Petroleum exploration began with the search for
hydrocarbon indications at the surface. Now, sophisticated airborne
and satellite remote sensing tools continue that search.
Hydrocarbon micro-seepage occurs for long time
periods - relative to vegetation life spans - so they don't actually
produce the usual "stress" in vegetation. Rather, the hydrocarbon
presence produces structural changes in vegetation (e.g., changes in
species, plant distribution, crown density, leaf structure, or
apparent vigor - dwarfs or giants). These changes, over an actively
seeping area, produce subtle changes in spectral reflectivity.
Each chemical element and molecular compound has
a unique spectral signature. Thus we can spectrally identify areas
altered by hydrocarbon seepage. The greater number of spectral bands
available in Spectral data, such as NASA's AVIRIS instrument, allows
even more precise detection and differentiation of alteration
produced by seeping hydrocarbons.
Hydrocarbon trap seals range from very efficient
to relatively inefficient. Thus, many hydrocarbon accumulations have
some leakage to the surface. Leaking hydrocarbons effect a host of
changes on the rocks and soils through which they pass. At the
surface, subtle differences in mineral composition or vegetation
manifest these changes. Using sophisticated spectral processing, one
can emphasize some of these subtle differences. Spectral satellite
data are particularly useful for this task because the data is
composed of millions of color-coded, digital, squares called pixels.
In a process knows as pattern recognition computers can easily
compare one pixel to other pixels from known oil and gas seeps. The
color-coded pixels are made into a map of favorable hydrocarbon
matches. Red pixels have the highest potential and green pixels the
lowest potential.
Airborne and Satellite Spectral sensors flown
over known hydrocarbon leaks have found that an absorption feature
near 2.31 µm (micron) is very sensitive to the amount of a specific
component of hydrocarbons. A ratio of two reflectance values on
either side of that absorption feature divided by the value of the
decreased reflectance in the spectral curve at the feature low point
enhances the delectability of the hydrocarbon and quantifies its
magnitude.
The DSSM maps are based on Spectral Satellite Images. The
interpretation is based on pixel pattern recognition algorithms,
stressed vegetation analysis, and the reflectivity ratios of iron
and clay minerals all of which are known hydrocarbon indicators. All
opinions are based on field experience and published data. We cannot
and do not warrant the accuracy, nor will we be liable for any other
interpretations.
