Introduction

Technological solutions have been designed to meet the global demand for energy and environmental sustainability, including enhanced hydrocarbon recovery1,2,3,4, geo-sequestration of carbon dioxide5,6, security of CO2 storage7,8, remediation of nonaqueous phase liquid contaminants in aquifers9. Overcoming major challenges in these processes relies, to a significant extent, on the understanding of how immiscible fluids interact with solid surface within porous rocks and soil10,11,12.

Interfacial phenomena in multiphase fluid flow become quite complex if the porous rock is chemically and physically heterogeneous. A further complication is the alteration of the original wettability of pore surfaces caused by the formation of “contaminant” layers throughout the rock11,13. For instance, the adsorption or deposition of heavy components of crude oil on a mineral surface has long been recognized as wettability modifiers14,15,16,17,18,19,20.

Significant progress towards a deeper understanding of wetting behavior of porous rocks was made with the employment of three-dimensional (3D) X-ray imaging techniques21,22,23,24,25,26,27. X-ray microtomography (XRT), in particular, allowed for measuring the in situ wettability of reservoir rocks at subsurface conditions13,21,25,27. With the use of XRT approaches, contact angle measurements between fluids and pore surfaces provided direct evidence of the mixed-wettability even in mineralogically homogeneous rocks11,13. Recently, the mixed-wet state of porous rocks has been associated with variations in surface roughness11,13. It was found that the contact angle tends to be lower on rougher surfaces due to the accumulation of water in crevices, what makes the surface more hydrophilic11.

Despite the great advances achieved with XRT approaches, imaging of molecular substances (such as water and oil) using X-ray absorption-based techniques provide poor contrast28. These techniques are based on the differences in attenuating power of the analyzed materials29, resulting on imaging contrast during acquisition. As the x-ray beam passes through the sample, photons get absorbed; this is known as attenuation. Much of this effect is related to the photoelectric effect. The probability of photoelectric absorption is strongly related with atomic number (Z) and is dependent on density (ρ) and thickness of the materials present in the sample29. In the context of porous rocks, XRT allows for imaging the 3D distribution of minerals, pores, and fractures usually with excellent contrast30; however, imaging molecular substances that exhibit low values of Z and ρ results in a poor contrast28,29.

Unlike X-rays, neutrons interact weakly with most minerals, but strongly with small amounts of hydrogen or, more precisely, hydrogen-containing substances31. However, neutron imaging has been limited to the investigation of coarse-grained materials due to its low spatial resolution32. Current developments of more sensitive detectors, such as cooled CCD detectors with an improved sensitivity, has led to significant improvements in spatial resolution reaching about 10 µm33. High-resolution neutron tomography (NT), with a level now comparable with XRT, emerges as a powerful technique to study the 3D distribution of hydrogen-containing phases (such as water and oil) in real systems in situ. This capability results from the high interaction cross section of hydrogen atoms for cold neutron scattering31.

Accordingly, we present a novel approach to probe the 3D interfacial characteristics of complex porous rocks using combined high-resolution neutron (NT) and synchrotron X-ray tomography techniques. The achieved spatial resolution of the neutron tomography (pixel size of 10 µm) combined to its extremely high sensitivity to hydrogen allowed us to resolve adsorbed or deposited molecular “contaminant” layers on the pore surface. Retrieving the 3D distribution of neutron attenuation coefficients of reservoir rocks by Monte Carlo simulations, we could unambiguously distinguish between water and oil phase through the sample volume. The coupling of high-resolution XRT and NT can be used as a platform to explore a huge range of interfacial phenomena, providing information that is not possible to obtain using other characterization techniques.

Results and Discussion

Conventional characterization of a complex porous rock

We investigated a fine-grained sandstone reservoir rock, which contains predominantly quartz (SiO2) and orthoclase (KAlSi3O8), with minor amounts of muscovite (KAl2(Si3Al)O10(OH,F)2) and albite (NaAlSi3O8). Elemental composition maps obtained by scanning electron microscopy coupled to energy dispersive x-ray spectroscopy (SEM-EDS) confirms that larger grains of about 100–250 µm were mostly composed of Si, O, Al, and K (Fig. 1a), whereas localized concentrations of Fe associated with S as well as Ti, Mn, Nb, and Ca could be noticed for smaller structures (Fig. 1b). Punctual analysis using electron probe microanalysis (EPMA) were performed in those small structures (Fig. 2). Figure 2 shows a representative mica grain holding inclusions in the interlayer region. These inclusions are mostly composed of species with high concentration of Fe and S (indicated by numbers 4 and 5 in Fig. 2).

Figure 1
figure 1

SEM image (from backscattered electron detection) of the sandstone rock and associated elemental maps. (a) Large grains mainly composed of Si, O, Al, K, and Na. Scale bar: 300 µm. (b) Enlarged view of the central region in (a). Scale bar: 50 µm.

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Figure 2
figure 2

SEM image of a mica grain with inclusions acquired from backscattered electron detection with punctual regions analyzed by electron probe microanalysis (WDS – wavelength dispersive spectroscopy). The inserted table shows the quantitative analysis of elemental content represented, as usual, as simple oxide phases. Numbers in the figure indicate the analyzed points.

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In addition, infrared spectroscopy was applied to probe que chemical components in a pulverized rock sample. The analyzed specimen was prepared as a KBr pellet and the collected spectra is presented in Fig. 3. The whole view from 400 to 4000 cm−1 evidence different bands associated with both the minerals phases and asphaltenes. The strong bands from 400–1300 cm−1 region are associated with the minerals, quartz, orthoclase and albite19,34,35. The wide band around 3500 cm−1 is attributed to the typical –OH stretching, present in the muscovite phase, water and asphaltenes. On the central region from 1300–3000 cm−1 are observed several medium and week bands attributed to the minor component asphaltenes. The asphaltenes are a complex mixture of organic compounds found in the crude oil which are often impregnated into these porous rocks. The organic structure is constituted by aliphatic and romantic chains with oxygen, nitrogen, and sulphur. These asphaltene bands are assigned on the table of Fig. 3, resulting mainly from stretching and bending of such aromatic and aliphatic structures19,34,35.

Figure 3
figure 3

Infrared spectra (FTIR) acquired from the pulverized porous rock, evidencing minerals phases and asphaltene (upper spectra). The asphaltene bands are assigned on the bottom spectra.

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Revealing the rock heterogeneity by combined neutron and X-ray tomography

The sandstone rock sample was evaluated by both XRT and NT techniques, providing complementary information on its main constituents (Fig. 4). The image contrast obtained using X-rays reveals variations in density and atomic number; and the contrast provided by neutrons reveals the distribution of hydrogen-containing materials such as water and oil33.

Figure 4
figure 4

Three-dimensional images of the sandstone rock obtained using synchrotron X-ray tomography (a) and neutron tomography (b). Comparison between cross-sectional images of the synchrotron X-ray tomography volume (c) and neutron tomography data (d). The upper diameter and height of the sample are about 6 and 14 mm, respectively.

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From the intensity profile obtained by synchrotron XRT, at least three phases and the pore space could be clearly distinguished (Figs 4 and S2). Based on the theoretical attenuation coefficient (µth) of minerals36, we could associate the brightest regions of the images mostly to mica and inclusions (Fig. S2-d). Dark gray covers quartz and albite together (Fig. S2-b); these minerals could not be distinguished due to their small difference in attenuation coefficient36. Intermediate gray levels correspond to orthoclase (Fig. S2-c)36. The quantitative analysis of the X-ray images showed that the volume fractions of quartz together with albite, orthoclase, and mica are 51.2%, 21.7%, and 2.2%, respectively. The total porosity computed from the X-ray images is about 24.9% (Table 1). By considering only the mineral phases (excluding pores), the volume fractions of quartz plus albite, orthoclase, and mica are 68.2%, 28.9%, and 2.9%. These results are in good agreement with the Rietveld X-ray diffraction quantitative analysis, which indicates 70.2% of quartz plus albite and 30.3% of orthoclase. These results are exhibited in Table S1 (Supplementary Information Appendix).

Table 1 Quantitative analysis of the X-ray images revealing the volume fraction of the mineral phases and pores.
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Complementing the X-ray results, neutron imaging reveals the distribution of hydrogen-rich materials in the sample (bright regions of Fig. 4b). For providing chemical information on the constituents of the sandstone sample, we computed the neutron attenuation coefficient (Σm) for each voxel (11 µm × 11 µm × 11 µm) of the reconstructed volume using Monte Carlo simulations37. This approach enables us to unambiguously distinguish the hydrogen-containing substances between hydrous minerals (such as mica), aqueous and non-aqueous phases because their attenuation properties differ largely in a cold monochromatic neutron beam38.

The distribution of the measured attenuation coefficients varies from values typical of pores (the absence of materials, Σm = 0 cm−1) to those produced by highly attenuating materials to neutrons (Σm ≈ 1.70 cm−1) (Fig. 5). Four classes of Σm values could be segmented: (i) Σm < 0.12 cm−1 accounting for 16.5% of the sample volume (highlighted in Fig. 5b); (ii) 0.12 ≤ Σm < 0.40 cm−1 with a volume fraction of 55.3% (Fig. 5c); (iii) 0.40 ≤ Σm < 0.65 cm−1 with a volume fraction of 24.2% (Fig. 5d), and (iv) Σm ≥ 0.65 cm−1 exhibiting nearly 4% of the total volume (Fig. 5e).

Figure 5
figure 5

Neutron image segmentation of the sandstone rock sample. The distribution of measured attenuation coefficients of a selected representative image (a) is divided in four classes: (b) Σm < 0.12 cm−1, (c) 0.12 ≤ Σm < 0.40 cm−1, (d) 0.40 ≤ Σm < 0.65 cm−1, and (e) Σm ≥ 0.65 cm−1.

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It should be noticed that the predominant minerals of the rock (i.e., quartz, orthoclase, and albite) exhibits values of Σm between 0.12 cm−1 and 0.65 cm−1 (Fig. 5c). The average Σm of these limits (0.265 cm−1) agrees well with the theoretical attenuation coefficients (Σth) of quartz (Σth = 0.287 cm−1), orthoclase (Σth = 0.260 cm−1), and albite (Σth = 0.280 cm−1)39. Voxels exhibiting Σm in the range of 0.40 and 0.65 cm−1 can be explained by the presence of hydrogenous substances in small pores which cannot be resolved by neutron tomography due to its limited spatial resolution (Fig. 5d). The attenuation coefficients ranging from 0.65 cm−1 to 1.7 cm−1 correspond to hydrogen-rich materials with varying concentration of hydrogen (Fig. 5e). This range of Σm includes hydroxide minerals such as muscovite (Σth is 0.935 cm−1) and aggregations of crude oil components. From the FTIR analysis (Fig. 3), we could ascribe these aggregations to asphaltenes40. In addition, the fact that asphaltene is not a single compound, but a compound class, may explain the observed variations in Σm in the range of 0.65 cm−1 to 1.7 cm−1 (Fig. 5d).

Asphaltenes comprises a complex mixture formed by molecules which contrast sharply in polarity and structure from the majority of the crude oil components, which accounts for their predisposition to self-aggregation and adsorption at surfaces19,40. In practice, this leads to undesirable consequences, such as the deposition and wettability alteration during crude oil extraction, production, and refining19,41. Several authors investigated the tendency for wettability alteration with the adsorption/deposition of asphaltenes on flat and homogeneous mineral surfaces by contact angle measurements and atomic force microscopy15,19,40,41,42,43,44. Unlike the previous studies, this work presents a novel approach to directly visualize the 3D distribution of crude oil components and aqueous phases. This approach will enable to study the influence adsorbed/deposited water or oil components on fluids flow and finally the displacement efficiency.

In order to reveal the location of adsorbed and/or deposited asphaltenes in the sandstone reservoir rock, 3D rendered X-ray and neutron volumes were superposed as shown in Fig. 6. Figure 6a exhibits the 3D rendered surface of the high-absorbing particles to X-rays (mica grains and heavy inclusions); Fig. 6b, the aggregations of asphaltenes extracted from the neutron volume; and Fig. 6c, the superposed images revealing that asphaltenes are mostly located on the mica grains and their surroundings. The rendered surface of oil aggregations was also superimposed on the X-ray cross-section in Fig. 7. Besides the interaction between the mica grains and asphaltenes, we could observe that some pores were filled with oil (Fig. 7). This agrees well with the reduced porosity computed for the neutron volume compared to the X-ray data (16.5% and 25.0%, respectively). The mica-asphaltenes interaction can be rationalized in terms of the mica structure and its chemical properties. Mica is a phyllosilicate mineral of aluminum and potassium with a highly perfect basal cleavage and a lamellar morphology. It is well known that this lamellar structure promotes strong interfacial binding due to van der Waals (vdW) interactions, for example, with graphene layers15. These vdW interactions can be the predominant adhesion forces between the mica grains and the asphaltenes.

Figure 6
figure 6

Direct evidence of the interaction between mica grains with crude oil components. Three-dimensional images of a slab of the sandstone rock. (a) 3D X-ray surface-rendered image indicating the distribution of the mica grains. (b) 3D neutron surface-rendered image highlighting the distribution of aggregations of oil components. (c) Both images superimposed, where the good matching suggests a mica-oil interaction.

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Figure 7
figure 7

Pore filling and mica-asphaltenes interactions. X-ray cross-sectional image (a) and this image overlaid by the rendered surface of oil aggregations extracted from the neutron volume (b). Higher magnification of the figures (a,b) are displayed in (c,d), respectively.

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In summary, we could distinguish between two types of inclusions containing hydrogen: i. fine inclusions within micropores (with size below the resolution of the neutron imaging) in minerals with a volume fraction of about 24.2% (Table 2); and ii. large ones with approximately 2% volume fraction (subtract the volume fraction of hydroxide minerals from the voxels exhibiting 0.65 < Σm ≤ 1.7 cm−1). Due to the presence of adsorbed and/or deposited crude oil components, we can infer that a significant portion of the minerals surface in the rock sample is preferentially wetting to a nonaqueous phase. This information is of paramount importance for the modelling and quantification of flow and transport in porous rocks. Therefore, the combined X-ray and neutron imaging approach provides a deeper understanding of the rock heterogeneity and the factors that affect its wettability pattern. The ability to properly characterize such complex systems at the pore level can be used to explore a huge range of phenomena in the energy and environmental arenas.

Table 2 Quantitative analysis of the neutron imaging revealing the volume fraction of the segmented phases.
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Conclusions

In this work, we present a novel approach for probing in situ the physical-chemical characteristics of complex porous rocks by the combined use of high-resolution X-ray and neutron tomography. Further, the distribution of measured neutron attenuation coefficients of the sample was retrieved from the intensity profiles using Monte Carlo simulations. This permitted to chemically distinguish the hydrogen domains between water, crude oil components, and hydroxide minerals (such as muscovite).

Here, we characterized a fine-grained and mineralogically heterogeneous sandstone rock from a producing oil reservoir. This sample is composed mostly of quartz, orthoclase, albite, and narrow flakes of mica. The complementarity of X-ray and neutron imaging enabled us to reveal for the first time the 3D distribution of crude oil components (asphaltenes) and their strong preference for the mica grains. Additionally, 10% of the porosity observed in the X-ray images were filled with crude oil components.

Besides the wetting behavior of natural porous systems, this approach paves the way for understanding rocks and fluids interactions. Such situations are conceivable across a broad range of extraction, separation, or contamination processes or phenomena involving immiscible fluids.

Materials and Methods

Porous rocks

Three sandstone core samples of about 7 mm in diameter and 10 mm in height from a producing oil reservoir were chosen for this study. They are principally composed of quartz (SiO2) and orthoclase (KAlSi3O8), albite (NaAlSi3O8), and minor amounts of muscovite (KAl2(Si3Al)O10(OH,F)2). The diffraction pattern of this sample is presented in Fig. S1 in the SI Appendix. In addition, quantitative phase analysis of the sample was performed using Rietveld refinement. Based on the diffraction pattern of the sandstone rock, the volume fraction of quartz, albite, and orthoclase were 39.9%, 30.3%, and 30.4%. respectively. The low amount of muscovite in the sample could not be accurately quantified by XRD.

Chemical and structural characterization of the sandstone rocks

Elemental mapping analysis of the rock samples were obtained using energy-dispersive X-ray spectroscopy (EDS) and wavelength-dispersive X-ray spectroscopy (WDS) in a JEOL 8900 electron microprobe. The infrared absorption spectra were recorded with a spectrometer 1760X Perkin-Elmer with Fourier Transform in the region of 400–4000 cm−1 with a resolution of 0.01 cm−1 by using KBr pellets.

Imaging rock and fluids interactions

We combined high-resolution neutron and synchrotron X-ray tomography to explore rock-fluid interactions in an oil reservoir rock. Whereas neutron imaging provides high contrast of hydrogen-rich substances45, the contrast of the images obtained using X-rays allows to differentiate mineral phases based on variations in both atomic number and density46.

Tomography experiments were performed at Helmholtz-Zentrum-Berlin für Materialien und Energie (HZB), in Berlin/Germany33,47. HZB operates two scientific large-scale facilities for materials investigation: the research reactor BER II for experiments with neutrons and the third-generation synchrotron photon source BESSY II. Fully dedicated instruments for materials imaging are provided by these facilities; particularly, the BAMline/BESSY II47 and the CONRAD-2/BER II33. The neutron and X-ray images achieved a spatial resolution of approximately 22 μm (11.2 μm/pixel) and 4 μm (2.2 μm/pixel), respectively. Further details on the experimental conditions are presented in Table 3.

Table 3 Experimental conditions used in the tomography experiments.
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The visualization and quantitative analysis of the reconstructed volumes were performed using Thermo Scientific™ Avizo™ Software (ThermoFisher Scientific, Oregon/USA). For the simultaneous visualization of the mineralogical and molecular characteristics of the rock sample, the X-ray and neutron volumes were aligned into the same coordinate system. For that, it was used a reliable image registration method available in Thermo Scientific™ Avizo™ Software. The registration of the two 3D data sets (i.e., XRT and NT volumes) was based on the position of specific pores which were used as markers. Independently on the imaging technique, pores always correspond to the darkest voxels. Thus, a set of large pores were selected for the image registration procedure and the centers of gravity (CG) of individual pores were computed for the XRT and NT volumes. The XRT volume was then rotated and translated with respect to the NT volume (reference) until a good matching is obtained based on the position of CGs of the individual pores. The optimized alignment was determined by a volume-matching quality measure which is a function of the differences in CG position of each pore.

For measuring the uncertainties of the quantitative analyses based on the XRT and NT data sets, voxel intensities (gray values) of different grains associated with a specific phase were used to calculate the average value and standard deviation. Approximately, 2500 voxel intensities were analyzed for each phase. Subsequently, volume fractions and porosity were recalculated varying the user-defined threshold limits by subtracting and adding the standard deviation. This process led to the uncertainties expressed in Tables 1 and 2.

The chemical analysis of the neutron tomography data was supported by Monte Carlo simulations which provided the theoretical values for the neutron attenuation coefficients of the minerals presented in the sample. The complex mineral composition and the multiparameter experimental conditions required more sophisticated model of the neutron interaction with matter. For this purpose, it was used the Monte Carlo N-Particle (MCNP) Transport Code (Los Alamos National Laboratory, U.S. Department of Energy’s NNSA) with full description of the material (composition and density), the geometrical parameters (sample size, source-sample and sample-detector distances) and the beam properties (neutron spectrum and beam divergence)37. The value of the attenuation coefficient for each mineral was calculated in cm−1 units; therefore, the voxel values from the tomography experiments were converted in the same units (cm−1). A computation procedure based on thresholding of the experimental tomography volumes using the theoretical values from the MCNPX simulations allowed for retrieving the 3D distribution of the different minerals and molecular substances in the rock sample. In addition, cross-check calculations were performed using the Neutron activation and scattering calculator provided as online service by NIST39; the theoretical attenuation coefficients were computed using a single neutron wavelength (0.25 nm – the maximum in the neutron spectrum) without any geometrical parameters (Table S2, SI Appendix). The results from the two methods agreed in the range of 2%, confirming the reliability of the calculated values for the mineral’s attenuation coefficients.