Abstract
Water–oil separation is important in the oil industry, as the incorrect classification of oil can lead to losses in the production and have an environmental impact. This paper proposes the use of fiber Bragg grating (FBG) temperature sensor array to identify the oil in water–emulsion–oil systems, using only the temperature responses for oil classification results in operational and economic benefits. To demonstrate the possibility of using the FBG temperature sensor to classify oil level, the temperature distribution of an oil storage tank, with 2 m height and 0.8 m in diameter, is simulated using thermal distribution models. Then, the temperature effect in a 2 m long FBG array with a different number and distribution of FBGs is simulated using the transfer matrix method. In each case, we extract the wavelength shift (Δλ), total width at half the maximum (FWHM) and the location of the FBG in the fiber. For the oil classification, we dichotomized the fluids into oil and non-oil (water and emulsion). Due to the low separability of the classes, the random forest algorithm was chosen for classification, starting with 200 FBG equidistant sensors and decreasing to 6, with different distributions along the fiber. As expected, the highest accuracy occurs with the 200 FBGs array (96%). However, it was possible to classify the oil with an accuracy of 94.89% with only 8 FBGs, using tests for two proportions (with a significance of 5%); the accuracy of 8 FBGs is the same as of 50 FBGs.
Highlights
The water-oil separation is an important process in oil industry [1]
This paper presents a simulation study of fiber Bragg grating (FBG) temperature sensors classification in oil using as lower number of sensors as possible
To find the ideal number of FBGs and their location, different points were tested based on RF accuracy
Summary
The water-oil separation is an important process in oil industry [1]. Oil is the principal energy source of the world [2]. The oil arrives in the tanks combined with water, gas, and sludge. The combination of these components forms the water-oil interface [3]. The effective monitoring, control and separation of oil and water layers in production tanks result in economy on oil production costs and reduction of the environmental pollution [3]. A problem in oil classification is to detect emulsion layers, a region between water and oil in which fluids blend homogeneously [1]
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