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Quantitative Risk Assessment and Mitigation for Onshore and Offshore Assets

Quantitative Risk Assessment and Mitigation for Onshore and Offshore Assets. Paolo Bazzurro, Ph.D. Akshay Gupta, Ph.D., PE 2010 Marine Insurance Seminar Houston , TX September 20, 2010. What’s Churning in the Atlantic?. Energy Insurance Market.

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Quantitative Risk Assessment and Mitigation for Onshore and Offshore Assets

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  1. Quantitative Risk Assessment and Mitigation for Onshore and Offshore Assets Paolo Bazzurro, Ph.D. Akshay Gupta, Ph.D., PE 2010 Marine Insurance Seminar Houston , TX September 20, 2010

  2. What’s Churning in the Atlantic?

  3. Energy Insurance Market • Energy capacity highest for 10 years (source: Willis Group Holdings, 03/24/2010) • Last four years, capacity has increased 60% overall • Lack of recent major catastrophe losses • Upturn in energy industry activity • Worldwide recovery in oil prices • Several potential buyers not purchasing the GoM wind products • Entering a soft market • “… volatility of the energy sector is such that a big loss is always looming around the corner.” • “…prices for offshore energy-related coverage was up as much as 50%.” (source: Willis Group Holdings, 06/03/2010)

  4. Agenda • Hurricane hazard for GoM • Exposure • Offshore • Onshore • Vulnerability • Evaluation of Loss Potential • Example: Energy entity with onshore and offshore assets

  5. Tropical Storms in the Atlantic

  6. Historical Major Hurricanes Major Hurricane (V > 110 mph) Tracks in GoM : 83 events

  7. TROPICAL STORMS 10.7 HURRICANES 6.2 (58%) MAJOR HURRICANES 2.8 (26%) Average and 2010 Atlantic Hurricane Season 18 9/15/10 12 11 10 9 8 7 6 5 4 3 2 1 11 10 Atlantic Basin Storm Count 5 5 4 CSU Projection (as of Aug. 4, 2010, same as Jun 2, 2010) May Jun Jul Aug Sep Oct Nov Dec Jan Atlantic Hurricane Season

  8. Exposure

  9. Offshore Exposure: Platforms and Rigs • ~5500 Platforms/Rigs • ~$90B

  10. Offshore Exposure: Platforms and Rigs *Platforms in TX state waters not accounted for Source: AIR

  11. Offshore Exposure: Wells • ~27,000 Wells

  12. Offshore Exposure: Oil Production Volume (2009) • 420 Million BLLS • $23B • OIL • 2300 BCF • $10B • GAS

  13. Offshore Exposure: Subsea Pipelines ~35,000 miles ~$70B

  14. Onshore Energy Exposure • Pipe Coating Yards • Natural Gas Processing Facilities • Natural Gas Storage Facilities • Refineries • Petrochemical Plants • Platform Fabrication Yards • Port Facilities • Shipyards and Shipbuilding Yards • Support and Transport Facilities • Waste Management Facilities Image source: National Petrochemical and Refiners Association

  15. Vulnerability

  16. Risk to Offshore Platforms

  17. Wind Wind Waves Risk to Offshore Platforms Jacket Platform Topside (Decks and Equipment) Mean Sea Level (MSL) Structure and foundations Waves dominate Mud line

  18. Risk to Offshore Platforms

  19. Risk to Offshore Platforms Drilling Rig on MARS Tension Leg Platform Before Rita After Rita ~ 150,000 bpd $300M PD loss ~ $10M/day BI loss ~ 10 months to fix Removing fallen drilling rig

  20. Risk to Subsea Pipelines, Wells and Equipment • Subsea currents • Mudslides • Damage and Failure of Platforms/Rigs (Image source : MMS Report # 581“Pipeline Damage Assessment from Hurricanes Katrina and Rita) Oscillatory current (Image source: OTC Ref #17734

  21. Risk to Onshore Assets • Wind • Flood (storm surge & precipitation)

  22. Risk Assessment for an Energy Entity

  23. Energy Company A: Upstream - Downstream • Company A Exposure • Three Platforms • 1 Fixed Jacket • 1 Jackup • Twenty Wells • 7 Natural Gas • 13 Oil • 75 miles of subsea pipelines • $3B onshore refinery • $750M storage farm

  24. Overall Modeling Methodology

  25. Annual Frequency Forward Speed Development of a HUR Stochastic Catalog Location Frequency StochasticCatalog Landfall Angle Min. Central Pressure Radius of Max. Winds

  26. Hazard: Simulation of Cyclone Parameters

  27. Hazard: Stochastic Catalog Event Set for GoM • 50,000 year event stochastic catalog • 50,000 possibilities of next year’s activity in GoM • Over 200,000 events in the 50,000 year catalog • Validated against historical record

  28. Category 1 Category 2 Category 3 Category 4 Category 5 1’-sustained wind speed (mph) 74 95 110 130 155 1’-sustained Wind (Hurricane) Hazard Curve

  29. Gulf of Mexico Wave Model • Significant Wave Height, Hs • Wave Crest, Hmax • Wave Duration Site A Site B

  30. Exposure: Platforms • Location • Type • Deck Height • # of Decks • # of Legs • Bracing System • Manned/Unmanned • TRV • % of TRV in topside • # of Wells • Production Volume 28.91°N 90.13°W

  31. Exposure: Undersea Pipelines • Path • Diameter • Buried/Unburied • Flow Volume Start: 28.91°N 90.13°W End: 29.22°N 90.09°W

  32. Exposure: Refinery and Storage Farm 29.22°N 90.09°W • Location • Facility TRV • Breakdown of TRV by blocks • Breakdown of block TRV by components (e.g., cooling towers, control centers, reactors, etc.) • Elevation of blocks and components • Product Daily Revenue 29.23°N 90.12°W

  33. Exposure: System Operations Network • Operational connectivity from wells to sales • Connectivity between facilities AND within facilities • Essential for accurate BI loss est. .es Refinery Connectivity System Connectivity Platform 1 Platform 2 Platform 1 Platform 2 VS. Storage Refinery Storage Refinery Sales Sales

  34. Mean Damage Ratio Wave Height - Deck Height Vulnerability of Platforms to Wave Loading Mean Damage Ratio Wind Speed

  35. Vulnerability of Pipelines to Currents/Mudslides • Pipeline Vulnerability defined by fragility functions relating probability of a particular damage state to the appropriate hazard intensity measure

  36. Vulnerability of Onshore Assets to Wind

  37. Probabilistic Loss Analysis + Event Catalog Site-Specific Hazard Curves Physical Loss BI Loss Exposure (Assets) and Vulnerability

  38. Probabilistic Loss Estimates: By Peril • Loss by peril: note difference in relative loss between 100 yr and > 1000 yr loss. Helps determine appropriate risk mitigation strategy within portfolio. Waves Wind Surge Current Total Loss Mean Return Period (years)

  39. Probabilistic Loss Estimates: By Asset • Disaggregation of loss (PD and/or BI) into primary components (could be amongst properties in the portfolio, by coverage, etc.). Helps determine where to focus risk mitigation. AAL Storage Platform 2 Oil Wells Refinery Pipeline Platform 1 Gas Wells Portfolio Oil Wells Storage Platform 1 Refinery Platform 2 Gas Wells Pipeline

  40. Probabilistic Loss Estimates: Network • Explicit network analysis leads to realistic BI computation; ignoring network results in markedly erroneous results Network NOT included Network included Total Loss Mean Return Period (years)

  41. Conclusions • Significant offshore and onshore exposure at risk from tropical cyclones • Scientific and engineering approach for probabilistically quantifying the hazard, physical damage, and business interruption • Quantitative risk estimate can provide the sound basis for informed decision making related to catastrophe risk mitigation

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