TY - JOUR
AU - Yahya, Noorhana
AB - Abstract The need to recover high viscosity heavy oil from the residual phase of reservoirs has raised interest in the use of electromagnetics (EM) for enhanced oil recovery. However, the transformation of EM wave properties must be taken into consideration with respect to the dynamic interaction between fluid and solid phases. Consequently, this study discretises EM wave interaction with heterogeneous porous media (sandstones) under different fluid saturations (oil and water) to aid the monitoring of fluid mobility and activation of magnetic nanofluid in the reservoir. To achieve this aim, this study defined the various EM responses and signatures for brine and oil saturation and fluid saturation levels. A Nanofluid Electromagnetic Injection System (NES) was deployed for a fluid injection/core-flooding experiment. Inductance, resistance and capacitance (LRC) were recorded as the different fluids were injected into a 1.0-m long Berea core, starting from brine imbibition to oil saturation, brine flooding and eventually magnetite nanofluid flooding. The fluid mobility was monitored using a fibre Bragg grating sensor. The experimental measurements of the relative permittivity of the Berea sandstone core (with embedded detectors) saturated with brine, oil and magnetite nanofluid were given in the frequency band of 200 kHz. The behaviour of relative permittivity and attenuation of the EM wave was observed to be convolutedly dependent on the sandstone saturation history. The fibre Bragg Grating (FBG) sensor was able to detect the interaction of the Fe3O4 nanofluid with the magnetic field, which underpins the fluid mobility fundamentals that resulted in an anomalous response. enhanced oil recovery, nanoparticles, electromagnetics, fibre Bragg grating sensor 1. Introduction The recovery of high viscosity heavy oil from the residual phase of reservoirs has garnered interest in the use of nanofluids activated by electromagnetics (EM) for enhanced oil recovery (Lapina & Bobrov 2016). To optimise the implementation of enhanced oil recovery (EOR) in marginal and brown fields, EM assisted nanofluids have been seriously considered. Nanoparticles are selected for improved oil recovery because of their physicochemical properties that allow them to reduce interfacial tension, modify wettability to water wet and reduce oil viscosity (emulsification) (Fletcher 2010) via phonon interactions. The introduction of nanoparticles in the reservoir lowers the interfacial tension between a water/wet system and crude oil by initiating an emulsion phase, as well as concurrently increasing the viscosity of the aqueous phase (Fernandez-Toledano et al. 2006; Ali et al. 2020). The phenomena play a vital role in displacing the oil from the pore. Suleimanov et al. (2011) also reported the reduction of surface tension by over 69% with the addition of nanoparticles to the aqueous phase. In addition, nanoparticles can convert fluid flow from Newtonian into non-Newtonian. In a nutshell, nanoparticles can enhance oil recovery in both heterogeneous and homogeneous pore media by improving oil mobility in the reservoir (Rodriguez et al. 2009). However, nanoparticles are plagued by instability, high settling rate in dispersive fluids (aggregation) and high retentivity in pore spaces. Since nanofluid only follows the fluid flow path in porous media, the residual oil trapped in hard-to-reach pore channels such as tiny pore throats and fingering geometries will not be affected. These issues can be resolved by modifying the balance of van der Waals attraction and electrical repulsive forces between the nanoparticles (Fernandez-Tolenado et al. 2006). To ensure this balance by creating Brownian motion, magnon (EM) forces are introduced in nanofluid injection. The EM force can influence the distribution of nanoparticles throughout the porous media. Hence, the effect of EM on oil recovery has to be studied. To determine the success of this approach, the transformation of EM wave properties must be taken into consideration with respect to the dynamic interaction between fluids and bulk sandstone material. Consequently, this study discretises EM wave interaction with heterogeneous porous media (sandstones) under different fluid saturations (oil, brine and nanofluid) to aid the monitoring of fluid mobility and activation of magnetic nanofluid in the reservoir. The phase transformation of wave amplitudes can accurately describe subsurface reservoir response to fluid injection (brine, nanofluid) during recovery ( TenCate et al. 1996). These variations can stem from micro-inhomogeneities derived from salinity changes, fluid mixing, nanoparticle infiltration, adsorption and retention in sandstone pores. The dispersion and attenuation of EM wave distribution in the saturated sandstones explains the recovery mechanism of in situ injection of magnetic NPs in the reservoir (photon). A nanofluid injection system was designed and constructed to integrate a functional nanofluid injection core-flood system with EM and fibre Bragg grating (FBG) sensors. Inductance, resistance and capacitance (LRC) were recorded as the different fluids were injected into a 1.0 m long Berea core, starting from brine imbibition to oil saturation, brine flooding and eventually magnetite nanofluid flooding. FBG technology was used for sensing and monitoring of oil mobility. Despite its high expense and sensitivity to fibre bending, FBG sensing is often considered and widely used because of its simple demodulation, high multiplexing, water and corrosion resistance, and use in both localised and quasi-distributed networks (Ferdinand et al. 1997; Majumder et al. 2008). EM wave variations were determined for dry sandstones, brine, oil and nanofluid saturated core. Amplitude change in the propagation of EM wave, reflected by changes in resistance and capacitance, is indicative of EM interaction with the reservoir sandstone (magnon). 2. Materials and methods 2.1. Core flooding The measurements of EM wave propagation were performed using nearly homogeneous but anisotropic cores of Berea sandstone. The Berea sandstone core used for the experiments had a length if 1 m and diameter of 10 cm. The petrophysical properties of the Berea sandstone were characterised using mercury microporosimetry. Using the plot of cumulative pore volume vs. pore diameter (nm) obtained from the MIP data (figure 1), the measured porosity of the Berea sandstone was 28.17%, with an average pore diameter of 13.5 μm, median pore diameter of 24.1 μm and modal pore diameter of 23.9 μm. The plot of pore size distribution shows a nearly variable pore distribution. The cumulative pore volume indicates micropores were the dominant pore type in the core, with a relatively lower presence of nanopores. The sandstone core dimensions are presented in Table 1. Figure 1. Open in new tabDownload slide Cumulative pore volume vs. pore diameter (nm) of the Berea sandstone showing micropores are the dominant pore type. Table 1. Core dimensions and average petrophysical properties at initial condition Length of core . Diameter of core . Porosity . Permeability . Volume of core . Pore volume . 91 cm 10 cm 28% 150–350 mD 7147 cm3 1572 cm3 Length of core . Diameter of core . Porosity . Permeability . Volume of core . Pore volume . 91 cm 10 cm 28% 150–350 mD 7147 cm3 1572 cm3 Open in new tab Table 1. Core dimensions and average petrophysical properties at initial condition Length of core . Diameter of core . Porosity . Permeability . Volume of core . Pore volume . 91 cm 10 cm 28% 150–350 mD 7147 cm3 1572 cm3 Length of core . Diameter of core . Porosity . Permeability . Volume of core . Pore volume . 91 cm 10 cm 28% 150–350 mD 7147 cm3 1572 cm3 Open in new tab Detectors were placed within small bore holes inside the sandstone, and fixed in place using epoxy resin. The holes were drilled into the Berea sandstone at 90° angles at various points along the core axis. A core-flooding system (Nanofluid Electromagnetic Injection System (NES)) was deployed to determine changes in electrical properties and saturation levels as fluid was injected into the core. The resistance (R) and capacitance (C) values were measured for different stages of core saturation in the frequency band of 200 kHz using the Tonghul TH 2830 LCR-meter. The electronics coupled to the source and receivers are illustrated in figure 2. Figure 3 shows the NES equipment. An Analogic 2020 arbitrary function generator was the signal source. The selection of source frequencies was dependent on the length of the sandstone. Figure 2. Open in new tabDownload slide Schematic diagram of (a) LCR measurement and (b) FBG setup of the Berea sandstone. Figure 3. Open in new tabDownload slide Nanofluid electromagnetics Injection System (NES) domiciled at the Institute of Hydrocarbon Recovery (IHR), PETRONAS. The core was first saturated with 11 000 ppm brine to create imbibition. Brine with a salinity of 11 000 ppm was prepared (by dissolving NaCl in de-ionised water) to reflect the concentration of infiltrated and connate water in an offshore sandstone reservoir. Afterwards, oil was injected into the core at a rate of 1 ml/min until no more brine was produced in the collection flask to develop the residual phase of hydrocarbon. The crude oil was obtained from Angsi Oilfield, Malaysia. Crude oil has a density of 0.8124 g cm−3 at 15°C, viscosities of 7.714 and 2.878  centistokes at 40 and 70°C, respectively, and API gravity of 42.6. At this stage the irreducible water saturation was attained. Afterwards, 11 000 ppm brine was injected as secondary recovery at the rate of 1 ml min−1. The volumetric ratio of oil and water was set at 40 : 60. Finally, 0.5 wt% of Fe3O4 nanofluid was injected as EOR process at 1 ml min−1 until no more oil was produced. During injection of each fluid, resistance and capacitance were recorded. The core-flooding experiment was carried out at ambient temperature. 2.2. Fibre Bragg grating (FBG) for fluid flow monitoring There was no system for detecting or sensing the effect of the EM activated nanoparticles on oil mobility. Hence, we developed a new sensing device to detect fluid mobility. The main goal was to produce a novel optical fibre sensing system for detection of oil movement. FBG is a periodic perturbation of the refractive index along the fibre length that is formed by exposure of the core to an intense optical interference pattern. The periodic pattern acts as a filter, because interference reflects some of the incident optical field. To increase sensitivity of FBG, the fibre is unclad at the grating part and a magnetic nanofluid, such as Fe3O4, is then coated on this unclad part. The interaction of the magnetic nanofluid with the external magnetic field will enhance the performance of FBG for EM and fluid flow monitoring. Figure 4 shows the schematic of the FBG mechanism. Figure 4. Open in new tabDownload slide Schematic of the FBG mechanism. 3. Results and discussion 3.1. Electromagnetic response The photon properties (resistance, capacitance and inductance) were measured from the onset of fluid injection into the sandstone core. For all phases of saturation, the inductance remained constant at 0.02 mH. The entire core-flooding process took about 50 hours, with resistance and capacitance values measured from the dry sandstone core to brine injection (to create imbibition), oil injection and nanofluid (Fe3O4) injection. Before brine incursion into the dry sandstone core, the resistance values varied between 250 000 and 500 000 Ω, while the capacitance value undulated from approximately −8000 to 250 000 Pf, as shown in figure 5a and 5b. As observed (figure 5a), the resistance dropped as brine was injected (for imbibition) into the initially dry core, but sharply increased/rebounded as oil was injected, then decreased as brine was injected for the first recovery. The resistance further decreased as nanofluid was injected into the saturated core for the secondary recovery. Similarly, the capacitance values show a marked increase during oil injection, as shown in figure 5b. These signatures are discretised to elaborate their relationship with differential fluid saturation. Figure 5. Open in new tabDownload slide Overall spectra of (a) resistance and (b) capacitance responses to the brine, oil and nanofluid injections in sandstone. 3.1.1. Brine injection Figure 6a and 6b illustrates the electrical resistance and capacitance responses to the dry sandstone for about 13 hours. The resistance fluctuates and oscillated between 24 000 and 30 000 Ω to create a harmonic motion, which is discernible in the close up image (figure 6c), while the capacitance remains constant at 520 pF until it steeply transforms (figure 6d). Figure 6. Open in new tabDownload slide The resistance (a) and capacitance (b) responses to the dry sandstone core and onset of brine saturation, resistance (c) and capacitance (d) responses to the brine injection in the sandstone core. As brine was injected into the dry core to achieve imbibition there, the amplitude of the propagated wave began to change, indicating change in media. After over 12 hours of continuous injection at a rate of 1 ml min−1, the initially harmonic motion became distorted, as illustrated in figure 6c. This anomaly was observed for about 3 hours, showing a drop in electrical resistance as compared to the dry core, while the capacitance oscillated between 5000 and 20 000 pF, as shown in figure 6d. Five hours after brine injection, the resistance value showed a harmonic behaviour, fluctuating around 20 000 Ω. The resistance value is reciprocally proportional to the conductivity value. Therefore, the decline in resistivity during the brine injection was due to the high electrical conductivity of the brine (i.e. 10 S m−1). 3.1.2. Oil injection With the injection of oil after brine saturation, the electrical resistance increased to mostly between 40 000 and 50 000 Ω, indicating rise in impedance due to the non-conductive nature of the non-polar fluid (oil). Figure 7c and d represent the resistance and capacitance responses to the continuous oil injection process, at the flow rate of 1 ml min−1. The resistance value remained unchanged during the first 6 hours of oil injection. However, after the 6 hours, the resistance responded to the environmental changes, showing a gradual increase from 27 000 Ω to a peak value of 800 000 Ω (Figure 5a). However, after 16 hours the harmonic peaks remained almost constant, at about 400 000 Ω. This increase is due to the fact that electrical resistivity of the oil is 10 to 50 times greater than that of brine. The response of the capacitive effect to the oil injection is clearly illustrated in figure 7d, where, the capacitance is unchanged at a peak of 10 000 pF, during the first 6 hours of oil injection. After 8 hours of oil injection, the wiggles of harmonic capacitance drop considerably to 7000 pF. This decline continued until the 15th hour at a capacitance of 6000 pF, and remained almost constant until oil saturation was completed. The dielectric constant of oil is 20 times less than that of the brine, thus the abrupt decline in capacitance during oil injection is expected. Figure 7. Open in new tabDownload slide (a) Resistance and (b) capacitance responses of oil injection in sandstone core, (c) resistance and (d) capacitance responses of brine injection for recovery. 3.1.3. Primary recovery via brine injection Subsequently, after attaining irreducible water saturation, the first recovery was performed via brine injection. Resistance and capacitance responses during this process are given in figure 7. As represented in figure 7a, for the first 7 hours of oil recovery via brine injection, the resistance was almost constant, with values ranging from 400 000 to 500 000 Ω. Seven hours after brine injection, the resistance value dropped sharply to about 125 000 Ω. A second significant drop occurred after 12 hours to approximately 45 000 Ω. The decrease in resistance during the recovery stage clearly indicates the change in environment from resistive oil saturation to a more conductive mixture of brine and oil. Figure 6b presents the capacitance effect in the first recovery. As anticipated, the harmonic motion of capacitance was unwavered until the brine reached the capacitance plates. Twelve hours after brine injection, the peak capacitance response increased gradually from 10 000 to 22 500 pF, and then remained constant until the end of the injection. As mentioned previously, the oil with dielectric constant of four was being replaced with saline water with a dielectric constant of 80. Therefore, the proportional relation of dielectric constant with capacitance accounts for the increment in capacitance value. Figure 7c indicates the capacitance of the core during 24 hours of brine injection. The capacitance remained approximately between 510 and 530 pF during the first 12 hours of brine injection (figure 7d). This is due to the positioning of the capacitor plates on the Berea sandstone (see figure 1). The capacitance value is proportional to the dielectric constant or electric permittivity (ε). Thus, as illustrated in figure 7c, the capacitance value was affected by the brine injection when brine (dielectric constant of 80) approached the vicinity of the capacitor plates, showing a very sharp increment. However, the dielectric constant of the dry core is about one. 3.1.4. Tertiary recovery via magnetite (Fe3O4) nanofluid injection For secondary recovery, magnetite (Fe3O4) nanofluid was injected after brine intrusion. Figure 8a shows a further dip in resistance during nanofluid injection. The drastic drop in resistance with the introduction of Fe3O4 nanofluid indicates higher magnetic permeability caused by the high polarity of Fe3+. The polarisation effect created the random movement of the nanofluid to interact with the immobile oil. The graph (figure 8b) shows a slight increase in capacitance with the introduction of EM. The presence of Fe3O4 in porous media increases the electric permittivity (Bobrov et al. 2015). The increasing of capacitance is due to the eddy current. Figure 8. Open in new tabDownload slide (a) Resistance and (b) capacitance responses of a sandstone core saturated with brine, Fe3O4 nanofluid and oil during nanofluid injection. 3.2. Oil recovery Results of core flood experiments are presented here. The sleeve or confining pressure within the core varied between 40 and 60 bar. The initial imbibition process was initiated, which involved the injection of brine at constant rate of 1 ml min−1. For two-phase flow, the drainage process was started by injecting oil at a rate of 1 ml min−1 until no more brine was produced, i.e. irreducible water saturation. The first recovery involved brine flooding. Afterwards, the injection continued, at a constant rate of 1 ml min−1, of magnetite nanofluid as the tertiary recovery mode. The core flood experiments were performed on two different cores (with similar petrophysical properties), with and without EM. Oil recovery by magnetite nanofluid increased with the introduction of EM. The recovery factor (displacement efficiency) for nanofluid recovery under (with and without EM) was calculated from equation (1): $$\begin{equation}\left[ {1 - \frac{{{\rm{Sor}}2}}{{{\rm{Sor}}1}}} \right] \times 100,\end{equation}$$(1) where Sor1 indicates the residual oil in place (ROIP) after brine injection and Sor2 denotes the original oil in place (OOIP). As shown in Table 2, the displacement efficiency drastically increased under EM from approximately 38 to 61%. This indicates improved oil mobility and recovery as EM interacted with the nanofluid. The improved oil recovery can be attributed to increased mobility due to lowered resistance with the introduction of EM. Thus, tertiary recovery using magnetite nanofluid flooding after secondary recovery is an effective recovery scenario. Table 2. EOR scenarios showing different saturation and recovery volumes (with and without EM) Nanoparticles . Original oil in place (OOIP) . Volume of recovered oil after brine injection (Q2) . Residual oil in place (ROIP) after brine Injection . Volume of recovered oil after nanofluid (NF) injection (Q3) . Residual oil in place (ROIPb) after nanofluid (NF) injection . Displacement efficiency (recovery factor) . Fe3O4 without EM 1171 ml 536 ml (46%) 636 (54%) 242 ml 394 ml 38.11% Fe3O4 with EM 1169 ml 522 ml (41%) 647 (59%) 392 ml 255 ml 60.57% Nanoparticles . Original oil in place (OOIP) . Volume of recovered oil after brine injection (Q2) . Residual oil in place (ROIP) after brine Injection . Volume of recovered oil after nanofluid (NF) injection (Q3) . Residual oil in place (ROIPb) after nanofluid (NF) injection . Displacement efficiency (recovery factor) . Fe3O4 without EM 1171 ml 536 ml (46%) 636 (54%) 242 ml 394 ml 38.11% Fe3O4 with EM 1169 ml 522 ml (41%) 647 (59%) 392 ml 255 ml 60.57% Open in new tab Table 2. EOR scenarios showing different saturation and recovery volumes (with and without EM) Nanoparticles . Original oil in place (OOIP) . Volume of recovered oil after brine injection (Q2) . Residual oil in place (ROIP) after brine Injection . Volume of recovered oil after nanofluid (NF) injection (Q3) . Residual oil in place (ROIPb) after nanofluid (NF) injection . Displacement efficiency (recovery factor) . Fe3O4 without EM 1171 ml 536 ml (46%) 636 (54%) 242 ml 394 ml 38.11% Fe3O4 with EM 1169 ml 522 ml (41%) 647 (59%) 392 ml 255 ml 60.57% Nanoparticles . Original oil in place (OOIP) . Volume of recovered oil after brine injection (Q2) . Residual oil in place (ROIP) after brine Injection . Volume of recovered oil after nanofluid (NF) injection (Q3) . Residual oil in place (ROIPb) after nanofluid (NF) injection . Displacement efficiency (recovery factor) . Fe3O4 without EM 1171 ml 536 ml (46%) 636 (54%) 242 ml 394 ml 38.11% Fe3O4 with EM 1169 ml 522 ml (41%) 647 (59%) 392 ml 255 ml 60.57% Open in new tab 3.3. Magnetic permeability (μ) and electrical permittivity (ε) The impact of EM on oil recovery is analysed based on the phenomenon of magnetic permeability and electrical permittivity (ε). Magnetic permeability (μ) is the relative increase or decrease in the resultant magnetic field inside a material compared with the external magnetising field in which the given material is located. It infers the ease with which the externally applied EM field can create a higher magnetic force. Electric permittivity (ε) is the ability of the sandstone to store electrical potential energy under the influence of an electric field. Electric permittivity is a measure of how much molecules resist an external electric field. Higher electric permittivity indicates better polarisation. The μ and ε values were determined for each stage of saturation, with and without the EM field. Table 3 indicates a general increase in μ and ε after the introduction of an EM field. These parameters are higher when Fe3O4 nanofluid is injected into the sandstone core, indicating an interaction. The changes in ε of the dry core to a higher value with the addition of brine can be attributed to increased capacitance (due to the polarity of brine). This change becomes more apparent with the introduction of EM, as shown in Table 2. The drop in ε with oil injection possibly results from decrease in capacitance due to the non-polar nature of oil. Nonetheless, ε rebounded after the expulsion of oil during brine injection of primary recovery. The further increase in ε with Fe3O4 nanofluid injection indicates higher polarsation as the nanofluid interacts with EM. Table 3. Magnetic permeability (μ) and electrical permittivity (ε) at different saturation conditions . Without EM . With EM . Δ% . Saturation levels of sandstone core . μ . ε . μ . ε . μ . ε . Dry core 0.0031 0.63 0.0061 0.74 96.77 17.46 Brine saturated 0.2832 4.37 0.4176 7.10 47.46 62.47 Oil saturated after reaching irreducible water saturation 0.0081 2.55 0.1222 3.80 14.26 49.02 Oil and brine saturated after first recovery with brine 0.2343 3.19 0.3514 4.81 49.97 50.78 Oil, brine and Fe3O4 nanofluid saturated after tertiary recovery with nanofluid 0.3107 7.10 0.5297 9.58 70.49 34.93 . Without EM . With EM . Δ% . Saturation levels of sandstone core . μ . ε . μ . ε . μ . ε . Dry core 0.0031 0.63 0.0061 0.74 96.77 17.46 Brine saturated 0.2832 4.37 0.4176 7.10 47.46 62.47 Oil saturated after reaching irreducible water saturation 0.0081 2.55 0.1222 3.80 14.26 49.02 Oil and brine saturated after first recovery with brine 0.2343 3.19 0.3514 4.81 49.97 50.78 Oil, brine and Fe3O4 nanofluid saturated after tertiary recovery with nanofluid 0.3107 7.10 0.5297 9.58 70.49 34.93 Open in new tab Table 3. Magnetic permeability (μ) and electrical permittivity (ε) at different saturation conditions . Without EM . With EM . Δ% . Saturation levels of sandstone core . μ . ε . μ . ε . μ . ε . Dry core 0.0031 0.63 0.0061 0.74 96.77 17.46 Brine saturated 0.2832 4.37 0.4176 7.10 47.46 62.47 Oil saturated after reaching irreducible water saturation 0.0081 2.55 0.1222 3.80 14.26 49.02 Oil and brine saturated after first recovery with brine 0.2343 3.19 0.3514 4.81 49.97 50.78 Oil, brine and Fe3O4 nanofluid saturated after tertiary recovery with nanofluid 0.3107 7.10 0.5297 9.58 70.49 34.93 . Without EM . With EM . Δ% . Saturation levels of sandstone core . μ . ε . μ . ε . μ . ε . Dry core 0.0031 0.63 0.0061 0.74 96.77 17.46 Brine saturated 0.2832 4.37 0.4176 7.10 47.46 62.47 Oil saturated after reaching irreducible water saturation 0.0081 2.55 0.1222 3.80 14.26 49.02 Oil and brine saturated after first recovery with brine 0.2343 3.19 0.3514 4.81 49.97 50.78 Oil, brine and Fe3O4 nanofluid saturated after tertiary recovery with nanofluid 0.3107 7.10 0.5297 9.58 70.49 34.93 Open in new tab The gradual decrease and increase in resistance as brine and oil are injected indicates concomitant changes in magnetic permeability and resistivity. The increase in magnetic permeability indicates greater conductivity for magnetic lines of force. These changes in resistance and capacitance can be attributed to the interaction between the brine and EM as well as magnetite nanofluid and EM. The introduction of EM field increases the magnetisation and polarisation of the reservoir fluids. The polarisation effect creates a random movement (Brownian motion) in the nanofluid, which allows it to unlock the immobile oil that in turn accounts for the improved oil recovery after nanofluid injection. 3.4. FBG response to nanofluid mobility To understand EM activation of nanoparticles (magnon effect), FBG responses of nanofluid mobility were determined. Five different nanofluids were selected for the nanofluid flooding process. Fe3O4 was selected due to its strong magnetic properties, and ZnO, graphene, carbon nanostructure and CuO were selected as dielectric nanomaterials. Since the propagated energy is a magnetic wave and the coating material of FBG is Fe3O4, it is expected that FBG would respond to a magnetic nanofluid. Figure 9 represents the FBG wavelength shift during the nanofluid flooding for the selected magnetic and dielectric nanofluids. FBG responded to Fe3O4 magnetic nanofluid, showing a wavelength shift of 0.03 and 0.05 nm, after 18 and 43 hours of nanofluid flooding, respectively. This is due to interaction of the Fe3O4 magnetic nanofluid with the EM field, hence the refractive index of magnetic fluid is considered to be dependent on the EM field (Meltz et al. 1989, 1991; Sun et al. 2015, 2016). Thus, certain deductions can be made. The behaviour of Fe3O4 nanoparticles in magnetic fluid depends on the externally applied EM field. In electromagnetic waves, the electric field is vertically polarised. Polarisation is a measurement of the electromagnetic field's alignment. The refractive index |$\eta $| is expressed in equation (2) as: $$\begin{equation}\eta {\rm{\ }} = \sqrt {{\varepsilon _r}} {\rm{\ }} = \sqrt {1 + \chi } {\rm{\ }},\end{equation}$$(2) where, |${\varepsilon _r}$| and |$\chi $| denote the dielectric constant and electric susceptibility, respectively. Thus, any change in refractive index or the grating period due to external measures will change the Bragg wavelength of the device and can be detected in either the reflected or transmitted spectrum of FBGs. This can be obtained as follows: $$\begin{equation}\Delta {\lambda _{Bragg}} = \Lambda {{\partial {n_{{\it{MF}}}}} \over {\partial {n_{eff}}}}\Delta {n_{eff}},\end{equation}$$(3) $$\begin{equation}{n_{eff}} = \sqrt {{\varepsilon _r}{\mu _r}}, \ \end{equation}$$(4) $$\begin{eqnarray}\frac{{\partial {n_{MF}}}}{{\partial H}} &=& \left( {{n_s} - {n_0}} \right)\ \bigg[ \left( { - \frac{{\alpha H}}{T}} \right)csc{h^2}\left( {\alpha \frac{{H - {H_c}}}{T}} \right)\nonumber\\ && - \alpha \frac{T}{{{{\left( {H - {H_c}} \right)}^2}}} \bigg].\end{eqnarray}$$(5) Figure 9. Open in new tabDownload slide FBG response to nanofluid flooding using magnetic and dielectric nanomaterials. Equations (3) and (4) show the relation of ΔλBragg to change in environment, while equation (5) indicates the change in refractive index with respect to changes in strength of magnetic field, at constant temperature, which results in changes in ΔλBragg. Δneff denotes the effective core index of refraction. |$\Lambda $| is the period of the index modulation, |$\varepsilon $|r and |$\mu $|r are relative permittivity and permeability of the magnetic field (MF), respectively, nMF (H, T) is refractive index of MF as a function of field strength (H) and temperature (T), Hc is the critical magnetic field strength, n0 is refractive index in a magnetic field less than Hc, ns is the refractive index of magnetic saturation and|$\ \alpha $| is the fitting coefficient. Equation (5) shows the relation of ΔλBragg to changes of MF and effective refractive indices in environment. 4. Conclusion Characteristic signatures of phase transformation in EM activated nanofluid injection for oil recovery were presented. A considerable decline in resistance with increasing saturation was observed, which indicated the ability of EM to reduce reservoir impedance, thus enabling fluid mobility. The electrical resistance of the sandstone changed with variable oil and brine saturation levels. It decreased with brine injection but increased during oil injection. EM emission affected the resistivity response. The resistance increased during nanofluid injection in the presence of EM, which confirms the interaction between EM and nanoparticles, since electrical resistivity is a frequency dependent parameter. The behaviour of magnetic permeability of an EM wave at frequencies of 200 kHz is convolutedly dependent on the saturation level of the saturating solution and saturation history. The FBG sensor was able to detect the interaction of fluid response to the EM flux. This underpins the fluid mobility fundamentals that resulted in better oil recovery. Acknowledgements The authors would also like to express their utmost gratitude to Universiti Teknologi PETRONAS, Malaysia for providing excellent research facilities. The authors also express their appreciation for the financial support provided by Yayasan Universiti Teknologi PETRONAS research grant (YUTP Cost Centre: 015LC0-149) Conflict of interest statement. The authors also express their appreciation for the financial support provided by Yayasan Universiti Teknologi PETRONAS research grant (YUTP Cost Centre: 015LC0-149). (i) All authors agree with the submission, (ii) the work has not been published elsewhere, either completely, in part, or in another form and (iii) the manuscript has not been submitted to another journal. References Ali A.M. , Yahya N., Qureshi S., 2020 . Interactions of ferro-nanoparticles (hematite and magnetite) with reservoir sandstone: implications for surface adsorption and interfacial tension reduction , Petroleum Science , 17 , 1037 – 1055 . Google Scholar Crossref Search ADS WorldCat Bobrov P.P. , Mironov V.L., Repin A.V., 2015 . Dielectric permittivity spectra of oil–water saturated sandy-clayey rocks of different mineralogical compositions and relaxation properties of water in these rocks , Russian Geology and Geophysics , 56 , 1065 – 1073 . Google Scholar Crossref Search ADS WorldCat Ferdinand P. , Magne S., Dewynter-Marty V., Martinez C., Rougeault S., Bugaud M., 1997 . Applications of Bragg grating sensors in Europe : 12th International Conference on Optical Fiber Sensors: Optical Society of America, Williamsburg, VA, USA , pp. 14 – 19 . Google Scholar Crossref Search ADS Google Preview WorldCat COPAC Fernandez-Toledano J.C. , Monacho-Jorda A., Martinez-lopez F., Hidaglo-Alvarez R., 2006 . Theory for interactions between particles in monolayer , in Colloidal Particles at Liquid Interfaces , pp. 303 – 301 , eds Binks B.P., Horozov T.S., Cambridge University Press . Google Scholar Crossref Search ADS Google Preview WorldCat COPAC Fletcher A.J.P. , 2010 . How EOR can be Transformed by Nanotechnology . SPE, Parr System Pty Ltd, and J.P. Davis, University of Bristol . Google Scholar Crossref Search ADS Google Preview WorldCat COPAC Lapina A.S. , Bobrov P.P., 2016 . Electromagnetic waves attenuation in the sandstones with grains of different size at imbibition and drying , Progress in Electromagnetics Research M , 45 , 9 – 16 . Google Scholar Crossref Search ADS WorldCat Majumder M. , Gangopadhyay T.K., Chakraborty A.K., Dasgupta K., Bhattacharya D.K., 2008 . Fibre Bragg gratings in structural health monitoring—present status and applications , Sensors and Actuators A: Physical , 147 , 150 – 164 . Google Scholar Crossref Search ADS WorldCat Meltz G. , Morey W.W., Dunphy J.R., 1991 . Fiber Bragg grating chemical sensor, in Proceedings of the SPIE Chemical, Biochemical, and Environmental Fiber Sensors III, Boston, MA, USA , 350 – 361 . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Meltz G. , Morey W.W., Glenn W.H., 1989 . Formation of Bragg gratings in optical fibers by a transverse holographic method , Optics Letters , 14 , 823 – 827 . Google Scholar Crossref Search ADS PubMed WorldCat Rodriguez E. , Roberts M.R., Yu H., Huh C., Bryant S.L., 2009 . Enhanced migration of surface-treated nanoparticles in sedimentary rocks , in Annual Technical Conference and Exhibition held in New Orleans, Louisiana, USA, 4–7 October 2009 . Google Scholar Crossref Search ADS Google Preview WorldCat COPAC Suleimanov B.A. , Ismailov F.S., Veliyev E.F., 2011 . Nanofluid for enhanced oil recovery , Journal of Petroleum Science and Engineering , 78 , 431 – 437 . Google Scholar Crossref Search ADS WorldCat Sun Y. , Li Q., Li X., Yang D., 2015 . Progress of real-time monitoring technology in oil and gas industry based on fiber Bragg grating sensing , Science and Technology Review , 33 , 84 – 91 . Google Scholar OpenURL Placeholder Text WorldCat Sun Y. , Li Q., Yang D., Fan C., Sun A., 2016 . Investigation of the dynamic strain responses of sandstone using multichannel fiber-optic sensor arrays , Engineering Geology , 213 , 1 – 10 . Google Scholar Crossref Search ADS WorldCat TenCate J.A. , Van Den Abeele K.E.A., Shankland T.J., Johnson P.A., 1996 . Laboratory study of linear and nonlinear elastic pulse propagation in sandstone , Journal of Acoustic Society of America , 100 , 1383 – 1391 . Google Scholar Crossref Search ADS WorldCat © The Author(s) 2020. Published by Oxford University Press on behalf of the Sinopec Geophysical Research Institute. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. © The Author(s) 2020. Published by Oxford University Press on behalf of the Sinopec Geophysical Research Institute.
TI - Photon-magnon response to fluid variability and saturation levels in sandstone reservoirs
JF - Journal of Geophysics and Engineering
DO - 10.1093/jge/gxaa064
DA - 2020-12-30
UR - https://www.deepdyve.com/lp/oxford-university-press/photon-magnon-response-to-fluid-variability-and-saturation-levels-in-uJSNT6BS2b
SP - 1065
EP - 1074
VL - 17
IS - 6
DP - DeepDyve
ER -