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Low salinity waterflooding (LSF) has been proposed to improve oil recovery, with major projects in progress worldwide. There is however no consensus o...
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A Magnetic Resonance Study of Low Salinity Waterflooding for Enhanced Oil Recovery Ming Li,†,‡ Sarah Vashaee,† Laura Romero-Zerón,‡ Florin Marica,† and Bruce J. Balcom*,† †

MRI Centre, Department of Physics, and ‡Department of Chemical Engineering, University of New Brunswick, P.O. Box 4400, Fredericton, New Brunswick E3B 5A3, Canada ABSTRACT: Low salinity waterflooding (LSF) has been proposed to improve oil recovery, with major projects in progress worldwide. There is however no consensus on the mechanisms of LSF for enhanced oil recovery (EOR). Wettability change is the most widely accepted mechanism. In this work, magnetic resonance (MR) and magnetic resonance imaging (MRI) were employed to monitor oil displacement processes during model laboratory scale LSF experiments. The MR and MRI measurements permit evaluation of putative LSF mechanisms. Two clay-coated sand packs, one with nonswelling kaolinite, the other with swelling montmorillonite, were prepared as model porous media for LSF. The interactions between pore fluids (oil and water) and the clay-coated pore surfaces were evaluated with relaxation time measurements. A MRI methodology, spin echo single point imaging (SE-SPI), was employed to spatially resolve the T2 distribution along the sand pack. The oil saturation profiles were determined from SE-SPI measurements. A new differential relaxation time distribution method is proposed in this work for oil saturation estimation. The pore fluid self-diffusion coefficients were measured. The mechanism of wettability change for LSF is suggested on the basis of the oil diffusion coefficient variation with LSF. The similarities and differences between the kaolinite and montmorillonite behaviors are discussed. This work demonstrates that MR and MRI are robust tools to monitor oil displacement processes, with the potential to reveal the mechanisms of LSF and other procedures for enhanced oil recovery. mechanism.19,22 Conventional methods for wettability measurement, such as the Amott method and the USBM method,23 are time-consuming and disturb the sample in the measuring process. Magnetic resonance (MR), as a noninvasive method, was first proposed by Brown et al.24 for determining rock core wettability. Zhang et al.25 used the MR T1 relaxation time to interpret wettability alteration in different oil and sandstone systems. They found that Bentheimer and Berea rocks were water-wet when saturated with refined oil; however, the rock surface displayed a mixed wettability when saturated and aged with crude oil. Chen et al.26 employed the MR T2 relaxation time to investigate pore occupancy and wettability modification during LSF. Li et al.27 employed a normalized T2 log mean ratio to study polymer flooding EOR in water-wet and oil-wet core plugs. Seland et al.28 utilized bulk diffusion-T2 measurements to investigate different wettabilities. Seland et al.28 found that the oil diffusion coefficient was lower in an oil-wet glass bead system as compared to a water-wet sample. Thomas et al.29 observed that liquid diffusion was impeded near a more-wetting surface but enhanced near a less-wetting surface. In the current work, MR T1 and T2 measurements were employed to determine the oil saturation and to reveal the interactions between pore fluids (oil and water) and the claycoated pore surface at high salinity waterflooding (HSF) and LSF stages. A MRI T2 mapping methodology, SE-SPI,30 was employed to spatially resolve the T2 distribution. The oil saturation profiles were estimated on the basis of SE-SPI MRI

1. INTRODUCTION Low salinity waterflooding (LSF) has been known to enhance oil recovery in some scenarios, as compared to high salinity waterflooding, since the 1950s.1,2 Some laboratory studies and field applications have reported negative results or negligible incremental oil recovery.3,4 This is a significant barrier to more widespread application of LSF, despite its potential.5−9 In addition, contradictory evidence exists for all proposed LSF mechanisms except for the mineral dissolution mechanism.10 More studies are required to determine the mechanisms of LSF for enhanced oil recovery (EOR). This research employs magnetic resonance (MR) and magnetic resonance imaging (MRI) measurements to monitor LSF oil displacement processes to better understand the processes of LSF for enhanced oil recovery. MRI has permitted measurements of fluid type and fluid viscosity, rock wettability, permeability, and pore size distribution in petroleum studies.11,12 MRI has been employed to quantitatively monitor enhanced oil recovery processes with results that are in agreement with traditional material balance methods.13,14 Rapid MRI methodologies have been employed to monitor the three-dimensional oil saturation distribution during flooding.15−17 MRI T2 mapping measurements have been undertaken to monitor fines migration in Berea core plugs during deionized water injection.18 While there is no consensus on the mechanism of LSF for enhanced oil recovery, numerous mechanisms have been proposed. These include multicomponent ion exchange, wettability alteration, fines migration, pH increment, double layer expansion, pressure osmosis, and mineral dissolution.19,20 Wettability alteration, usually increased water wetness, during LSF, is the most frequently suggested mechanism.21 Wettability alternation toward a less water-wet state is also a proposed © XXXX American Chemical Society

Received: July 24, 2017 Revised: September 1, 2017 Published: September 5, 2017 A

DOI: 10.1021/acs.energyfuels.7b02166 Energy Fuels XXXX, XXX, XXX−XXX

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more MR spin echoes with different magnetization recovery times. The spin echo signals or the T2 distributions are subtracted to yield a differential result, which is further processed to estimate fluid saturation.11 Interpretation of the DSM however requires that the T1 distributions of water and oil do not overlap.38 This limits the application of DSM in the current work as the T1 distribution of water in smaller pores and the T1 distribution of crude oil overlap in the sand packs employed. Therefore, in this work, a new method based on the differential relaxation time distributions is proposed to estimate oil and water saturations in the porous media. The conditions, assumptions, and calculations for this method are detailed below. The area under the T2 distribution curve is proportional to the associated oil and water saturations in the sample.11,13 The T2 distribution can be expressed as a linear combination of the individual T2 distributions of various pore fluids such as bound water, mobile water, and oil.39 In the current work, it was assumed that T2 components longer than 100 ms in the sand pack were due to water, not oil. In this study, the bulk crude oil T2 distribution ranged from 0.1 ms, with a peak value at 35 ms, to a maximum of 100 ms (Figure 1). It was also assumed that the oil injection and aging process

measurements with a new differential relaxation time distribution method. A MR self-diffusion measurement was employed to evaluate wettability variation during LSF. LSF improves oil recovery for specific rock/oil/brine systems. A kaolinite-coated sand pack and a montmorillonitecoated sand pack were employed as model porous media in the current work. Kaolinite can change the pore surface to more oil-wet.31,32 Montmorillonite is less oil-wet but has much higher cation exchange capacity as compared to kaolinite.31 A kaolinite-coated sand pack model32 and a montmorillonitedeposited glass substrate model33 have shown positive LSF effects in the literature. In this work, the different behaviors of these two clays with LSF in the sand packs were examined with MR and MRI measurements.

2. MATERIALS AND METHODS 2.1. Fluids. A crude oil (Wainwright oil field, Husky Energy, Canada) with a viscosity of 87 mPa s and a density of 0.91 g/cm3 at 25 °C was employed. A 1.5 wt % NaCl brine was employed to prepare two clay-coated sand packs. A high salinity brine (HSB)34 and three low salinity brines (LSB) were employed for HSF and LSF (LSF1, LSF2, and LSF3), respectively. Table 1 shows the brine compositions.

Table 1. Brine Composition (wt %) NaCl CaCl2 MgCl2 Na2SO4 a

HSF

LSF1

LSF2

2.899 0.211 0.067 0.690

0.290 0.021 0.007 0.069

0.387

LSF3a

Deionized water for LSF3.

2.2. MR and MRI Methodologies. Five MR and MRI methodologies were employed to determine the water and oil saturation and the fluid behavior at the pore scale during HSF and LSF. A Carr−Purcell−Meiboom−Gill (CPMG) method and an inversion recovery method were utilized to determine the bulk T2 relaxation time and bulk T1 relaxation time of oil and water in the sand pack, respectively. The bulk oil saturation and water saturation were estimated with a proposed method outlined in section 2.3 based on relaxation time distributions. A bulk two-dimensional (2D) T1−T2 method was employed to distinguish oil and water in the sand pack. 2D MR techniques generally improve the separation of the different 1H populations based on two contrasts instead of one.35,36 A T2 mapping SE-SPI method30 was employed to acquire spatially resolved T2 distributions along the sand pack. The oil saturation profile along the sand pack was estimated on the basis of the SE-SPI measurements with the new method described in section 2.3. A stimulated echo pulsed field gradient (STE-PFG) diffusion measurement37 was utilized to measure the oil and water self-diffusion coefficients in the sand packs. The diffusion of a pore fluid is affected by the pore wettability.28,29,31 In the current work, variation of the oil diffusion coefficient may be attributed to wettability alterations with LSF. The WinDXP software program (Oxford Instruments, Oxfordshire, UK) was employed to determine the T1 distribution and the T2 distribution. One-dimensional Fast Laplace Inversion software (Schlumberger-Doll Research, Cambridge, MA) was utilized to determine the diffusion coefficient distribution. Two-dimensional Fast Laplace Inversion software (Schlumberger-Doll Research, Cambridge, MA) was employed for 2D T1−T2 distribution determination. 2.3. Determination of Oil and Water Saturation with a New Differential Relaxation Time Distribution Method. The Differential Spectrum Method (DSM) has been employed in the literature to characterize fluids in porous media.11 The DSM measures two or

Figure 1. Bulk crude oil T1 (a) and T2 (b) distributions. The T1 distribution ranged from 0.1 ms to a maximum value of 300 ms with a peak value of 57 ms. The T2 distribution ranged from 0.1 ms, with a peak value at 35 ms, to a maximum of 100 ms. will change the interaction between pore surface and fluid (oil and water) in larger pores, but not in smaller pores. Kaolinite is waterwet,40,41 but it shows a high affinity for crude oil and can change the pore surface to more oil-wet when contacting crude oil.31,32,40,42,43 Montmorillonite is more water-wet than kaolinite.31 Figure 2 shows a schematic of the proposed differential T2 distribution method. The T2 distributions of 100% water (Sw = 1), and partially saturated water and oil (Sw and So) in the sand pack, are shown in Figure 2a. The vertical dashed line shows the longest T2 of the bulk crude oil, T2 longest, 100 ms. The area under the T2 distribution for a fully water saturated sample, Sw = 1, is denoted by A1 (b). The area A1 is proportional to the pore volume of the sand pack. The B

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1.5 wt % NaCl brine was prepared with deionized water.44 A 5 wt % clay suspension was prepared by adding clay powder to the stirred NaCl brine. The clay suspension was slowly injected into the sand pack in a Teflon holder. The sand pack holder was gently rotated to generate a homogeneous clay suspension in the sand pack. The sand pack was first dried at 60 °C with the two ends open. Air was then injected into the sand pack for 2 h for further drying. Additional air was injected, from the other end, for 1.5 h to generate a homogeneous clay distribution. To completely dry the sample, the sand pack (in the holder) was heated at 60 °C for 30 min and then dried under vacuum for 20 min. The heating and vacuum drying process was repeated five and six times until a constant weight was achieved for kaolinite-coated and montmorillonite-coated sand packs, respectively. The weight fractions of coated kaolinite and montmorillonite were 0.86 and 0.48 wt %, respectively, relative to the sand. The sand packs had a length of 5 cm, diameter of 2.5 cm, and porosity of 33% (kaolinite-coated) and 36% (montmorillonite-coated). 3.3. Experimental Procedure. High salinity brine (HSB, Table 1) was injected into the dried clay-coated sand pack at 0.5 mL/min to saturate the sample. No clay particles were observed in the effluent during HSB injection. The volume difference between the injected brine and the produced brine provided an estimate of the sand pack pore volume (PV). To establish initial oil saturation with irreducible water in the sand pack, crude oil was injected at a rate of 0.6 mL/min to displace brine. Injection continued until no further water production was observed. Additional oil was injected, from the other end, to ensure a homogeneous oil distribution. The brine and oil effluent was collected in graduated cylinders when injecting oil. The ratio of brine effluent volume to the sand pack pore volume was calculated as the initial oil saturation, Soi. The oil saturated sand pack was aged at 60 °C for 8 days and then transferred to the MRI instrument for MR and MRI monitoring of flooding experiments. The flooding experiments were undertaken at 25 °C. HSF was switched to LSF1 when oil production ceased. LSF2 and LSF3 followed LSF1. The waterflooding rate was 0.1 mL/min. More than 10 PV HSB and low salinity brine (LSB) was injected at each stage of waterflooding. CPMG, SE-SPI, inversion recovery T1, 2D T1−T2, and STE-PFG measurements were undertaken at different flooding stages to measure initial oil saturation before flooding, residual oil saturation after HSF, and residual oil saturation after each stage of LSF. Table 2 shows the MR and MRI measurement parameters.

Figure 2. Schematic of the differential relaxation distribution method to determine oil and water saturation. T2 distributions of 100% water (Sw = 1) and partial water and oil saturation (Sw and So) in the sand pack are shown. The vertical dashed line indicates the maximum value of the bulk crude oil T2 longest, 100 ms. The area under the T2 distribution of Sw = 1 is denoted by A1 (b). The overlapped area under the two T2 distribution curves, with T2 < 100 ms, is denoted by A2 (c). A2 is assumed to correspond to water in smaller pores and clay bound water. The area under the T2 distribution of Sw and So with T2 > 100 ms is denoted by A3 (d). A3 is attributed to water in larger pores. The water saturation (Sw) is estimated by Sw = (A2 + A3)/A1, and thus oil saturation is So = 1 − Sw.

common area under the two T2 distribution curves with T2 < 100 ms is denoted by A2 (c). A2 is assumed to correspond to water in smaller pores and clay bound water. It was assumed that oil injection will not change water in these environments. The area under the T2 distribution of Sw and So with T2 > 100 ms is denoted by A3 (d). This area is assigned to water in larger pores. The water saturation (Sw) in the sand pack is estimated by Sw = (A2 + A3)/A1, while the oil saturation is So = 1 − Sw. Because A1, A2, and A3 correspond solely to the water volume in the sample, the oil hydrogen index is not required for the proposed method. The same method can also be employed with T1 relaxation time measurements to estimate oil saturation. Once more, it was assumed in this work that T1 components longer than the bulk crude oil in the sand pack are due to water, not oil, because the bulk crude oil T1 distribution ranged from 0.1 ms to a maximum value of 300 ms with a peak value of 57 ms (Figure 1).

4. RESULTS Two-dimensional (2D) MR techniques usually improve the discrimination of different 1H populations because of two contrasts rather than one.35,36 A bulk 2D T1−T2 method was employed to distinguish oil and water in the sand packs. Figure 3 shows the bulk 2D T1−T2 spectra of oil and water in the two sand packs before and after HSF. For the kaolinitecoated sand pack, at initial oil saturation state (a), one component is observed at T1 = 70 ms and T2 = 36 ms. The peak is dominated by oil but is also affected by water in smaller pores as irreducible water saturation was Swi ≈ 0.13, determined by a volumetric method. Two components were observed in the T1−T2 spectrum after HSF (b). The longer component, T1 = 1046 ms and T2 = 666 ms, is associated with water in larger pores. The shorter component, T1 = 80 ms and T2 = 35 ms, with a lower signal amplitude, is attributed to residual oil but is also affected by water in smaller pores. Similar T1−T2 spectra were observed for the montmorillonite-coated sand pack in Figure 3c and d. Figure 4 shows the oil saturation in a Bentheimer core plug determined with the proposed differential relaxation time distribution method and the volumetric method. The new method provides oil saturation results consistent with the conventional volumetric measurements.

3. EXPERIMENTAL SECTION 3.1. Experimental Setup. The flooding apparatus includes a Dual 100-DX pump (Teledyne ISCO, NE) for oil and water injection and a homemade Teflon holder for holding the sand pack. MR and MRI measurements were undertaken on a 0.20 T Maran DRX permanent magnet spectrometer (Oxford Instruments, Oxfordshire, UK). The corresponding 1H resonance frequency was 8.54 MHz. A homemade solenoid RF probe with a 1.75 in. inside diameter was employed. The differential pressure across the core plug was monitored with an OMEGA DPG409 pressure transducer (Omegadyne Inc., Sunbury, OH). 3.2. Clay-Coated Sand Pack Preparation. The porous media employed were clay-coated sand packs, prepared following Lebedeva et al.32 and Song et al.44 with some modifications. S23-3 Ottawa sand (20−30 mesh, 0.841−0.595 mm) (Fisher Scientific, Fair Lawn, NJ) was employed. Two clays, kaolinite and montmorillonite (SigmaAldrich, St. Louis, MO), were employed. C

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Energy & Fuels Table 2. Magnetic Resonance Measurement Parameters SE-SPI 90° pulse length (μs) relaxation delay (s) number of averages first echo time (μs) echo time (μs) number of echoes field of view (cm) number of image pixels imaging time (min)

11.2 13 4 802 800 4096 9 64 69 CPMG

90° pulse length (μs) relaxation delay (s) number of averages echo time (μs) number of echoes Inversion Recovery T1 90° pulse length (μs) 180° pulse length (μs) relaxation delay (s) number of averages delay τ (ms) number of τ values

11.2 12 16 800 6656 11.2 22.4 12 4 0.7−9500 26

Figure 3. 2D T1−T2 spectrum of oil and water in the two sand packs before and after HSF. For the kaolinite-coated sand pack, one component is observed at T1 = 70 ms and T2 = 36 ms in the spectrum at the initial state (a), and two components were observed in the spectrum after HSF (b). Similar T1−T2 spectra were observed for the montmorillonite-coated sand pack in (c) and (d). 2D T1−T2 measurements cannot distinguish oil and water in smaller pores in the two sand packs, but clearly reveal the appearance of water in larger pores after HSF through a new peak at long T1−T2 lifetimes in each case.

STE-PFG 90° pulse length (μs) relaxation delay (s) number of averages gradient duration δ (ms) duration between gradients Δ (ms) gradient strength (gauss/cm) gradient steps

11.2 13 16 7 125 0−31 31

Figure 5 shows the SE-SPI estimated oil saturation profiles with the proposed differential T2 relaxation time distribution method in the two clay-coated sand packs before flooding, after HSF, and after a series of LSF. In Figure 5a for the kaolinitecoated sand pack, a homogeneous initial oil saturation profile was observed. The average initial oil saturation was 0.86, which was consistent with the volumetrically determined value of 0.87. HSF dramatically decreased the oil saturation. The HSF residual oil saturation profile was inhomogeneous, increasing from 0.23 to 0.43 along the flow direction. LSF1 decreased the oil saturation at the sand pack outlet end but did not change saturation at the inlet section. LSF2 did not decrease the oil saturation. LSF3 slightly decreased the oil saturation at the outlet end. A higher residual oil saturation is observed in the sand pack outlet after LSF3. Similar oil saturation changes were observed in Figure 5b for the montmorillonite-coated sand pack. The average initial oil saturation was 0.85, which was once again consistent with the volumetrically determined value of 0.86. Higher residual oil saturation was also observed at the outlet of the sand pack after each waterflooding stage. The difference as compared to the kaolinite-coated sand pack is that LSF decreased residual oil saturation along the entire sand pack (except at position 1.9 cm), and not only at the outlet end of the sample. The SE-SPI MRI measurements were repeated to monitor the dynamic flooding process in the montmorillonite-coated sand pack. Constant oil saturation distribution results were observed for the last three measurements in each waterflooding stage (not shown). The standard deviations of oil saturation values

Figure 4. Oil saturation in a Bentheimer core plug determined with the proposed differential relaxation time distribution method and the volumetric method. The proposed method provides consistent oil saturation results as compared to the conventional volumetric method.

estimated on the basis of the last three SE-SPI measurements at each waterflooding stage were calculated. These standard deviations were considered as the uncertainties of the oil saturation distribution in Figure 5b. The uncertainties are smaller than the data symbol in the figure and thus are not shown. Figure 6 shows the SE-SPI spatially resolved T2 distribution along the kaolinite-coated sand pack at the initial state, after HSF and after successive LSF. At initial oil saturation with irreducible water in the sand pack (a), a longer T2 component, 33 ms, and a shorter component, 0.5 ms, were observed. Figure 6b shows that HSF reduced the amplitude of the oil T2 as the oil saturation decreased. HSF generated a new T2 component at approximately 600 ms. The two T2 components, 33 and 600 ms, are consistent with the result of the 2D T 1 −T 2 D

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Figure 5. SE-SPI MRI estimated oil saturation profiles along the claycoated sand packs at initial state (●), after HSF (■), LSF1 (○), LSF2 (gray ▲), and LSF3 (gray ◆). Estimates employed the differential relaxation time distribution method. In (a) and (b), overall homogeneous initial oil saturation profiles (●) were observed. HSF (■) dramatically decreased the oil saturations, generating inhomogeneous residual oil saturation profiles. LSF decreased the oil saturation at the sand pack rear section in (a), and along the entire sand pack in (b), both generating inhomogeneous residual oil saturation profiles after LSF3.

Figure 6. SE-SPI spatially resolved T2 distribution along the kaolinitecoated sand pack at five flooding stages. The flooding direction is from bottom to top. (a) At initial oil saturation, a longer T2 component located at 33 ms and a shorter component 0.5 ms are observed. (b) HSF decreased the oil saturation, reduced the amplitude of oil T2 component, 33 ms, and generated a new T2 component, 600 ms. (c) LSF1 slightly decreased the amplitude of the oil component, 33 ms, and increased the amplitude of the free water component. (d) LSF2 increased the amplitude of the short T2 component, 0.5 ms. (e) LSF3 decreased the amplitude of the short T2 component, 0.5 ms.

measurement shown in Figure 3b. LSF1 further decreased the amplitude of the T2 component at 33 ms and increased the amplitude of the free water T2 component when displacing more oil. LSF2 increased the amplitude of the short T2 component, 0.5 ms. LSF3 decreased the amplitude of the short T2 component, 0.5 ms. Similar spatially resolved T2 distributions were observed for the montmorillonite-coated sand pack in Figure 7. Figure 8 shows the SE-SPI spatially resolved T2 logarithmic mean (T2LM) along the two sand packs at the initial state before flooding, after HSF, and after a series of LSF stages. The T2LM values were calculated on the basis of the data of Figures 6 and 7 with a literature method.45 These values depend on the combined water T2 distribution and oil T2 distribution. For the kaolinite-coated and montmorillonite-coated sand packs, the oil saturation was 0.86 and 0.85 before HSF, and was approximately 0.22−0.43 and 0.12−0.29 after HSF and LSF (Figure 5), respectively. Therefore, T2LM was dominated by oil before HSF but dominated by water after HSF and LSF for these two samples. In Figure 8a, a homogeneous T2LM map, with a value of 13 ms, was observed at the initial oil saturation state. HSF increased T2LM along the sand pack as water saturation increased, generating an inhomogeneous T2LM map. T2LM decreased from approximately 150 ms at the inlet to approximately 70 ms at the outlet. This is consistent with the inhomogeneous oil saturation profile as shown in Figure 5a. LSF1 further increased T2LM along the sand pack as water saturation increased when LSF1 improved oil recovery. T2LM

decreased with LSF2, and increased to approximately 152 ms with LSF3. In Figure 8b for the montmorillonite-coated sand pack, a heterogeneous T2LM map with the maximum T2LM values at position 3.2 cm was observed after each flooding stage. Figure 9 shows the oil recovery from HSF and a series of LSF stages in the two sand packs. The oil recovery is the average result estimated on the basis of bulk T1 measurements, bulk T2 measurements, and SE-SPI measurements, all with the differential relaxation time distribution method. The error bars show the standard errors of the results of these three measurements. For the kaolinite-coated sand pack, the oil recovery from HSF was 68% OOIP. LSF increased oil recovery, from LSF1 to LSF3, to 72% OOIP. For the montmorillonitecoated sand pack, LSF improved oil recovery in total by 9% OOIP with the greatest improvement of 6% OOIP by LSF3. Figure 10 shows the STE-PFG37 self-diffusion results of oil and water in the two sand packs at five flooding stages. Figure 10a and c shows the diffusion coefficient distribution. The slow component, ∼10−10 m2/s, is associated with oil, while the faster component, ∼10−9 m2/s, is attributed to water in the pore space of the sand packs. For the kaolinite-coated sand pack, the water diffusion coefficient (peak value) increased from 8.6 × 10−10 to 1.7 × 10−9 m2/s with HSF and was constant during LSF. For the montmorillonite-coated sand pack, the water diffusion coefficient increased from 6.5 × 10−10 to 1.9 × 10−9 E

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Figure 8. SE-SPI spatially resolved T2LM along the clay-coated sand packs at initial state before flooding (●), after HSF (■), LSF1 (○), LSF2 (gray ▲), and LSF3 (gray ◆). Homogenous T2LM maps were observed at the initial oil saturation state (●) in (a,b). HSF (■) increased T2LM as water saturation increased, generating inhomogeneous T2LM maps in (a,b). LSF1 (○) further increased T2LM in (a), but decreased T2LM in (b). LSF2 (gray ▲) decreased T2LM in (a), but increased T2LM in (b). LSF3 (gray ◆) elevated T2LM. Relatively homogeneous and heterogeneous T2LM maps were observed after LSF3 in (a) and (b), respectively.

Figure 7. SE-SPI spatially resolved T2 distribution along the montmorillonite-coated sand pack at the initial state, after HSF and a series of LSF stages. The flooding direction is from bottom to top. (a) At initial oil saturation, a longer T2 component located at 21 ms and a short component located at 0.6 ms are observed. (b) HSF reduced the amplitude of the oil T2 component, 21 ms, and generated a new T2 component, 530 ms. (c) LSF1 slightly decreased the amplitude of the oil component and increased the amplitude of the free water component. The amplitude of the short T2 component, 0.6 ms, was increased. (d) LSF2 slightly decreased the amplitude of the oil component, 21 ms. (e) LSF3 increased the amplitude of the longer T2 component and shifted the peak to 710 ms.

m2/s. These water diffusion coefficients are less than that of bulk water, 2.3 × 10−9 m2/s, reflecting restricted water diffusion in the sand pack. Figure 10b and d shows the data of Figure 10a and c zoomed to focus on the diffusion coefficient component ∼10−10 m2/s ascribed to oil after HSF and successive LSF. For the kaolinitecoated sand pack, the oil diffusion coefficient (peak value) gradually increased after HSF with the successive LSF (b). However, for the montmorillonite-coated sand pack, the oil diffusion coefficient decreased with LSF2 and LSF3 (d). Figure 11 shows the differential pressure during HSF and LSF. For the kaolinite-coated sand pack, the differential pressure rapidly increased during earlier periods of HSF (0− 0.3 PV) and then decreased to a constant level at approximately 0.17 psi after water breakthrough. The differential pressure increased significantly during LSF2 and decreased with LSF3. The montmorillonite-coated sand pack had a high differential pressure as compared to the kaolinite-coated sand pack. The differential pressure fluctuated significantly during LSF3 in the montmorillonite-coated sand pack.

Figure 9. Oil recovery from HSF and LSF. The oil recovery is the average result estimated based on bulk T1 measurements, bulk T2 measurements, and SE-SPI spatially resolved T2 measurements. The error bars show the standard error of the results of these three methods. LSF increased oil recovery from LSF1 to LSF3 after HSF, improving oil recovery by 4% OOIP and 9% OOIP for kaolinitecoated and montmorillonite-coated sand packs, respectively.

5. DISCUSSION 5.1. Determination of Water Saturation and Oil Saturation. D2O has been commonly employed to distinguish oil (with 1H) and water in rock core plugs.15,16,25,30 However, the water behavior cannot be probed when the MR and MRI signal is due solely to the oil. The pore scale water behaviors may reveal oil trapping and displacing mechanisms during flooding processes. In the current work, H2O rather than D2O was employed to ensure the evaluation of the interactions between water and the pore surface in the sand pack. Although 2D MR techniques often improve the ability to distinguish different 1H populations F

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The differential relaxation time distribution method proposed to determine fluid saturation requires a high-quality T1 or T2 distribution. The most important criterion for a highquality distribution is the signal-to-noise ratio (SNR) of the original data. In this work, bulk CPMG measurements had a SNR of 3900. Spatially resolved SE-SPI measurements had a SNR of 660. Quality control measurements associated with data processing (not reported) show that the final results were robust to variation of the regularization parameter. The T2 distribution range was maintained constant in all data processing. Although 2D T1−T2 measurements did not distinguish oil and water in smaller pores in the two sand packs, the new longer lifetime components in Figure 3b and d reveal the water in larger pores after HSF displaced oil in these larger pores. It seems that the greatest displacements between oil and water occurred in larger pores. In other words, water in the smaller pores may not be affected by flooding. This is consistent with a previous assumption (section 2.3) that the oil injection process will change the interaction between the pore surface and fluid in larger pores, but not in smaller pores. In this work, the STE-PFG self-diffusion (D) measurement was not able to quantitatively determine the oil and water saturations. This is related to the short relaxation time of the oil phase and significant signal loss due to the long duration between magnetic field gradient pulses.46 As shown in Table 2, Δ = 125 ms and δ = 7 ms were required to measure the low diffusion coefficient of crude oil as the maximum possible gradient was 31 G/cm. 2D D−T2 measurements have been employed to determine oil and water saturations in the literature.13 In the current work, due to limitations of the diffusion measurement, it was not possible to accurately determine fluid saturations in the sand pack from D−T2 measurements. Although the STE-PFG measurements failed to quantify the oil and water saturation, the qualitative separation of oil and water behaviors by diffusion is reliable.46 5.2. Oil Saturation Profiles and Oil Recovery Improvements by LSF. For the SE-SPI measurement, the differential relaxation time distribution method was employed, based on the spatially resolved T2 distribution, to determine oil saturation at each position along the sand pack. Most studies in the literature consider the LSF influence on oil recovery in a bulk core plug. Figure 5a shows that LSF decreased the residual oil saturation and improved oil recovery mainly from the rear section in the kaolinite-coated sand pack, revealing a spatially dependent LSF effect. The higher residual oil saturation at the outlet of the sand pack is consistent with a capillary end effect in an oil-wet sample. LSF increased oil recovery by 4% OOIP and 9% OOIP for the kaolinite-coated and montmorillonite-coated sand packs, respectively. The literature suggests that the oil recovery improvement with LSF can be approximately 10% in some cases but may be negligible in others.3,4,19 Winoto et al.47 measured LSF for a series of sandstone samples and found the highest recovery improvement from LSF was approximately 5% OOIP, while most were 1−3% OOIP. Therefore, a 4% OOIP and a 9% OOIP increase from LSF in the current work are reasonable oil recovery improvements. Montmorillonite is a swelling clay with higher cation exchange capacity as compared to the nonswelling kaolinite clay.31 Cation exchange between the pore surface and injected brine has been identified as a mechanism of LSF for EOR.48 This may explain the incremental oil recovery in the montmorillonite-coated sand

Figure 10. STE-PFG diffusion coefficients of oil and water in the two sand packs at different flooding stages. The slow component is associated with oil, while the faster component is attributed to water in (a,c). Oil diffusion coefficient distributions are reported in (b,d). For the kaolinite-coated sand pack (b), the oil diffusion coefficient gradually increased with LSF. For the montmorillonite-coated sand pack (d), the oil diffusion coefficient decreased with LSF. The bulk crude oil diffusion coefficient distribution (red line, ○) had a peak value of 2.0 × 10−10 m2/s.

Figure 11. Differential pressure (Δp) during HSF and LSF. The higher Δp values are for montmorillonite-coated sand pack, while the lower values correspond to the kaolinite-coated sand pack. Δp increased during LSF2 for kaolinite-coated sand pack. Δp fluctuated significantly during LSF3 in montmorillonite-coated sand pack.

as compared to 1D MR methods,35,36 Figure 3 indicates that 2D T1−T2 measurements cannot distinguish oil and water in smaller pores in the two sand packs employed. The proposed differential relaxation time distribution method (section 2.3) was employed to estimate the water and oil saturations. The initial oil saturation, Soi, in the kaolinite-coated and montmorillonite-coated sand packs, determined from bulk CPMG measurements with the new differential relaxation distribution method, were 0.85 and 0.84, consistent with the volumetrically determined Soi, 0.87 and 0.86, respectively. The Soi values determined from the inversion recovery T1 measurement with the new method were also consistent with the results from volumetric measurement. Figure 4 also demonstrates that the differential relaxation time distribution method provides consistent oil saturation results as compared to the conventional volumetric method. G

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For the kaolinite-coated sand pack, the T2LM map is inhomogeneous after LSF1 and LSF2 (Figure 8a). T2LM decreased from the inlet to the outlet. This indicates an inhomogeneous water saturation and oil saturation at the pore scale along the sand pack. Water saturation was higher in the pores at the inlet section as compared to those at the outlet section. The amplitude decrease for the short T2 component, 0.5 ms, in Figure 6e may be due to a decrease in clay bound water in the kaolinite-coated sand pack. A relatively homogeneous T2LM map (although with scattered data points) with a longer T2LM, ∼152 ms, along the sand pack was observed after LSF3 as compared to HSF, LSF1, and LSF2, as shown in Figure 8a. Deionized water was employed for LSF3 following work in the literature.44,54 Opaque water was produced during LSF3, indicating solid particles in the water effluent. This observation is consistent with fines migration from sandstone core plugs during low salinity or deionized waterflooding.18,55 The coated kaolinite clay may be displaced from the sand pack during LSF3. This could increase the pore size in the sand pack and thereby increase T2LM. In addition, kaolinite is known to contain some paramagnetic elements such as manganese and iron.56 Decreasing the kaolinite content with LSF3 reduced the paramagnetic impurities in the sand pack. This could decrease the surface relaxivity,57 thereby increasing the T2 lifetime. For the montmorillonite-coated sand pack, similar variations of spatially resolved T2 distribution and T2LM were observed as compared to the kaolinite-coated sand pack, suggesting similar pore scale fluid behaviors. However, there were a few specific differences. LSF1 increased the amplitude of the short T2 component, 0.6 ms, for the montmorillonite-coated sand pack (Figure 7c), but did not do so for the kaolinite-coated sample (Figure 6c). Instead, LSF2 increased the amplitude of the short T2 component, 0.5 ms, for the kaolinite-coated sand pack (Figure 6d). These short T2 components were assumed to be associated with clay bound water in the sand packs. Consistent with the difference above, LSF1 increased T2LM for the kaolinite-coated sand pack (Figure 8a), but decreased T 2LM for the montmorillonite-coated sand pack (Figure 8b). On the contrary, LSF2 decreased T2LM for the kaolinite-coated sand pack, but increased T2LM for the montmorillonite-coated sand pack. 5.4. Evaluation of the Wettability Changes with LSF. Seland et al.28 observed that the oil diffusion coefficient was lower in oil-wet glass spheres as compared to a water-wet sample. Thomas et al.29 found that liquid diffusion was impeded near a more-wetting surface but enhanced near a less-wetting surface. Therefore, the increase of oil diffusion coefficient with LSF in Figure 10b, for the kaolinite-coated sand pack, is assumed to be associated with the pore surface changing to be more water-wet, providing less restriction for oil diffusion. On the contrary, the decreased oil diffusion coefficient with LSF2 and LSF3 in Figure 10d may be related to the pore surface changing to be less water-wet for the montmorillonite-coated sand pack. Although the wettability alteration toward more water-wet is the most common proposed mechanism for LSF EOR,21 a wettability change in the opposite direction may be a mechanism for different sample systems,19,22 such as the montmorillonite-coated sand pack in this work. Kaolinite is more oil-wet than montmorillonite.31 A reasonable hypothesis is that the kaolinite-coated sand pack was oil-wet while the

pack by LSF. Clay swelling can reduce rock core permeability and thus decrease the oil recovery in some reservoirs. In this work, however, the montmorillonite-coated sand pack was unconsolidated with high permeability and low clay content, 0.48 wt %. The swelling-montmorillonite may temporarily block some flow channels, but, ultimately, the clay particles are able to migrate forward as solid particles were observed in the effluent during LSF. 5.3. Pore Scale Fluid Behaviors. MR and MRI measurements have been employed by many authors to reveal the pore scale fluid behaviors in porous media.11,16 Li et al.49 employed a k−t accelerated SE-SPI MRI method to monitor core flooding processes in Berea core plugs. They concluded that the amplitude increase of the longer T2 component during water and polymer flooding was related to the water saturation increase in larger pores. Yang et al.50 determined the oil saturation and oil recovery as functions of pore size by comparing T2 distributions before and after waterflooding in a water-wet core plug. The spatially resolved T2 distributions (Figures 6 and 7) and the T2LM maps (Figure 8) report on the water and oil behaviors at the pore scale in the sand packs. T2LM is conventionally employed for rock core studies.11,51 The following discussion will first focus on the kaolinite-coated sand pack. The different behaviors observed for the two clay-coated sand packs will then be compared. The longer T2 component, 33 ms in Figure 6a, is dominated by oil in the kaolinite-coated sand pack, but is overlapped with the signal from water in smaller pores as the irreducible water saturation was approximately 0.13. The irreducible water in smaller pores is assigned to capillary bound water, while the shorter component, 0.5 ms, with very low amplitude may be associated with clay bound water, observations that are consistent with the literature.11,49,52,53 The new T2 component, 600 ms, shown in Figure 6b is attributed to water in larger pores after HSF. For the kaolinite-coated sand pack, the increase of the amplitude of the short T2 component, 0.5 ms, by LSF2 in Figure 6d is similar to the observation by Li et al.49 They attributed this amplitude increase to more clay bound water. Increased clay bound water suggests more restriction for fluid flow, consistent with the increased differential pressure during LSF2 as shown in Figure 11. The T2LM decrease with LSF2 (Figure 8a) suggests the pore size and/or pore wettability were affected by the interactions between water and the clay-coated pore surface. Kaolinite is a nonswelling clay.40,41 A decreasing pore size and thereby a decreasing T2 relaxation lifetime due to clay swelling is not expected. In this work, it is hypothesized that LSF2 can increase the detachment of clay particles from the pore wall.41 Detached but not yet migrated clay can decrease the pore size and thereby decrease T2LM. Transparent water effluent was observed during LSF2, suggesting no clay was produced. Another possible reason for the T2LM decrease is that LSF2 might change the sand pack to be more water-wet. This analysis is consistent with the discussion for the oil diffusion coefficient increase with LSF2 presented later. Afrough et al.18 undertook SE-SPI MRI measurements to monitor fine migrations in Berea core plugs and observed increased and decreased T2LM at the sample inlet and outlet, respectively, after deionized water injection. They attributed these T2LM changes to altered pore sizes in the samples. H

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(5) Tang, G. Q.; Morrow, N. R. Salinity, Temperature, Oil Composition, and Oil Recovery by Waterflooding. SPE Reservoir Eng. 1997, 12 (4), 269−276. (6) Webb, K. J.; Black, C. J. J.; Al-Ajeel, H. Low Salinity Oil Recovery-Log-Inject-Log. Presented at the SPE/DOE Symposium on Improved Oil Recovery, Tulsa, OK, April 17−21, 2004; Paper SPE 89379. (7) Yousef, A. A.; Al-Saleh, S.; Al-Jawfi, M. Smart Waterflooding for Carbonate Reservoirs: Salinity and Role of Ions. Presented at the SPE Middle East Oil and Gas Show and Conference, Manama, Bahrain, September 25−28, 2011; Paper SPE 141082. (8) Hamouda, A. A.; Valderhaug, O. M. Investigating Enhanced Oil Recovery from Sandstone by Low-Salinity Water and Fluid/Rock Interaction. Energy Fuels 2014, 28 (2), 898−908. (9) Hadia, N. J.; Ashraf, A.; Tweheyo, M. T.; Torsæter, O. Laboratory Investigation on Effects of Initial Wettabilities on Performance of Low Salinity Waterflooding. J. Pet. Sci. Eng. 2013, 105, 18−25. (10) Hughes, D.; Law, S.; Pitt, G. Low Salinity EOR “State of Play” Review; Senergy Limited: Aberdeen, UK, 2012. (11) Coates, G. R.; Xiao, L.; Prammer, M. G. NMR Logging Principles and Applications; Halliburton Energy Services: Houston, TX, 1999. (12) Mitchell, J.; Chandrasekera, T. C.; Holland, D. J.; Gladden, L. F.; Fordham, E. J. Magnetic Resonance Imaging in Laboratory Petrophysical Core Analysis. Phys. Rep. 2013, 526 (3), 165−225. (13) Mitchell, J.; Staniland, J.; Chassagne, R.; Fordham, E. J. Quantitative in situ Enhanced Oil Recovery Monitoring Using Nuclear Magnetic Resonance. Transp. Porous Media 2012, 94 (3), 683−706. (14) Romero-Zerón, L.; Ongsurakul, S.; Li, L.; Balcom, B. Visualization of the Effect of Porous Media Wettability on Polymer Flooding Performance through Unconsolidated Porous Media using Magnetic Resonance Imaging. Pet. Sci. Technol. 2010, 28 (1), 52−67. (15) Li, M.; Xiao, D.; Romero-Zerón, L.; Marica, F.; MacMillan, B.; Balcom, B. J. Mapping Three-Dimensional Oil Distribution with π-EPI MRI Measurements at Low Magnetic Field. J. Magn. Reson. 2016, 269, 13−23. (16) Li, M.; Xiao, D.; Shakerian, M.; Afrough, A.; Goora, F.; Marica, F.; Romero-Zerón, L.; Balcom, B. J. Magnetic Resonance Imaging of Core Flooding in a Metal Core Holder. Presented at the International Symposium of the Society of Core Analysts, Snowmass, CO, Aug. 21− 26, 2016; Paper SCA2016-019. (17) Ramskill, N. P.; Bush, I.; Sederman, A. J.; Mantle, M. D.; Benning, M.; Anger, B. C.; Appel, M.; Gladden, L. F. Fast Imaging of Laboratory Core Floods Using 3D Compressed Sensing RARE MRI. J. Magn. Reson. 2016, 270, 187−197. (18) Afrough, A.; Zamiri, M. S.; Romero-Zerón, L.; Balcom, B. J. Magnetic Resonance Imaging of Fines Migration in Berea Sandstone. SPE J. 2017, in press, 10.2118/186089-PA. (19) Sheng, J. J. Critical Review of Low-Salinity Waterflooding. J. Pet. Sci. Eng. 2014, 120, 216−224. (20) Sandengen, K.; Arntzen, O. J. Osmosis During Low Salinity Water Flooding. Presented at the 17th European Symposium on Improved Oil Recovery, St. Petersburg, Russia, April 16−18, 2013; Paper A-19. (21) Morrow, N. R.; Buckley, J. Improved Oil Recovery by LowSalinity Waterflooding. JPT, J. Pet. Technol. 2011, 63 (5), 106−112. (22) Hamon, G. Low-Salinity Waterflooding: Facts, Inconsistencies and the Way Forward. Petrophysics 2016, 57, 41−50. (23) Anderson, W. G. Wettability Literature Survey-Part 2: Wettability Measurement. JPT, J. Pet. Technol. 1986, 38 (11), 1246− 1262. (24) Brown, R. J. S.; Fatt, I. Measurements of Fractional Wettability of Oil Fields’ Rocks by the Nuclear Magnetic Relaxation Method. Presented at the Fall Meeting of the Petroleum Branch of AIME, Los Angeles, CA, Oct. 14−17, 1956; Paper SPE 743-G. (25) Zhang, G. Q.; Huang, C. C.; Hirasaki, G. J. Interpretation of Wettability in Sandstones with NMR Analysis. Petrophysics 2000, 41, 223−233.

montmorillonite-coated sample was water-wet, respectively, after HSF and before LSF1. Neutral wettability may be generated during LSF in the two sand packs. The wettability alteration toward neutral conditions could contribute to the oil recovery improvement as the lowest residual oil saturation was found at the neutral-wet conditions.58,59

6. CONCLUSIONS In this study, MR relaxation time measurements were employed to reveal the interactions between fluid (oil and water) and clay-coated pore surfaces with HSF and LSF. The T2 mapping methodology, SE-SPI, was employed to spatially resolve the T2 distribution. A differential relaxation time distribution method was proposed to estimate the oil and water saturation on the basis of the relaxation time distributions. The oil saturation profiles were determined on the basis of the SE-SPI MRI measurements with the differential relaxation time distribution method. The STE-PFG diffusion measurements were employed to measure the oil and water diffusion coefficients before and after each LSF. For the kaolinite-coated sand pack, the increased oil diffusion coefficient with LSF is assumed to be associated with increased water wettability during LSF, while for the montmorillonite-coated sample, the oil diffusion decrease may be related to decreased water-wetness with LSF. MR and MRI measurements can be employed to evaluate oil and water behaviors and mechanisms of low salinity waterflooding for enhanced oil recovery.



AUTHOR INFORMATION

Corresponding Author

*Tel.: (506) 458-7938. Fax: (506) 453-4581. E-mail: bjb@unb. ca. ORCID

Ming Li: 0000-0001-9861-7858 Notes

The authors declare no competing financial interest.



ACKNOWLEDGMENTS B.J.B. thanks NSERC of Canada for a Discovery grant and an Idea to Innovation grant as well as the Canada Chairs program for a Research Chair in MRI of Materials. We also thank Green Imaging Technologies, ConocoPhillips, Saudi Aramco, and the Atlantic Innovation Fund for financial support. M.L. thanks Dr. B. MacMillan for Matlab programs.



REFERENCES

(1) Martin, J. C. The Effects of Clay on the Displacement of Heavy Oil by Water. Presented at the SPE Venezuelan Annual Meeting, Caracas, Venezuela, October 14−16, 1959; Paper SPE 1411. (2) Bernard, G. G. Effect of Floodwater Salinity on Recovery of Oil from Cores Containing Clays. Presented at the SPE California Regional Meeting, Los Angeles, CA, October 26−27, 1967; Paper SPE 1725. (3) Thyne, G.; Gamage, P. Evaluation of the Effect of Low Salinity Waterflooding for 26 Fields in Wyoming. Presented at the SPE Annual Technical Conference and Exhibition, Denver, CO, October 30November 2, 2011; Paper SPE 147410. (4) Skrettingland, K.; Holt, T.; Tweheyo, M. T.; Skjevrak, I. Snorre Low-Salinity-Water Injection-Core Flooding Experiments and SingleWell Field Pilot. SPE Reservoir Eval. Eng. 2011, 14 (2), 182−192. I

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Article

Energy & Fuels (26) Chen, Q.; Mercer, D.; Webb, K. NMR Study on Pore Occupancy and Wettability Modification during Low Salinity Waterflooding. Presented at the International Symposium of the Society of Core Analysts, Halifax, Nova Scotia, Canada, October 4−7, 2010; Paper SCA 2010-27. (27) Li, M.; Romero-Zerón, L.; Marica, F.; Balcom, B. J. Polymer Flooding Enhanced Oil Recovery Evaluated with Magnetic Resonance Imaging and Relaxation Time Measurements. Energy Fuels 2017, 31, 4904−4914. (28) Seland, J. G.; Washburn, K. E.; Anthonsen, H. W.; Krane, J. Correlations between Diffusion, Internal Magnetic Field Gradients, and Transverse Relaxation in Porous Systems Containing Oil and Water. Phys. Rev. E 2004, 70, 051305. (29) Thomas, J. A.; McGaughey, A. J. H. Effect of Surface Wettability on Liquid Density, Structure, and Diffusion near a Solid Surface. J. Chem. Phys. 2007, 126, 034707. (30) Petrov, O.; Ersland, G.; Balcom, B. J. T2 Distribution Mapping Profiles with Phase Encode MRI. J. Magn. Reson. 2011, 209, 39−46. (31) González Sánchez, F. Water Diffusion through Compacted Clays Analyzed by Neutron Scattering and Tracer Experiments. Ph.D. Thesis, University of Bern, Bern, Switzerland, 2007. (32) Lebedeva, E. V.; Fogden, A. Micro-CT and Wettability Analysis of Oil Recovery from Sand Packs and the Effect of Waterflood Salinity and Kaolinite. Energy Fuels 2011, 25, 5683−5694. (33) Mahani, H.; Berg, S.; Ilic, D.; Bartels, W. B.; Joekar-Niasar, V. Kinetics of Low-Salinity-Flooding Effect. SPE J. 2015, 20, 8−20. (34) Fogden, A.; Kumar, M.; Morrow, N. R.; Buckley, J. Mobilization of Fine Particles during Flooding of Sandstones and Possible Relations to Enhanced Oil Recovery. Energy Fuels 2011, 25, 1605−1616. (35) Fleury, M.; Romero-Sarmiento, M. Characterization of Shales using T1-T2 NMR Maps. J. Pet. Sci. Eng. 2016, 137, 55−62. (36) Jerath, K. Reconciliation of Two-Dimensional NMR Measurements with the Process of Mud-Filtrate Invasion: Synthetic and Field Examples. M.sc. Thesis, University of Texas at Austin, Austin, TX, 2011. (37) Tanner, J. E. Use of the Stimulated Echo in NMR Diffusion Studies. J. Chem. Phys. 1970, 52, 2523. (38) Freedman, R.; Lo, S.; Flaum, M.; Hirasaki, G. J.; Matteson, A.; Sezginer, A. A New NMR Method of Fluid Characterization in Reservoir Rocks: Experimental Confirmation and Simulation Results. SPE J. 2001, 6, 452−464. (39) Minh, C. C.; Jain, V.; Griffiths, R.; Maggs, D. NMR T2 Fluids Substitution. Presented at the SPWLA 57th Annual Logging Symposium, Reykjavik, Iceland, June 25−29, 2016. (40) Lebedeva, E. V.; Fogden, A. Wettability Alteration of Kaolinite Exposed to Crude Oil in Salt Solutions. Colloids Surf., A 2011, 377, 115−122. (41) Barnaji, M. J.; Pourafshary, P.; Rasaie, M. R. Visual Investigation of the Effects of Clay Minerals on Enhancement of Oil Recovery by Low Salinity Water Flooding. Fuel 2016, 184, 826−835. (42) Lebedeva, E. V.; Fogden, A. Adhesion of Oil to Kaolinite in Water. Environ. Sci. Technol. 2010, 44, 9470−9475. (43) Durand, C.; Rosenberg, E. Fluid Distribution in Kaolinite- or Illite-Bearing Cores: Cryo-SEM Observations versus Bulk Measurements. J. Pet. Sci. Eng. 1998, 19, 65−72. (44) Song, W.; Kovscek, A. R. Functionalization of Micromodels with Kaolinite for Investigation of Low Salinity Oil-Recovery Processes. Lab Chip 2015, 15, 3314. (45) Nechifor, R. E.; Romanenko, K.; Marica, F.; Balcom, B. J. Spatially Resolved Measurements of Mean Spin-Spin Relaxation Time Constants. J. Magn. Reson. 2014, 239, 16−22. (46) Vashaee, S.; Newling, B.; MacMillan, B.; Marica, F.; Li, M.; Balcom, B. J. Local Diffusion and Diffusion-T2 Distribution Measurements in Porous Media. J. Magn. Reson. 2017, 278, 104−112. (47) Winoto, W.; Loahardjo, N.; Morrow, N. Assessment of Oil Recovery by Low Salinity Waterflooding from Laboratory Tests. Presented at the SPE Improved Oil Recovery Symposium, Tulsa, OK, April 12−16, 2014; Paper SPE 169886.

(48) Lager, A.; Webb, K. J.; Black, C. J. J; Singleton, M.; Sorbie, K. S. Low Salinity Oil Recovery-An Experimental Investigation. Presented at the International Symposium of the Society of Core Analysts, Trondheim, Norway, September 12−16, 2006; Paper SCA2006-36. (49) Li, M.; Xiao, D.; Romero-Zerón, L.; Balcom, B. Monitoring Oil Displacement Processes with k-t Accelerated Spin Echo SPI. Magn. Reson. Chem. 2016, 54, 197−204. (50) Yang, P.; Guo, H.; Yang, D. Determination of Residual Oil Distribution during Waterflooding in Tight Oil Formations with NMR Relaxometry Measurements. Energy Fuels 2013, 27, 5750−5756. (51) Hirasaki, G. J.; Mohanty, K. K. Fluid-Rock Characterization for NMR Well Logging and Special Core Analysis-1st Annual Report; Rice University and University of Houston: Houston, TX, 2005. (52) Peveraro, R.; Thomas, E. C. Effective Porosity: A Defensible Definition for Shale Sands. Presented at the SPWLA 51st Annual Logging Symposium, Perth, Australia, June 19−23, 2010. (53) Thern, H.; Page, G. Joint Interpretation of Magnetic Resonance and Resistivity-Based Fluid Volumetrics − A Framework for Petrophysical Evaluation. Presented at the SPWLA 57th Annual Logging Symposium, Reykjavik, Iceland, June 25−29, 2016. (54) Nasralla, R. A.; Alotaibi, M. B.; Nasr-EI-Din, H. Efficiency of Oil Recovery by Low Salinity Water Flooding in Sandstone Reservoirs. Presented at the SPE Western North American Regional Meeting, Anchorage, AK, May 7−11, 2011; Paper SPE 144602. (55) Tang, G. Q. Influence of Brine Composition and Fines Migration on Crude Oil/Brine/Rock Interactions and Oil Recovery. J. Pet. Sci. Eng. 1999, 24, 99−111. (56) Balan, E.; Allard, T.; Boizot, B.; Morin, G.; Muller, J. P. Quantitative Measurement of Paramagnetic Fe3+ in Kaolinite. Clays Clay Miner. 2000, 48 (4), 439−445. (57) Kenyon, W. E. Petrophysical Principles of Applications of NMR Logging. Log Analyst 1997, 38, 21−43. (58) Morrow, N. R. Wettability and Its Effect on Oil Recovery. JPT, J. Pet. Technol. 1990, 42 (12), 1476−1484. (59) Donaldson, E. C.; Alam, W. Wettability; Gulf Publishing Co.: Houston, TX, 2008; pp 42−43.

J

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