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Inversion Algorithm of Fiber Bragg Grating for Nanofluid Flooding Monitoring.

ABSTRACT: 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.

SUBMITTER: Yahya N

PROVIDER: S-EPMC7070743 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Inversion Algorithm of Fiber Bragg Grating for Nanofluid Flooding Monitoring.

Yahya Noorhana N Nyuk Chai Mui CM Ismail Ahmad Fauzi AF Hussain Nazabat N Rostami Amir A Ismail Atef A Ganeson Menaka M Ali Abdullah Musa AM

Sensors (Basel, Switzerland) 20200213 4

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 Fe<sub>3</sub>O<sub>4</sub> injection was 75% higher than that of dielectric ...[more]

PMID: 32069956

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