The need existed for an advanced rapid spectroscopic scanning tool, to qualitatively discriminate crude oil reflection spectra, providing and integrated approach to petroleum exploration, improving optimization for refining processes and generally identifying oil origin and oil quality level. This need can be understood as a result of several factors, or viewed from several perspectives.
When viewed from management perspective, any explorations for oil or minerals have to be regarded as a venture investment (Eggert, 1993). Unfortunately, unlike typical business ventures, explorations are more unpredictable and have long lead times. Eggert (1993) states that the research and exploration projects have to be entirely free from pressures from upper management. So, since since oil explorations provide incredibly long lead times, that are unacceptable in the business world, certain strategies have to be applied to counter the deficiencies. Saaty et al. (2012) provides a decision model, which includes various factors like Oil Saturation (inside the place of accumulation, or trap), Effective Porosity, Effective Permeability, Bottom-Hole pressure and Recovery Factor, and while these are very important in establishing the decision for further drilling operations, one crucial factor has been either slipped or intentionally omitted. This is the quality of the product chosen for extraction, i.e. the saturation of it with various fractions. If this kind of information is available for crude oils, more smart business decisions can be derived, on which locations are to be drilled immediately or postponed, based on current market demands and resources available. Moreover, the total costs of each exploration and drilling investment can be cut. The model presented by Saaty et al. (2012) probably included these in Recovery Factor, but, to author's mind, a more sophisticated business decision model can be derived, and the facilitation of such approach can be made by an instrument that provides an in-depth analysis of targeted locations' oil contents, in a fast, industrially powerful and reliable way.
While traditional exploration methods, like seismic reflections/refractions, mostly replaced by more modern remote sensing techniques can be efficient in detecting sites of oil, by thermal imaging, land-satellite imaging and airborne spectrography (Assaad, et al., 2009; Zeinalov, 2000; Wang & Ding, 2000; Borengasser, 2007), these techniques are only able to provide geologic analysis for locations of petroleum traps, or exact locations and possible quantities of hydrocarbons in general. The former techniques can provide detaled maps of geological faults, by combinations of Panchromatic SPOT, Landsat MSS and TM (thermal) imagery with detailed topographic maps, especially if sound processing has been applied to this information conglomerate (Zeinalov, 2000). Other approach to gathering information, provided by airborne infrared VIS-NIR remote sensing, is extremely helpful in locating natural resources and environmental contaminations (Borengasser, 2007). Unfortunately, since a great part of infrared spectrum is closed by air absorptions, and especially this part of the spectrum provides features that allow distinguishing specific hydrocarbons (Borengasser, 2007, Chapters 2,4; Mayo, et al., 2004), only presence of hydrocarbons can be remotely sensed, while more thorough analysis has to be done locally, by core drilling and further …