Throughout the day, natural gas pipelines post scheduled receipt and delivery quantities for each meter point on their systems. This data represents natural gas flows and capacities in producing regions, demand areas, storage facilities and all points in between. This data is powerful, with the potential to show natural gas production out of a basin each day, or the total volume of gas moving into or out of storage daily. However, the data is posted in a variety of formats using somewhat cryptic coding structures, and as such can be difficult to interpret. The challenge is being able to assemble that massive amount of data in a usable format and in a timely fashion.
Platts has met that challenge with its Energy Data WarehouseTM. Platts' proprietary, flow-data-gathering technology collects data on daily volumetric gas flows from more than 140 pipelines and storage facilities covering more than 28,000 specific points. On a near-real-time basis, every detail of gas flow in the North American market is available for analysis. The data can be accessed through either of two different methods: online via BENport, Platts' web-based portal, or delivered electronically to your company’s servers.
Using BENport, you can use easy-to-understand, drop-down menus to select the data you need, and then extract the data into various document types, including Excel, CSV or HTML. No IT expertise is needed. Just make your data selections and download the data. Data can be queried by day, week or month, and historical data can be accessed back to Jan. 1, 2001, on most pipelines.
Platts also offers pipeline data via its FTP Energy Data WarehouseTM. This version of the Energy Data Warehouse creates and maintains a replica of the database that Platts analysts use each day – on your company’s servers. That gives you complete control over how the data is used.
Of course, Platts' customer support representatives are available to help set up your Energy Data Warehouse, and our analysts are available to answer any questions on techniques and methodologies for using the data.