NGA posts oil storage management RFI

On November 25, the National Geospatial-Intelligence Agency (NGA) posted a request for information on oil storage measurement services. Responses are due by 5:00 p.m. Central on December 10.

NGA in support of the Analysis Directorate is seeking information on how an interested contractor could provide oil storage measurement services, which leverage advanced Synthetic Aperture Radar/Electro-Optical (SAR/EO) processing.

The purpose of this Request for Information (RFI) is to gain information on commercial capabilities to meet this requirement, identify sources, analytic tools, and methodology that would be used to meet this requirement, and to gain information on expected cost associated with accessing all vendor data and/or on a per-location (country) basis.

NGA has a need to monitor Petroleum, Oil, and Lubricants (POL) tank inventories across several geographic areas.  We would like to automate the process of measuring storage levels of floating -lid POL tanks. We would like to see a streamlined process for the capture of floating lid oil tank data.

Additionally, NGA seeks to understand the following elements of the service:

  • Scalability: the ability of the vendor to scale the service to additional geographic areas with expanded infrastructure, personnel resources and additional data sources; when describing the method for scaling the service, the vendor should describe the required expanded infrastructure and personnel resources – and the additional data sources – necessary for each “level” of scalability.
  • License: the vendor must thoroughly describe any and all license conditions and assumptions, such as the ability to share raw measurements, derived products and any analysis.
  • Automation: the use of automation and benefits of human intervention, when applied to specific segments of the processing chain.
  • Machine Learning: describe the use of machine learning and training sets and describe the ability of the vendor’s service to reduce human intervention over time through the use of machine learning.
  • Geographic Coverage: ability to cover oil storage sites for any location in the world, any geographical limitations to the service.
  • Derived Data Accuracy: the vendor should include information on known and tested derived data accuracy regarding the measurements and clearly address how uncertainty is quantified and addressed
  • Sources: current and planned, weather, temporal (how many observations per month), geographical or any other constraints.
  • Metadata: information on metadata associated with the measurements and imagery used to derive the measurements
  • Geospatial Usability: description of how the vendor anticipates users to interact with their products, especially the raw data measurements. 

Full information is available here.

Source: SAM