Dynamics and Wettability of Oil and Water in Oil Shales - The

We used both cylindrical rock cores samples of 1 cm and 2 inch in length ... Figure 2. 1H NMR spectrum of oil/water/air shale at 300 MHz (top); X-band...
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Dynamics and Wettability of Oil and Water in Oil Shales Jean-Pierre Korb,*,† Benjamin Nicot,‡ A. Louis-Joseph,† Salvatore Bubici,§ and Gianni Ferrante§ †

Physique de la Matière Condensée, Ecole Polytechnique-Centre National de la Recherche Scientifique (CNRS), 91128 Palaiseau, France ‡ Centre Scientifique et Technique Jean Feger (CSTJF), TOTAL EP, 64018 Pau, France § STELAR s.r.l., Via Enrico Fermi, 4-27035 Mede, Pavia (PV), Italy ABSTRACT: It is critical to probe in situ the dynamics and wettability of oil, water, and gas trapped in the complex microstructure of oil-shale rocks. However, usual techniques cannot separate these fluids in shale rocks. Here, we use multifrequency and multidimensional nuclear magnetic relaxation (NMR) techniques for probing these dynamics. The frequency dispersion behaviors of the longitudinal relaxation rates 1/T1 for oil and water confined in shales are interpreted through a relaxation model showing one-dimensional (oil) and two-dimensional (2D) (water) diffusing phases confined within the organic kerogen and mineral layers, respectively. We probe the average hopping and residence times of these fluids at pore surfaces and assign signals to water and oil at both organic and mineral pore surfaces for characterizing their local wettability. This allows interpreting our 2D T1−T2 correlation spectra that could be made down-hole, thus giving an invaluable tool for investigating oil and gas recovery on these important porous rocks. NMRD allow interpretation of our 2D T1−T2 correlation spectra of petroleum fluids in oil and water shales, which are also made down-hole.

I. INTRODUCTION How to probe noninvasively the dynamics and wettability of petroleum fluids (oil/water/gas) trapped in the complex microstructure of an oil-shale rock? This question is important because liquid and gas hydrocarbons can be produced from this organic rich fine-grained sedimentary rock. Hydrocarbon production depends on porosity, saturation, wettability, pore pressure, matrix permeability, and hydraulic fractures. 1 Mineralogical variations, low permeability, and the multiscale microstructure of the organic kerogen complicate the evaluation of these rocks. Usual 1H one-dimensional (1D) and two-dimensional (2D) low-field NMR techniques have been proposed to answer the question.1−3 However, it is still difficult to separate the oil and water NMR responses. A recent NMR technique relies on the presence of Na in the brine to distinguish the water-based fluid from oil in Bentheimer sandstone rock-cores.4 However, this determination implies that one knows the salinity of the brine in the sample. In the case of shale rocks, often the reservoir salinity is not known, and the salinity of the water present in the plug is a mixture between reservoir salinity and drilling mud salinity. So, other NMR techniques must be sought for such identification. Here, we propose the nuclear magnetic relaxation dispersion (NMRD), the measurement of longitudinal spin relaxation rate R1 as a function of magnetic field strength or Larmor frequency5 for probing dynamics and wettability of oil and water confined in shale rocks. We show that the striking differences observed in the NMRD profiles are mainly due to the low dimensionality of the diffusion of oil and water in organic kerogen and mineral pore structures, respectively. We find parameters qualifying the dynamics and local wettability of these confined petroleum fluids. The results found from © 2014 American Chemical Society

II. EXPERIMENTAL SECTION 1. Materials. The different rocks samples (oil/water/air and water/air) come from a field producing light oil and are supplied by Total EP, France. The analysis reveals a density of ρshale = 2.6 g/cm3. We used both cylindrical rock cores samples of 1 cm and 2 inch in length and 8 mm and 1.5 inch in diameter. For separating the NMR responses of confined oil and water in the 2D NMR T1−T2 correlation experiments, we used both oil-shale samples and gas-shale samples in fresh states (or as-received state). Moreover, for separating the NMRD responses of confined oil and water, the samples have been measured in fresh states (or as-received state), but they have been also cleaned by Soxhlet using chloroform and isopropanol, and then dried. We verified on the dry samples that no NMR signal was present. The sample is then saturated with water, and the resulting NMR signal can be assigned undoubtedly to water. 2. Methods. Scanning Electron Microscopy. The porous samples are first characterized by scanning electron micrographs (SEM) performed by Oklahoma University (Figures 1a,b). These images clearly show the organic kerogen micropores (Figure 1a) as well as the mesoporous lamellar mineral matters (Figure 1b). Received: August 27, 2014 Revised: September 16, 2014 Published: September 16, 2014 23212

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diluted in heavy water for facilitating the field homogenization and 1H assignment. One notes an intense water peak at 4.7 ppm, and two large bumps at 1.1 and 6.0 ppm that are typical of the oil proton ranges (aliphatic and aromatic), respectively. This NMR spectrum thus proves the presence of water and oil in the oil-shale rock as received. Electron Spin Resonance. We use electron spin resonance (ESR) spectroscopy to determine the nature and quantity of paramagnetic species in oil shales. The six-peak hyperfine structure centered on g = 2 (Figure 2, bottom) is characteristic of electronic spins S = 5/2 of paramagnetic Mn2+ ions in a single environment. We have calibrated the X-band ESR surface area by measuring the signal in the presence of monocrystals of CuSO4·5H2O diluted in inert KBr powder. This gives a density of ηS = 4.50 × 1019 Mn2+ ions per gram of oil-shale sample. Assuming a homogeneous repartition of paramagnetic ions in the sample, we deduce from ηS a homogeneous surface density of paramagnetic relaxation sinks σS = 2.39 × 1013 Mn2+/cm2, which will be active on the nuclear magnetic relaxation of liquid proton species moving in proximity of the pore surface. One-Dimensional Nuclear Magnetic Relaxation at 20 MHz. We use the standard NMR Car−Purcell−Meiboom−Gill (CPMG) sequence realized on a Bruker minispec for probing the bimodal distribution of transverse relaxation times T2 at 20 MHz of petroleum liquids embedded in these rocks (Figure 3).

Figure 1. Scanning electron micrographs of the organic kerogen (a) and mineral matters (b) measured in an oil shale sample.

Nuclear Magnetic Resonance Spectroscopy. Figure 2 (top) shows the 1H NMR spectrum performed with a Bruker Avance II 300 MHz of an oil/water/air-shale rock crushed in a powder

Figure 3. NMR distributions of transverse (T2) and longitudinal (T1) relaxation times made at 20 MHz of petroleum liquids embedded in an oil/water/air shale. The percentages indicate the relative surface area of each peak.

The distribution extends over 2 orders of magnitude of T2 values, where the peaks centered at T2 = 0.55 ms and T2 = 10 ms represents 72% and 28% of the 1H population, respectively. We also used the standard inversion recovery method for measuring the bimodal distribution of longitudinal relaxation time T1 at 21.8 MHz (Figure 3). The peaks centered at T1 = 0.55 ms and T1 = 40 ms represents 63% and 37% of the 1H population, respectively. As expected, one observes that T1 > T2 for the latter 1H population. However, these two 1D NMR techniques are not sufficient for identifying the contributions of water and oil protons in the observed bimodal distributions of Figure 3. Other NMR techniques must be sought for such identification. Two-Dimensional T1−T2 Correlation Experiments at 2.5 MHz. We introduce here the 2D NMR T1−T2 correlation experiments6 performed at 2.5 MHz with an Oxford Instrument spectrometer, on oil/water/air (Figure 4a) and water/air (Figure 4b) as-received shale samples. A mixed inversion

Figure 2. 1H NMR spectrum of oil/water/air shale at 300 MHz (top); X-band ESR spectrum of the same sample (bottom). 23213

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Figure 4. Two-dimensional T1−T2 spin correlation maps made at 2.5 MHz of oil/water/air (a) and water/air (b) as-received shales. The projections of this two-dimensional T1−T2 spin correlation maps on the T1 and T2 axes are also shown. A color code index is given for estimating the relative intensities of the different peaks.

recovery-CPMG sequence was used, at 2.5 MHz, to generate T1−T2 correlation data, and the final map has been obtained with a 2D inverse Laplace transform program. Nuclear Magnetic Relaxation Dispersion. The proton NMRD data has been performed, for the first time, on oil/ water/air and water/air shale rocks at room temperature with a fast-field cycling (FFC) spectrometer from Stelar s.r.l., Mede,

Italy (Figures 5−7). The experiment is repeated over a large range of proton Larmor frequencies ωI/2π (from 10 kHz to 35 MHz) to obtain the relaxation dispersion profile of 1/T1(ωI). To further improve the accuracy of the NMRD technique, we proceeded to two experiments made at room temperature on two companion samples, coming from the same reservoir, but realized on two different FFC spectrometers differing by the 23214

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a highly confined water population. The other elongated peak in Figure 4a, can thus be assigned to a confined oil population, which surprisingly exhibits a high T1/T2 ratio varying from 10 to 5. One sees in Figure 4a that the projections of the 2D correlation maps on both T1 and T2 axes are clearly bimodal contrary to the single projected peaks observed for very short values of T1 and T2 for the gas-shell sample (Figure 4b). One also notes the similarity of these bimodal T 1 and T 2 distributions obtained at 20 MHz (Figure 3). The surprisingly high T1/T2 ratio could be due to the presence of bitumen, but the two studied shale samples come from a field producing light oil. Moreover, the typical NMR signal for bitumen in a T1−T2 map does not fall on the diagonal because of its viscosity. We will interpret such a high T1/T2 ratio for the oil response in the theoretical section. 2. Nuclear Magnetic Relaxation Dispersion. We introduce here the proton NMRD data performed, for the first time, on oil/water/air and water/air shale rocks (Figures 5 and 6). Unlike conventional longitudinal relaxation studies made at a given Larmor frequency, this approach gives a direct probe of the dynamical surface affinity of liquids (NMR wettability) because it scans over a large range of applied magnetic fields and yields unique information about which a liquid is dynamically correlated with paramagnetic relaxation sinks at solid surface.7 Varying the magnetic field changes the Larmor frequency and therefore the time and length scales of the fluctuations responsible for the nuclear spin−lattice relaxation rate R1. This is especially true in spatially confined systems, which force more frequent re-encounters between proton in the pores (bulk molecules) and pore-surface paramagnetic relaxation sinks (Mn2+). Moreover, as the longitudinal magnetization Mz(ωI,τ) decays present, at each proton frequency ωI, a nonexponential behavior (insets of Figure 5a,b), an efficient inverse Laplace transform method was used to extract the distribution of T1 from the raw data Mz(ωI,τ). For all the Larmor frequencies, we obtain bimodal distributions of T1 of sufficiently thin peaks (Figures 5a,b) allowing to build NMRD profiles of the T1 values associated with the two peaks of these distributions (Figure 6a). The net separation of the two profiles crossing each other around 1 MHz in Figure 6a reveals an absence of proton exchange between oil and water confirming the result of Figure 4a. It is well-known that the NMRD data cannot detect T1 values shorter than the switching time that is about 1−3 ms. So the water T1 data of Figure 6a,b do not correspond to the very short water data of Figure 4b. Assignment of Water and Oil NMRD Profiles. A detailed analysis is now needed to assign water and oil to the two strikingly different NMRD profiles observed (Figure 6a). In order to identify the signal of water in such a rock we have cleaned, dried, and saturated the sample with water (standard procedure in the petroleum industry described in the Materials section). The NMRD profile acquired on such a water saturated sample, presented in Figure 6b, exhibits a quasilogarithmic behavior. Therefore, we can unambiguously assign water to the quasi-logarithmic (Figure 6b) and oil to the inverse-square root (Figure 6a) NMRD profiles, respectively. In Figure 6a,b, the dashed lines displayed are just guides for the eyes that we aim at interpreting theoretically in the following sections. Theoretical Model for Interpreting the Water NMRD Data. Here, we apply the main relaxation equations of our previous theoretical works on the nuclear magnetic relaxation of

Figure 5. T1 distributions obtained by ILT of the longitudinal magnetization decays of oil/water/air shale sample at high (a) and low (b) frequencies. We show in the insets the continuous lines representing the best fits obtained from the ILT of the magnetization decays for high and low frequencies. For all the frequencies studied, this method leads to the bimodal distributions displayed in the figure.

strength of the polarization field 0.5 and 1 T, respectively. In the present day, field cycling relaxometers from Stelar allow measurements of plugs of diameter up to 1 inch. This is far from being a limitation for the technique. We check that the NMRD data on large rock-core samples of 1 inch diameter and 1 inch height were quite identical with the ones obtained with the regular FFC spectrometer.

III. RESULTS AND DISCUSSION 1. Two-Dimensional T1-T2 Correlation Experiments at 2.5 MHz. Figure 4a shows two different 2D relaxation features without any cross peaks, thus proving the absence of proton exchange between these two populations. Figure 4b describes the situation of a gas-shale sample with only water present. So, the striking comparison of Figure 4a,b allows assigning unambiguously the single peaks at low values of T1 and T2 to 23215

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frequency (ωI/2π) dependence in the range studied here.10 On the contrary for a protic liquid, the contribution 1/T1,2D of the water relaxation induced by the 2D diffusion in proximity of the fixed paramagnetic species7−9 and the nuclear paramagnetic contribution 1/T1,param, induced by the relaxation of water linked to the first coordination sphere of paramagnetic centers11,12 are highly sensitive to the local physical chemistry effects at the pore surface resulting in different frequency behaviors in disconnected ranges.7−9 In eq 1, Nsurface/N = δwaterρwaterSp,NMR is the ratio between the number of water molecules diffusing within a thin transient layer of the order of a water molecular size (δwater ≈ 0.3 nm) close to the pore surface. ρwater = 1.0 g/cm3 is the bulk water density. Sp,NMR = SpF is an NMR-based specific surface area9 that appears to be directly proportional to the ratio F = ms,eq/mw,eq ≪ 1 of the solid-proton magnetization ms,eq to the liquid-proton magnetization mw,eq at equilibrium, and Sp is the real specific surface area of the clay-like material. Nparam/N = (Nparam/Nsurface)(Nsurface/N) ≪ Nsurface/N is the ratio between the number Nparam of water molecules bonded to the paramagnetic sites at the pore surface and the bulk. Basically, in the 2D diffusing relaxation process, the proton− water dynamics modulates the intermolecular dipole−dipole interaction between the moving proton−water of spins I = 1/2 and the fixed S=5/2 paramagnetic spins of Mn2+ at the pore surface. The reduced dimensionality (2D) of such local dynamics in the clay-like mineral pores enhances drastically the reencounter probability between I and S spins that evolves at long times t as ∝1/t. This maintains at long-times t the pairwise dipolar correlations between these two spins resulting in a logarithmic frequency behavior of 1/T1,2D at low frequency7−9 observed in Figure 6b. The frequency dependence of the nuclear paramagnetic relaxation rate (1/T1,param) is a sum of two Lorentzian at nuclear and electronic frequencies11,12 that is very well-known from the magnetic resonance imaging in which Mn(II) or Gd(III) are used as contrast agents. The NMRD profiles of such contrast agents have been largely studied, and it is known that R1,bound = (Nparam/N)1/T1,param is a constant in the low frequency range studied here, though it has a significant bump around 70 MHz.13 Substituting in eq 1 all the well-known NMR prefactors gives the following frequency-dependent expression coming from the bulk, bound, and 2D diffusing relaxation contributions of water molecules in proximity of the pore surface:7−9

Figure 6. (a) Measured logarithmic proton longitudinal relaxation rate constants R1 as a function of the proton Larmor frequency for an oil/ water/air shale. The two different sets of data points represent the NMRD profiles of the longitudinal relaxation rate constants estimated at the two peaks of the bimodal T1 distribution of Figure 5. The dashed line represents the frequency behavior ∝1/√νI as a guide for the eye. (b) Measured semilogarithmic proton longitudinal relaxation rate constants R1 of the set of data points estimated at the peak of the longest T1 in the bimodal distribution of Figure 5 as a function of the proton Larmor frequency for an oil/water/air shale before and after having expelled oil and refilled the shale sample by water.

R1,water(ωI ) = 1/T1,bulk + R1,bound + π /(30δwater 3)σSρwater Sp,NMR (γγ ℏ)2 S(S + 1)τm IS

proton−liquid in the proximity of a pore surface with paramagnetic relaxation sinks.7−9 In the fast diffusion limit, one can apply the biphasic fast exchange model where the exchange time between the surface and the bulk phases is shorter than their respective relaxation times; then a single proton−water relaxation rate R1,water =1/T1 exists as the following linear combination: R1,water(ωI ) =

1

⎡ ⎛ 1 + ω 2τ 2 ⎞ I m ⎟ × ⎢3 ln⎜ 2 2 2 ⎢⎣ ⎝ (τm/τs) + ωI τm ⎠ ⎛ 1 + ω 2τ 2 ⎞⎤ S m ⎟⎥ + 7 ln⎜ 2 2 2 ⎝ (τm/τs) + ωS τm ⎠⎥⎦

N 1 + surface N T1,2D(ωI)

T1,bulk Nparam 1 + N T1,param(ωI)

(2)

In eq 2, 1/T1,bulk ≈ 0.5 s−1, ωI and ωS = 659ωI are the proton and electronic Larmor frequencies, respectively, and γI and γS = 659γI are the gyromagnetic ratio of proton and electronic spins, respectively. The translational correlation time, τm, is associated with individual molecular jumps at the vicinity or on the pore surface. The surface residence time, τs (≫ τm), which is limited by the molecular desorption from the thin surface layer of the

(1)

In eq 1, because of the fast rotational water molecular motions the bulk relaxation term, 1/T1,bulk, has no proton Larmor 23216

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order of δwater, controls how long the proton species I and S stay correlated at the pore surface. The ratio τs/τm thus represents the dynamical surface affinity or NMR wettability. Though the water data are dispersed, one obtains a reasonable fit obtained with eq 2 over almost 4 orders of magnitude of the frequency as shown as a continuous line in Figure 7 (and inset).

longitudinal rate induced by a translational diffusion of a liquid confined in 1D cylindrical nanopores14 allows reproducing all the features shown in Figure 7: oil + R1,oil(ωI) = R1,bulk

ℏ)2 2 /(15πRδ1D,oil 2)σSρoil Sp,NMR (γγ IS

⎡ 2 2 ⎢ 3 1 + 1 + ωI τs S(S + 1) τmτs × ⎢ 1 + ωI2τs2 ⎢⎣ +

⎤ 1 + ωS2τs 2 ⎥ ⎥ 1 + ωS2τs2 ⎥⎦

7 1+

(3)

−1 where Roil has no frequency dependence in the range 1,bulk = 1 s studied,10 and the oil density is ρoil = 0.85 g/cm3. R ≈ 3.0 nm is the average radius of the kerogen nanopores,15,16 and δ1D,oil = δoil/2 is the distance of minimal approach between I and S spins where δoil is the average size of hydrocarbon (octane). The best fit obtained with eq 3 of our NMRD oil data shown as a dashed line in Figure 7 is obtained with Sp,NMR = 30 m2/g, τm = 4.1 ns, and τs = 0.78 μs (τs ≫ τm). An estimation of the translational diffusion coefficient of oil thus gives Dsurf = δoil2/(4τm) = 2.6 × 10−7 cm2/s in proximity of the kerogen pore surface. Theoretical Model for Interpreting the High Values of the Ratio T1/T2 for the Oil Phase. We applied a similar relaxation theory for obtaining expressions of 1/T2 for confined oil and water, in 1D and 2D pore geometries, respectively. This gives 2D an almost constant value for T2D 1,water/T2,water ≈ 1.36 for water confined in 2D mineral pores when τs varies between 8 and 0.6 μs at 2.5 MHz. This is exactly what we observed on another T1−T2 experiment realized on a pure water-shale rock. On the contrary, after neglecting Roil 1,bulk in eq 3 in comparison to the surface contributions, one obtains the following ratio, T1D 1,oil/ T1D 2,oil, for oil confined in 1D micropores of kerogen depending only on the time of residence τs at the pore surface, at a fixed Larmor frequency (2.5 MHz), and independently of all the other NMR parameters:

Figure 7. Measured logarithmic proton spin−lattice relaxation rate constants R1 as a function of the proton Larmor frequency for an oil/ water/air shale. The method proposed in the text has allowed assigning water and oil NMRD profiles. The continuous (water) and dashed (oil) lines are the best fits obtained with eqs 2 and 3, respectively. In the inset, we show in a semilogarithmic plot the bilogarithmic fit achieved with eq 2 of the water NMRD profile.

The best fit has been obtained with a constant value R1,bound = 50 s−1 in agreement with a water-wet phase at the mineral pore surface and with Sp,NMR = 47 m2/g, τm = 10.0 ps, and τs = 0.6 μs (τs ≫ τm). An estimation of the translational diffusion coefficient of water close to the mineral clay-like surface thus gives Dsurf = δwater2/(4τm) = 2.2 × 10−5 cm2/s corresponding exactly to what is expected for water at 25 °C. Theoretical Model for Interpreting the Oil NMRD Data. On the basis of our previous proton NMRD data in 1D pores of ettringite in cement pastes,14 the inverse-square root behavior with a leveling-off at low frequency shown as a dashed line in Figure 6a strongly supports a relaxation process induced by a quasi-1D-translational diffusion of proton−oil species in proximity of paramagnetic Mn2+ ions at the surface of kerogen micropores. Here again, the dominant feature of this relaxation process is the time dependence of the probability of reencounters between moving protons I and fixed paramagnetic spins S evolving at long times t as ∝1/t1/2. This gives the behavior R1 ∝ 1/√ωI observed in Figure 6a. The threedimensional (3D) microstructure of kerogen has been recently characterized with SEM and STEM imaging including FIB technique for removing very thin layers.15,16 The 3D microstructure is sponge-like with a high surface area and a huge number of quasi 1D connected kerogen pores of sizes ranging between 2.5 and 7 nm.15,16 This could look like a sort of fractal Menger sponge with a highly connected hierarchy of 1D channels. The following relationship that we proposed for the

1D T1,oil 1D T2,oil

⎡ ⎧ ⎪ ⎢1 + (3 2 /8) 1 + = 2 2⎨ ⎪ ⎩⎢⎣

1 + ωI 2τs 2

/ 1 + ωI 2τs 2 + (13 2 /8) 1 +

1 + ωS2τs 2

⎤ ⎡ / 1 + ωS2τs 2 ⎥ /⎢3 1 + ⎥⎦ ⎢⎣

1 + ωI 2τs 2

/ 1 + ωI 2τs 2 + 7 1 +

1 + ωS2τs 2

⎤⎫ ⎪ / 1 + ωS2τs 2 ⎥⎬ ⎥⎦⎪ ⎭

(4)

1D 1D Equation 4 shows that T1D 1,oil/T2,oil → 1 when ωI → 0 and T1,oil/ 1/2 1D T2,oil ∝ (ωIτS) at high frequency. We have displayed in Figure 1D 8 that the calculated τs variations of T1D 1,oil/T2,oil evolve from 10 to 5 values when τs varies between 8 and 1.7 μs at 2.5 MHz in good agreement with the observations of Figure 4a. We have 2D also displayed the calculated τs variations of T2D 1,water/T2,water that stays almost constant in good agreement with the observations of Figure 4a. On Figure 8, the range of τs values (1.7−8 μs) is larger than those found in Figure 7 due to the frequency dependence of the length of diffusion ldiff(ωI) = (2Dsurf/ωI)1/2,

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discussions. We thank C. Cassino and M. Botta (Università del Piemonte Orientale) for helping in the ESR measurement.

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(1) Singer, P. M.; Rylander, E.; Jiang, T.; McLin, R.; Lewis, R. E.; Sinclair, S. M. 1D and 2D NMR Core-Log Integration in Organic Shales. Society of Core Analysts, 2013; paper SCA2013-018, 1−12. (2) Ozen, A. E.; Sigal, R. F. T1/T2 NMR Surface Relaxation Ratio for Hydrocarbons and Brines in Contact with Mature Organic-Shale Reservoir Rocks. Petrophysics 2013, 54, 11−19. (3) Odusina, E.; Sondergeld, C.; Rai, C. A NMR Study on Shale Wettability. Society of Petroleum Engineers, 2011; paper SPE147371. (4) Washburn, K. E.; Madelin, G. Imaging of Multiphase Fluid Saturation Within a Porous Material via Sodium NMR. J. Magn. Reson. 2010, 202, 122−126. (5) Kimmich, R.; Anoardo, E. Field-Cycling NMR Relaxometry. Prog. Nucl. Magn. Reson. Spectrosc. 2004, 44, 257−320. (6) Hürlimann, M. D.; Venkataramanan, L. Quantitative Measurement of Two Dimensional Distribution Functions of Diffusion and Relaxation in Grossly Inhomogeneous Fields. J. Magn. Reson. 2002, 157, 31−42. (7) Korb, J.-P.; Whaley-Hodges, M.; Bryant, R. G. Translational Diffusion of Liquids at Surface of Microporous Materials: Theoretical Analysis of Field-Cycling Magnetic Relaxation Measurements. Phys. Rev. E 1997, 56, 1934−1944. (8) Korb, J.-P.; Freiman, G.; Nicot, B.; Ligneul, P. Dynamical Surface Affinity of Diphasic Liquids as a Probe of Wettability of Multimodal Porous Media. Phys. Rev. E 2009, 80, 061601−061612. (9) Barberon, F.; Korb, J.-P.; Petit, D.; Morin, V.; Bermejo, E. Probing the Surface Area of a Cement-Based Material by Nuclear Magnetic Relaxation Dispersion. Phys. Rev. Lett. 2003, 90, 116103−4. (10) Abragam, A. The Principles of Nuclear Magnetism; Clarendon: Oxford, U.K., 1961; Chapter VIII. (11) Solomon, I. Relaxation Processes in a System of Two Spins. Phys. Rev. 1955, 99, 559−565. (12) Bloembergen, N.; Morgan, L. O. Proton Relaxation Times in Paramagnetic Solutions Effects of Electron Spin Relaxation. J. Chem. Phys. 1961, 34, 842−850. (13) Korb, J. P.; Diakova, G.; Bryant, R. G. Paramagnetic Relaxation of Protons in Rotationally Immobilized Proteins. J. Chem. Phys. 2006, 124, 134910−6. (14) Dalas, F.; Korb, J.-P.; Pourchet, S.; Nonat, A.; Rinaldi, D. Surface Relaxivity of Cement Hydrates. J. Phys. Chem. C 2014, 118, 8387−8396. (15) Curtiss, M. E.; Ambrose, R. J.; Sondergeld, C. H.; Rai, C. S. Investigating the Microstructure of Gas Shales by FIB/SEM Tomography and STEM Imaging, 2011. http://www.ogs.ou.edu/ MEETINGS/Presentations/ShalesMoving2011/CurtisMicro.pdf. (16) Curtiss, M. E.; Ambrose, R. J.; Sondergeld, C. H. Rai, C. S. Structural Characterization of Gas Shales on the Micro- and NanoScales 2010. Canadian Unconventional Ressources & International Petroleum Conference, Calagary, Alberta, Canada, Oct 19−21, Paper CUSG/SPE 137693.

1D 2D Figure 8. Calculated variations of the ratio T1D 1,oil/T2,oil and T1,water/ T2D 2,water versus the time of residence τs at the different pore surfaces of both liquids in a 1D and 2D pore geometry schematized in the insets. The range of τs values corresponding to the observations of the T1/T2 ratios in Figure 4 is between the squared brackets.

which is highly localized at 2.5 MHz. The striking evolution of the central peak of the T1−T2 correlation spectrum (Figure 4a) as well as the large value observed for T1/T2 can thus be explained by the low dimensionality of the diffusion and the very long τS value for the oil phase at the huge kerogen pore surface.

IV. CONCLUSIONS Multidimensional (T1−T2) and multifrequency (T1(ω0)) nuclear magnetic relaxation techniques have proven useful for noninvasively probing the dynamics of oil and water confined in oil shales. We evidence a quasi-1D diffusing phase of oil confined within the organic kerogen micropores and a 2D diffusing phase of water confined in the mineral mesoporous layers. We observe an absence of exchange between these two populations of protons. Last, we probe the average hopping and residence times of petroleum fluids and assign signals to water and oil at both mineral and organic pore surfaces thus qualifying for the first time the local wettability of the two embedded fluids. The combination of these NMR techniques gives an invaluable tool for investigating the oil and gas recovery on these important porous rocks.

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REFERENCES

AUTHOR INFORMATION

Corresponding Author

*(J.-P.K.) E-mail: [email protected]. Author Contributions

The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS J.-P.K. thanks the scientific direction of Total for financial support. We thank G. Hamon (Total) for stimulating scientific 23218

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