Compositional mapping petroleum

Nevertheless, in the simplest sense, petroleum can be considered composites of four major operational fractions. However, it must never be forgotten that the nomenclature of these fractions lies within the historical development of petroleum science and that the fraction names are operational and are related more to the general characteristics than to the identification of specific compound types. Nevertheless, once a convenient fractionation technique has been established, it is possible to compare a variety of different feedstocks varying from conventional petroleum to propane asphalt (Corbett and Petrossi, 1978). Later studies have focused not only on the composition of petroleum and its major operational fractions but on further fractionation, which allows different feedstocks to be compared on a relative basis to provide a very simple but convenient feedstock map. 

Composition map a means of illustrating the chemical make-up of petroleum using chemical and/or physical property data. 

The purpose of an activity map is to show at what range of concentrations in a system and how a chemical flood will work. For a given reservoir where the temperature, composition of crude oil, and residual oil saturation are fixed, five kinds of variables are under our control types of alkalis, concentrations of alkalis, types of surfactants, concentrations of surfactants, and salinity. Another important variable that is not under our direct control is the type and amount of petroleum acid that will convert to soap when contacted by the alkalis. As discussed earlier, the amount of soap will determine the concentrations of alkali and surfactant injected. In other words, to generate an activity map, we have to know the amount of soap that can be generated. Because the alkali concen-ttation typically is much greater than that required to convert all the petroleum acids in the oil to soap, the petroleum soap concentration (meq/L) is calculated... 

The LST and total petroleum hydrocarbon (TPH) are positively correlated. The methodology followed is based on the fact that most of the satellites carry a thermal infra-red band which can be used for LST estimation. The spatio-temporal variation in the thermodynamic properties of surface material has been mapped in order to identify hydrocarbon polluted surfaces using Landsat TM data. Emissivity is a strong indicator of compositional variation in silicate minerals which make up the bulk of the earth s surface material. Emissivity affects the apparent temperature due to changes in the thermal properties of materials (conductivity, density, capacity, and inertia). There are several algorithms proposed to estimate LST from remotely sensed data. The most common of these are mono-window and split window methods [22-25], the latter was used initially to estimate sea surface temperature. 

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