An article* in Total’s TechnoHub magazine describes a novel use of OSIsoft’s PI System to gather and transmit metocean data with remote shore-based meteorologists. A 2008 pollution incident on Total’s Angolan Dalia complex revealed that its legacy oil slick tracking tool performed poorly and that consequently, drift prediction was unreliable.
Total set out to develop a solution, Spill Watch, leveraging new developments in satellite imaging, data transmission and weather forecasting. Total SVP HSE Thierry Debertrand said, ‘Good prediction models make it possible to forecast the drift of an oil slick, identify areas for intervention teams, predict the timing and areas of potential impact and inform neighboring installations, authorities and NGOs.’
Metocean data, including high-frequency radar imagery, of wind, currents and temperatures at the surface and in the water column are captured to an OSIsoft PI System data historian for transmission in real time to the French meteorological service Météo France. Here, location-specific metocean models have been created and calibrated with accurate drift models.
Météo France integrates the local data with the World Meteorological Organization’s real time system. Historical data is shared with the SIMORC (System of Industry Metocean data for the Offshore and Research Communities) database and made available to the wider community. Total’s location-specific spill models have been fine tuned and now provide five day forecasts of current and wind information.
Spill Watch was activated in 2012 when a gas leak on the North Sea Elgin field occurred. Here the condensate slick’s shape and drift were forecast and used in organizing Total’s response. Spill Watch proved a ‘valuable instrument for communicating with the authorities.’ Real time metocean data, satellite images and modeling reports were communicated to crisis managers and the regulator.
Spill Watch has allowed Total to coordinate geographically dispersed resources and to advance its understanding of local metocean conditions, slick-tracking and drift-prediction.
* Spill Watch, Total Techno Hub N° 4, July 2013.
This article originally appeared in Oil IT Journal 2013 Issue # 9.
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