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Open AccessArticle

Inversion Algorithm of Fiber Bragg Grating for Nanofluid Flooding Monitoring

1
Department of Fundamental and Applied Science, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Perak, Malaysia
2
Advanced Membrane Technology Research Centre (AMTEC), Universiti Teknologi Malaysia, Skudai 81310, Johor, Malaysia
3
Department of Physics, Al-Azhar University, Assiut 71524, Egypt
4
Geology Department, Bayero University Kano (BUK), Kano 700241, Nigeria
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(4), 1014; https://doi.org/10.3390/s20041014
Received: 12 September 2019 / Revised: 12 November 2019 / Accepted: 1 December 2019 / Published: 13 February 2020
(This article belongs to the Section Optical Sensors)
In the current study, we developed an adaptive algorithm that can predict oil mobilization in a porous medium on the basis of optical data. Associated mechanisms based on tuning the electromagnetic response of magnetic and dielectric nanoparticles are also discussed. This technique is a promising method in rational magnetophoresis toward fluid mobility via fiber Bragg grating (FBG). The obtained wavelength shift due to Fe3O4 injection was 75% higher than that of dielectric materials. This use of FBG magneto-optic sensors could be a remarkable breakthrough for fluid-flow tracking in oil reservoirs. Our computational algorithm, based on piecewise linear polynomials, was evaluated with an analytical technique for homogeneous cases and achieved 99.45% accuracy. Theoretical values obtained via coupled-mode theory agreed with our FBG experiment data of at a level of 95.23% accuracy. View Full-Text
Keywords: nanotechnology; fiber Bragg grating; coupled-mode theory; inversion algorithm nanotechnology; fiber Bragg grating; coupled-mode theory; inversion algorithm
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MDPI and ACS Style

Yahya, N.; Mui Nyuk, C.; Ismail, A.F.; Hussain, N.; Rostami, A.; Ismail, A.; Ganeson, M.; Ali, A.M. Inversion Algorithm of Fiber Bragg Grating for Nanofluid Flooding Monitoring. Sensors 2020, 20, 1014.

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