A View from Space: Multi-spectral and Hyperspectral Data

The first satellite was launched in 1957 by the Soviets (Sputnik 1), quickly followed by one launched by the Americans (Explorer 1).  And so began a new way to look at the Earth.  Today more than 2,200 satellites orbit the Earth, many providing a steady stream of scientific data.

Accurate satellite imagery may be the most cost-effective source of data collection in oil and gas exploration available today. It often has the ability to reach parts of the Earth that are otherwise too difficult to access or photograph, providing datasets of value to industry geoscientists.

In the case of oil and gas exploration, the most common and valuable types of satellite data include multi-spectral, hyperspectral, gravity, magnetic and remote sensing (the use of aerial photography [often satellites], combined with other methods to view that which cannot be seen by the unaided eye).

Although some of these datasets may not contain the spatial sampling, therefore resolution, associated with NEOS’ new data acquisition programs, our geoscientists are nonetheless able to generate many of the same interpretive products you need to explore, including:

  • Assessments of basin-scale geologic trends
  • Maps of basin architecture and regional structure
  • Maps of key lineaments, regional fault systems, and intrusions
  • 2-D and 3-D structural and stratigraphic models
  • Maps of basement topography, faulting and composition
  • Assessments of relative acreage prospectivity derived using predictive analytics.

In this blog series we look closely at the data provided by satellites that reside in the public domain, to see what value can be gleaned as well as encountered limitations that result from limited spacial samples or true global coverage.

Multi-Spectral Data

(Left) ASTER multi-spectral satellite data and (right) public data from the NASA earth observatory website. Both show oil slicks on surface of the water. The one on the left highlights slicks and their buildup on the coast after an oil spill disaster.

What is it/How is it used: The Landsat 8 is a polar orbiting satellite system that collects publically-available multi-spectral data of the entire Earth every 16 days. One common use might be to detect lithologies or minerologies (such as iron, clay and carbonate) on the Earth’s surface. For offshore use, it is often used to look at sea migrations.  With the detection of sea temperature variations, it can detect offshore seeps which can be used for oil spill management.

Value: Because of its continual orbit of the earth, there is a significant amount of Landsat 8 data available. It is optimal for assessing large swaths of land. NEOS has incorporated Landsat 8 data previously in various neoBASIN programs as part of the ‘ground’ component of the project to “postage stamp” the area and cross correlate the data with later-collected NEOS airborne hyperspectral data.

Limitations: Unfortunately, the Landsat 8 has a relatively lower spectral resolution, with 11 bands. It has difficulty detecting onshore oil seeps; they are often too small at this resolution.  The spectral resolution also limits our detection of specific minerals as well as indirect hydrocarbon features.

Hyperspectral Data

Hyperion coverage for the San Juan project. There were two separate images taken at different times.
Hyperion data over a large area. There were two separate images, of the same location, taken at different times.

What is it/How is it used: The Hyperion Sensor is another free satellite resource that collects hyperspectral data at 30 meter resolution pixels.  It can detect seepages and mineralogy at a higher spectral resolution than Landsat 8 with hundreds of spectral bands (as opposed to 11), though still at a lower resolution than NEOS acquired airborne Hyperspectral data (4-5 meter resolution). It collects data around the world, both onshore and offshore, but the total collection area is very limited.

Value: Hyperion data is of great value when cross checking/cross correlating with NEOS Hyperspectral data.  For neoBASIN projects, where Hyperspectral data isn’t a part of the program, NEOS can incorporate Hyperion data (when available) into the general interpretation for a little more insight into the area.

Limitations: The EO-1 satellite, that the Hyperion sensor is situated on, is not always collecting data, therefore global coverage is minimal.  The USGS does allow you to request areas for scanning but requests aren’t always fulfilled.