Method for Calculating a Generic Oil

Accidental oil spills are an all-too-common occurrence. In order to properly plan for and respond to oil spills, responders and planners need to understand how the oil will behave in the environment: how it will weather and how it will affect ecosystems and biota. To address this need, databases of oil properties have been developed, such as NOAA’s Automated Data Inquiry for Oil Spills (ADIOS®) Oil Database, a publicly available database of oil properties useful for oil spill modelers, responders, and planners, currently containing over 1400 oil records. However, despite its size, when a spill occurs, the actual oil spilled is unlikely to be in the database, even if the oil’s identity is known. The challenge is even greater for planners, who cannot possibly plan for the spilling of thousands of individual different oils. When the exact product is not available, the responder must choose an oil record from the database that closely resembles the product at hand. This process can slow the responder down and may require them to have years of experience to choose the most appropriate oil record. If not done with care, a user can inadvertently select an atypical oil with a similar name, or a record with poor data quality, which can yield inappropriate results. In this work, we generated a set of “generic” oil records for the ADIOS® Oil Database that have been developed to be a good representation of typical products of a certain type, e.g., “medium crude” or “diesel fuel”. These oil records can then be used in the early stages of a response when details about the spilled product are sparse. These generic oil records can also be very helpful for drills, training, and planning when the user does not need to work with a specific product. These generic records were developed by examining the extensive dataset available in the ADIOS Oil Database and determining which records matched a given type of oil and were of sufficient quality. Then all the records for each oil type were combined to create a “typical” or “average” oil that is representative of that oil type. In the course of this project, statistical methods were chosen that were most appropriate to the property at hand. The oil types chosen were: Light, Medium, and Heavy Crude, Condensate, Jet Fuel, Diesel, Gasoline, Intermediate Fuel Oil (IFO), and Heavy Fuel Oil (HFO). These are all oil types that are likely to be spilled, and for which sufficient data existed in the ADIOS Oil Database to compute an “average” oil. Other potential product types could be added in the future should more data become available.