Ship & storage/refinery: highest freq. for medium severity Exploration/production: Global frequency [1/year] Highest freq. for high severity DWH Largest oil tanker Spill amount [tons]IDRC, Davos, August 28, 2012 17
  • Risk before and after Deep Water Horizon Compare expected return frequency of the DWH spill before and after the new „data point“ Global frequency [1/year] 17 years return period* *Uncertainty interval 5-95%: 10-70 yrs 22 years return period Spill amount [tons]IDRC, Davos, August 28, 2012 18
  • Conclusion Structure of risk varies strongly between infrastructure subcategories: - Transport/storage spills dominate small/medium spill risk - Exploration/production: highest potential for very severe accidents Top down risk assessment as a complement to bottom up engineering risk assessment For risk of high severity events – global and long term dataset is essentialIDRC, Davos, August 28, 2012 19
  • Thank you for your attention www.psi.ch/gabeIDRC, Davos, August 28, 2012 20