Ocean predictions and the oil and gas industry - room for improvement?

1. Ocean predictions and the oil and gas industry - room for improvement? Colin Grant Metocean Technical Authority

2. Ocean predictions and the oil & gas industry • Ocean predictions have uses in 3 main areas in the industry • Forecasts – real time operations and short term planning (1 to 5 day) • Reanalysis products / hindcasts – operational planning • “weather windows” • Databases to establish design criteria such as 100 year and 10,000 year values

3. How useful are present ocean predictions? • Waves • Generally acceptable quality for both short term forecasts and as hindcast databases. Suitable calibration with measured data permits use for design studies and operability analyses. • Currents • Lack of accuracy in temporal comparisons – frequently miss peak events when compared to measured data. Issues of sampling. Some skill in certain regions on a climatological basis. Used with care by the industry, for design studies, often after calibration & adjustment. • Water level • Useful products for design when combined with extreme wave predictions to establish total water levels. Setting of platform decks. • Temperatures & Salinity • Industry not a major user. Hindcast archives used for design (flow assurance issues – hydrate formation etc). Oil spill weathering issues • Sea ice conditions • Increasingly important with the move towards Arctic environments

4. Wave and current comparisons with data

5. Major challenges & requirements • Industry moving to deeper water and arctic areas. • Deep water operations require knowledge of currents through the water column, both as forecasts and as hindcast databases. • Riser and mooring design and control • Combinations of parameters for response-based analyses using joint probabilities of key parameters • Winds, waves & currents • Wave crests & water levels • Waves, currents and sea ice • Example • Gulf of Mexico

6. Gulf of Mexico - Loop & Eddy Forecasts

7. Macondo Oil Spill

8. Macondo oil spill modeling • Much modeling activity both by BP and the US Govt • BP’s in-house oil spill model is being standardised on SINTEF’s “Marine Environmental Modelling Workbench” • OSCAR – Oil Spill Contingency & Response • DREAM – Dose-related Risk & Effects Assessment Model • DEEPBLOW • Require initialisation and boundary conditions from atmospheric and ocean models in order to run effectively • Several other oil spill modelling providers e.g. ASA, BMT etc http://www.sintef.no/static/ch/environment/numerical_modelling.htm

9. Scenario – West of Shetland spill • “My Ocean” Resource • Time res – Hourly (+ daily mean) • Spatial res - 0.1 deg • (approx 6km) • Depth • Numerous levels to 600m • Variables • N & E Velocity • Salinity • Temperature • Sea surface height above geoid

10. West of Shetland complexity

11. Issues for oil spill modelling • Availability of input data varies regionally • Prediction of deep water oil spill trajectories is now a 3D dispersion problem • Global models e.g. US Navy HYCOM – daily mean values • Nest finer models from global models • Use the ocean model that the regulator uses to enhance acceptability? • Australia - Blue Link CSIRO / BoM / RAN • BP long term collaboration with Imperial College, London • ReEMS - Regional Environmental Monitoring System • Open source codes • WRF + ROMS (including sea ice) + SWAN + NOAH • Main focus is climate change but also being used to assist in oil spill modeling • Caspian used as a test bed (4km resolution) • Work on Mediterranean, West Africa, Brazil etc

12. The future of ocean prediction? • Linking modelling with observations • In-situ, remotely sensed (satellite, aerial, HF radar etc) • Formatting and geo-referencing issues • Data assimilation • Product development and dissemination • Web / GIS based • User friendly – aimed at decision makers, not specialists • Integrated approaches to observation, forecasting and ultimately end user problem solving.

13. Questions