Photonic sensor systems for the identification of hydrocarbons and crude oils in static and flow conditions

Abstract Identification of hydrocarbons and crude oils is typically carried out with samples that, taken from natural sources or refineries, must be brought to the laboratory for their analysis with rather sophisticated instruments. Alternatively, “in situ” procedures have been also developed for this purpose. In this work, we propose the use of a series of several sensor systems based on photonic transducers in the form of chips for the identification and classification of crude oils and hydrocarbons through the determination of their refractive index in the visible and absorption in the near infrared regions of the electromagnetic spectrum. Two of the photonic transducers rely on modifications of a Bragg microcavity and they monitor the changes in visible light interference phenomena that occur in response to the variation of the refractive index of oils. The third one, in the form of a dielectric mirror, monitors the near infrared absorption of crude oils and hydrocarbons through the recording of a transflectance spectrum. The capacity of these transducers for crude oil identification is proved by the analysis of a series of oils and distilled fractions that have been properly identified and classified as a function of their density and partition of long hydrocarbon chains. The three photonic transducers are operated with optical fibers and can be used in static and dynamic modes, this latter under conditions that are especially well-suited for “in-situ” analysis of oil streams in real facilities. The proved resistance of the chips to high pressure and temperature conditions supports their suitability to withstand harsh working environments as those existing in extraction wells.