The Energetic Elephant...
Anonym
Perhaps a descriptive subtitle might read: Energetic = Energy, and Elephant = the proverbial “elephant in the room”. What I’m getting at is a question on my mind that should seem obvious but is otherwise elusive: “Why on Earth (no pun intended) is remote sensing not used more pervasively in energy sectors to provide valuable surface feature information that could help solve problems, increase margins, and improve safety?”
Granted, that is a pretty bold statement, and slightly inaccurate in the sense that remote sensing technology has been used over the years to help with mineral identification, mapping, and generalized resource and operations planning. However, it seems as though several factors have driven the industry toward traditional solutions including sub-surface modeling with electromagnetic and gravimetric data rather than utilizing surface information derived from remote sensing data and technologies.
For years this more traditional approach has been the de-facto standard to many workflows, and with good reason. Low pixel resolution from available satellites has long been cited as one of the major limiting factors thus-far for extracting the scale and accuracy required from a data source for many applications. Some other limiting factors have been: landcover obstruction of relevant surface features, low spectral resolution thus limiting the ability to identify distinguishing surface features, short revisit rates impairing temporal analyses, and high cost for data with the spatial and spectral resolutions necessary for meaningful analysis.
Increased availability to better data is becoming availableto address these shortcomings. For example, the recent launch of Sentinel 1 and access to FREESAR DATA will be a game-changer in the ability to measure and map land subsidence. The launch of micro-satellites by companies like Skybox Imaging will deliver very high revisit rates to enable temporal analyses, and the higher spectral resolution with Digital Globe’s WorldView 3 imagery will provide more spectral insight. These are only a few new datasources out there. I have not even mentioned the use of LiDAR to enable very high-resolution surface modeling, or the impending explosion of the UAS industry which promises to deliver spatial resolution beyond what we might have imagined.
My point is this: Perhaps it is time for the energy industries to take another look at remote sensing technologies – not only as an improved source of surface information, but to add a valuable data layer to existing analytics. Together these pieces tell a more complete story that enable an organization to manage resources and grow their bottom line.