Microscopic and Fractal Characterization of OrganicMatter within Lacustrine Shale Reservoirs in the FirstMember of Cretaceous Qingshankou Formation, Songliao Basin, Northeast China

Pore sizes in shale are mainly in the micron-nanometer ranges. Although there are various methods for characterizing pore structures, their accuracy and measurement range vary because of different analytical principles. Optical microscopy (polarized light microscopy) is a commonly used method for the direct observation of pore structures at micron scale (Liu et al., 2020, 2018; Misch et al., 2019). By using polarized light microscopy on thin sections, the two-dimensional structures of pores including pore size, shape, type, distribution and connectivity, can be observed (Bultreys et al., 2016; Anovitz and Cole, 2015). It should be noted that the theoretical resolution of an optical microscope is up to 0.2 μm, and the thickness of the thin section that is commonly used under such type of microscope is 0.03 mm. This means the pore throat is less than the thickness of the thin section (Chalmers et al., 2012). The light source used for optical microscopy casts light onto the surface of thin section, and the resultant reflecting light from the matrix and blue dyed epoxy, can interfere with each other. The result from this interference causes a low quality and unclear image. Thereby, the resolution and sharpness of the image will get affected. The structure of pores cannot be displayed clearly because of the overlap in optical imaging (Al-Ostaz et al., 2008). As a result, it is difficult to observe the structure of micro-pores (< 10 μm) clearly using polarized light microscopy, especially with the image based quantitative analysis of the micro-pores (Liu et al., 2018; Bultreys et al., 2016).

In addition, the occurrences including abundance, size, and spatial distribution of hydrocarbon within shale reservoir are significant for understanding the shale oil potential (Lu et al., 2012). Previous studies have explained that shale gas often exists in three phases, including free phase in natural fractures and pores, absorption phase on the surface of kerogen and clay, and dissolved phase in water, kerogen or asphalt (Wu et al., 2013; Zou et al., 2013; Huang et al., 2012; Curtis, 2002). Free gas can be calculated with PVT equations based on gas saturation and porosity, while the adsorbed gas can be calculated by the Langmuir Equation at different temperatures and pressures (Gasparik et al., 2014; Xia and Tang, 2012). Furthermore, quantities of the dissolved gas, can be calculated according to the dissolution mechanism and solubility equation (Fu et al., 1996). However, there might not be any sharp difference or boundary between the adsorption state and the dissociated shale oil because of the complex components of organic matter (OM) and the theory of "Like Dissolves Like" (Montes et al., 2003). High-resolution scanning electron microscopy (SEM) also rarely observes oil in nano-pores within shale samples (Katz and Arango, 2018). To date, there has not been any effective microscopic method to evaluate quantitatively the characteristics of OM in shale oil reservoirs.

In order to solve the above problems, we integrated confocal laser scanning microscopy (CLSM) and quantitative fluorescence detecting technology (Liu et al., 2018; Chi et al., 2017; Kus, 2015; Li et al., 2014; Mauko et al., 2009). The laser has the advantages of small divergence, high monochromaticity, strong directionality, high brightness, and good coherence. Additionally, the laser is capable of scanning and imaging point by point, line by line, and face by face. By using CLSM, the interference caused by light scattering can be avoided effectively. Compared with conventional optical microscopy, CLSM method has several advantages, such as simple sample preparation and high resolution that can not only observe the internal structure of the sample but also reconstruct 3D images. In addition, digital information can be obtained to process quantitative analyses of pore structure (Bankole et al., 2019; Blaga, 2012; Bustin, 2012). In this regard, through multilayer scanning and 3D reconstruction, complete structural information of all micropores in the sample can be obtained, while is beyond the ability of common SEM methods (Ambrose et al., 2010). Based on the analyses of pore structure, the fractions of OM in the pores or between mineral particles can also be quantified through fluorescence spectral analysis.

In this study, 3D CLSM technology was used to study micro-pore structures and OM occurrences in different lithologies that were deposited in the fine-grained sedimentary system of the Qingshankou Formation, Songliao Basin. Aggregation of micropores and different fractions of OM with a diameter of more than 0.1 μm can be obtained, and minimum recognizable scale is 35 nm. Based on statistics and fractal analyses, a quantitative discrimination of OM within Qingshankou shales was investigated to provide insights into occurrences of different fractions of OM.

The Songliao Basin is located in the north of the Pacific Rim between Siberia and the Sino-Korean platforms, being one of the most important petroliferous basins in Northeast China (Fig. 1a). The Songliao Basin is a continental sedimentary basin, dominated by Jurassic and Cretaceous formations, with an area of about 260 000 km². The Cretaceous strata are widely distributed in the Songliao Basin, with large sedimentary thickness, and are the main source and reservoir rocks of the basin (Fig. 1b).

Figure 1.  (a) Sketch map showing the location of the study area in the central depression; and (b) diagram showing the lithological characteristics of the drill site.

During deposition of the first member of the Qingshankou Formation (qn1 in Fig. 1c) in the Songliao Basin, as the hydrodynamic force of paleosedimentary environment weakened gradually, the sedimentary facies transited from delta to lacustrine. The Qingshankou Formation is characterized by interbedded lacustrine siltstones and mudstones. The black mudstones, including organic-rich shale formed in semi-deep and deep lake facies, were developed sequentially. The content of total organic carbon (TOC) in these shale samples ranges mainly between 1 wt.%–10 wt.%, with an average of 2.0 wt.%, which indicates that the OM abundance is high. The main macerals found in the shales are lamalginite with strong fluorescence of green to yellow colors. A combination of types I and II kerogen, indicates that the generative potential for oil is very good (Liu et al., 2019) and the OM is in the low to mature stage (Ro ranges from 0.5% to 1.2%; Liu et al., 2017), suggesting a great shale oil potential. The maturity increases with depth, and the Ro value reaches 0.8% at the depth of 1 500 m, 1.0% at 2 000 m and 1.4% at about 2 400 m.

The X-ray diffraction (XRD) and carbon analyses were performed on all 15 samples by Liu et al. (2019) to obtain mineralogical data and TOC values using a Bruker D8A diffractometer and Eltra Helios CS elemental analyzer, respectively. For the present study, all these 15 samples were observed and analyzed for the fabric, mineral composition and pore structures under polarizing microscope. In addition, fluorescence analysis was conducted to observe the distribution and emission color of OM in the pores and between mineral particles. Finally, the occurrences of different fractions of OM were observed by CLSM and characterized by fractal method.

Samples including fine sandstone, silty sandstone, silty mudstone, mudstone and ostracoda limestone were selected within the first member of the Qingshankou Formation to evaluate the OM occurrences (Table 1). Additional details about the sedimentary descriptions and related photographs of the lithofacies can be found in Liu et al. (2019). To maintain the original state of the oil and water in pores, the oil-bearing samples cannot be soaked within organic solvents and should be cryopreserved in liquid nitrogen. In the process of thin section preparation, samples also need to be drilled and sliced under freezing conditions (Li et al., 2014). The sliced samples were air dried at temperatures below 5 ℃, and then glued in a vacuum environment with 502 glue. During sample preparation, mechanical polishing parallel to the bedding plain in particular, if there are any loose aggregates, glue should be applied to rebind the particles until all free space is filled with epoxy resin.

The laser confocal model used in this study is a LEICA SP5II, which needs to be warmed up for 0.5–1 h after booting. The scanning laser and a full-spectrum fluorescence collection share the objective lens. A conventional high-pressure mercury lamp was used with an excitation wavelength ranging between 200–400 nm (i.e., ultra violet light) to obtain epifluorescence. Using a range of wavelength leads to unknown exact wavelength that excites the fluorescence. To avoid this uncertainty, a constant excitation wavelength of laser at 488 nm (i.e., blue light) was applied in this study. With a specific wavelength laser as the launching light source, two-dimensional (2D) images of the samples can be obtained. The scanning times of image should be determined according to the data volume and the image effect. In the detection of micro-pores and organic matter, the objective lens is generally selected to be a large multiple, such as 10, 20, and 50 times. The instantaneous imaging point is a function of the focal point of both the objective lens and scanning laser (Li et al., 2014; Mauko et al., 2009). Images at different depths within the thin section can be obtained by changing the depth of focus and stored in a computer (Orangi et al., 2011) to create three-dimensional (3D) structure of the samples (Kus, 2015).

In traditional experimental observations, it is believed that the color of fluorescence reflects the maturity of hydrocarbons (Munz, 2001; Stasiuk and Snowdon, 1997). As hydrocarbons evolve from low to high maturation, fluorescent color changes from red, yellow, orange, green to blue (i.e., blue shift). Also, through maturation, as OM progresses from heavy to light, the fluorescent color changes from brown, orange, yellow, to green (Goldstein and Reynolds, 1994). When the proportion of small- molecule (i.e., light components) and the maturity increases, the fluorescence will undergo a "blue shift", and the peak of the wavelength spectrum of fluorescence will decrease (Przyjalgowski et al., 2005). On the contrary, the peak of the wavelength spectrum will increase in case of more proportion of heavy components. The light components of the OM will produce a fluorescence signal in the wavelength ranges from 490 to 500 nm, whereas heavy components between 680 and 710 nm (Li et al., 2014). Therefore, the fractions of OM can be recognized as light and heavy components by a cutoff fluorescence wavelength of 600 nm. Based on these characteristics, this method could also be used to calculate the density of homogenized oil inclusions by the fluorescence intensity of the spectra from 500 to 800 nm (Chi et al., 2017).

The fractal model has been widely applied in geological studies to characterize the geometry of complex non-Euclidean shapes, especially the geometry of rock pores (Wu et al., 2019; Mandelbrot, 1967). In 3D modeling of CLSM, each OM was analyzed as a solid unit to obtain quantitative parameters such as volume, radius and the total number. According to the fractal geometry principle, for the occurrences of light and heavy components with fractal characteristics, the number of OM with radius larger than r which is abbreviated as N (≥r), has a power function relationship with r, i.e.,

where, r_max is the maximum radius of the OM in the reservoir and D is the fractal dimension of OM occurrences. Taking the logarithm of both sides of Eq. (1) will result

Based on Eq. (2), ln N has a linear relationship with ln r, and the absolute value of its slope is the fractal dimension D of OM occurrences.

The main minerals of Qingshankou shale are quartz and feldspar (Table 1). The silt stones have the highest content of quartz and feldspar, ranging from 84.2% to 100.0%. The content of quartz and feldspar of silty mudstones wildly ranges from 48.8% to 90.9%, indicating the appearances of silty lamina. The "pure" mudstones have moderate quartz and feldspar content that varies between 76.5% and 76.8%. Limestone is dominated by carbonate (Fig. 2). In addition, both the siltstones and limestones are characterized by low TOC values which are mostly less than 0.5%. The mudstones have the higher TOC values which were more than 1.0% compared to silty mudstones. The TOC and XRD data sets show that the TOC values have a positive correlation with clay content.

Figure 2.  Ternary diagram showing the mineral compositions of Qingshankou shale oil reservoir in the Songliao Basin.

In this study, the fractions of OM were recognized as light and heavy components by a cutoff fluorescence wavelength of 600 nm. It is important to relate these two fractions with OM types based on their geochemical characteristics. Kerogen is defined as OM "that is soluble neither in aqueous alkaline solvents nor in the common organic solvents" (Milliken et al., 2013; Tissot and Welte, 1984). Bitumen is defined as a soluble OM and subdivided into hydrocarbons and NSO (nitrogen, sulphur, and oxygen) compounds (hydrocarbon heterocyclic compounds containing variable amounts of nitrogen, sulphur, and oxygen; Milliken et al., 2013). Based on previous studies (Liu et al., 2019, 2018; Chi et al., 2017; Li et al., 2014), the light components of OM are similar to hydrocarbons when aliphatic and aromatic compounds in it are dominant which was the case here too. Likewise, heavy components would consist of polar NSO compounds in hydrocarbon and partly kerogen (i.e., liptinite) associated with bright yellow fluorescing oil droplets (Gorbanenko and Ligouis, 2014). Although fluorescence reflectance can be caused by other fluorescence macerals and minerals (Liu et al., 2018), numerous OM are discernable by their much brighter fluorescence than the background (Chi et al., 2017; Shah et al., 2013).

The distribution of mineral particle size under the microscope is heterogeneous based on confocal large field imaging (Fig. 3). The mineral particles with different diameters are rich in laminations on the order of millimeters, parallel to the stratification. The light components are concentrated mainly in interparticle pores between coarse mineral grains and distributed in a laminar pattern and the heavier components are relatively more widely distributed without any clear stratification (Fig. 4).

Figure 3.  Microphotographs showing the laser confocal analyses of the laminated mudstone. (a) Mineral grain reflected-light morphology; (b) short-wave fluorescence, which was defined as light components; (c) long-wave fluorescence, defined as heavy components. The color bars of (b) and (c) show the strength of fluorescence, indicating the distribution of different components of OM. The white dashed lines separate the fine-grained and coarse-grained laminae, showing the parallel distribution of light components in the interparticle pores.

Figure 4.  Confocal laser scanning photomicrographs showing the 3D pore structure of silty and clayed laminae. The images were obtained using a 20X objective lens with microscope. Yellow-dot lines show the laminations. Red color indicates light component, blue indicates heavy component, and green indicates detrital mineral.

Based on the 3D modeling results that are summarized in Table 2, it is found that the occurrences of light and heavy components are related to the fabric of samples. In siltstone and silt-laminae within silty mudstone (Figs. 5a and 5c), the proportion of light components (colored red in Fig. 5) is significantly higher than heavy components (colored blue in Fig. 5). The heavy components do not appear alone but overlap with light ones, which were colored purple in 3D models (Fig. 5). Other silty mudstones are clearly different in light and heavy components. The difference originates from the laminated mudstones that have long-wave fluorescence, indicating the appearance of organic-rich lamina (identified as lamalginite based on its shape, color and aggregates), which has been indicated by fluorescence photomicrographs (Fig. 5d). In mudstones, the diameter of OM is much smaller than OM of the siltstone and silt-lamina lithofacies (Figs. 5b, 5e and 5f). We infer the long-wave fluorescence to represent liptinite macerals (Liu et al., 2018). Unlike previous studies (Li et al., 2014), the analysis of oil inclusions in heavy component obtained by the same method include the kerogen in organic-rich shale.

Figure 5.  Microscopic characteristics of OM within the typical lithology of the first member of Qingshankou Formation. Each pair of photomicrographs from the same sample, the left one is fluorescence micrograph and the right one is 3D model based on CLSM. In the fluorescence micrographs, light components occur as hydrocarbons in interparticle pores, and exhibit blue fluorescence; heavy components occur as bitumen and macerals, represented by orange fluorescence. In CLSM models, the short-wave fluorescence marked in red color indicates light components, and long-wave fluorescence in blue color heavy components. Purple color is the overlapping of short and long wave fluorescence. (a), (b) Siltstone; (c), (d) laminated silty mudstone, lamalginite exhibits different fluorescence strength, while brighter lamalginite often is associated with bright yellow fluorescing light components; (e), (f) mudstone. The photomicrographs and OM models show larger diameter of OM within siltstone and silt lamina than OM within mudstone and clay lamina. OM. Organic matter; LC. light components; HC. heavy components; OC. overlapping of light and heavy components; lamalg. lamalginite.

In general, the proportion of light components is less than 25% based on the entire pore volume, while the proportion of heavy components is less than 5%, and the light components content of each sample is higher than its heavy components content (Table 2). We numbered the samples from siltstone to mudstone (Table 2) where with the increase trend in particle size and TOC content, the proportion of light components also increases, and the light components become more evident. In contrast, the heavy components are dominated relatively in the mudstone and mud-lamina (Fig. 6). Based on the fluorescence analysis results (Figs. 5a and 5c), the inter-pores between coarser mineral particles often show blue fluorescence, indicating more abundance of light components. On the contrary, the reservoir space within mudstone and clay lamina is hardly observed, and the fluorescence is not bright. However, it should be noted that the content of light components varies distinctly (number 1 to 5 in Fig. 6), suggesting high reservoir heterogeneity of silt stones caused by diagenesis (Zhou et al., 2019).

Figure 6.  Diagram showing the relationship between lithology and light/heavy components. Sample numbers correspond to the lithology based on Table 1.

The content of heavy components is not related to the mineral composition in all samples where with the increasing content of quartz and feldspar, the content of heavy components does not change significantly (Fig. 7). However, there is a relatively weak positive correlation between the quartz content and light components proportion. And the higher proportion of light components only appears in the case of higher feldspar content. With the increase in the quartz and feldspar content, the amount of light components in the rock should increase too. The results indicate that the coarser mineral particles are mainly quartz and feldspar, which have more interparticle pores at micron scale than clay minerals, resulting in the enrichment of light components.

Figure 7.  Diagram showing the relationship between quartz/feldspar and light/heavy components.

Based on the comparison of fluorescence photomicrographs and CLSM 3D models (Fig. 5), the differentiation of light and heavy components, which is similar to chromatographic fractionation, represents expulsion of generative hydrocarbon at a macroscopic scale. The enrichment of light components infers abundant movable hydrocarbon, i.e., good potential of shale oil. Integrating this latest outcome with the above particle size and mineral composition analysis, it is concluded that clay lamina within the mudstone is organic-rich and is a good source rock; silt stone and silt laminae within laminated mudstone has a higher probability to accumulate light components, to become the reservoir in this unconventional shale oil system.

In addition, as the depth of the samples increases, the maximum content of light components appears between 2 200–2 300 m depth (Fig 8a), corresponding to the oil maturity and representing the oil generative process (Liu B et al., 2019; Liu C L et al., 2017). With the increase of depth, the content of heavy components remains basically unchanged (Fig. 8a). It can be seen from Fig. 8b that the maximum radius of light components is larger than heavy components'. The radius and volume of light component could reflect the shape and size of macropores. Although the heavy components are partly consisted of kerogen associated with bright yellow fluorescing light components (Fig. 5d; Gorbanenko and Ligouis, 2014), the maximum radius of heavy components is totally smaller than 20 μm. Porosity in kerogen and clays observed by SEM is often at a much smaller scale which is not in this case. The separation of light and heavy components is mostly affected by the pore diameter, which is similar to the effect of particle size on different fractions. The particle size often correlates positively with the pore size (Liu et al., 2020). When the pore radius is larger than 20 μm, the light components become dominant, meaning the micro migration of hydrocarbons has occurred.

Figure 8.  Diagram showing the relationship between depth/radius and light/heavy components.

In summary, particle size, mineral composition, maturity and pore radius at micron scale all have effects on the content of light and heavy components of OM in fine-grained sedimentary rocks. With the increase of particle size, content of quartz and feldspar, and pore radius (at micron scale), and the proportion of light components all would increase. Moreover, the enrichment of light components also relates to the oil maturity, providing a reliable representation for the "sweet spot" exploration of shale oil.

Figure 9 displays the fractal models of light and heavy components in the samples. Based on the fitted trend line (dotted line in Fig. 9), the light and heavy components distributed in the shale samples all satisfy the fractal law. The slope of the trend line and the fractal dimension of each sample are not significantly different. The slope of the fractal curve of the light components is approximately the same, with the intercept (ln r_max/ln N in Eq. 2) between 4.6 and 8.3, and the fractal dimension between 2.2 and 2.5. In addition, the slope of the fractal curve of the heavy components also is approximately similar, with the intercept between 4.2 and 7.3 and the fractal dimension between 2.2 and 2.5. Overall, only the middle part of the data distribution satisfies the fractal dimension, and both ends deviate from the trend line. The deviation in the negative side may be due to the errors by the software, while some smaller size OM cannot be identified. The deviation of the data on the positive end might be caused by the aggregation of some smaller OM that could have been identified mistakenly as a large one by the software. From the fractal models, both the fractal dimensions of light and heavy components distribution vary between 2.2 and 2.5 within the allowable error range. The varying intercept corresponds to variation of the r_max in different samples. The intercept of light components is slightly larger than that of heavy components, suggesting light components accumulated in relatively bigger pores. Based on the results of fractal analysis, the 3D model of heavy and light components that was created from microscopy can be corrected in the case of data deviation, and more accurate results can be obtained.

Figure 9.  Fractal diagram of light/heavy components. The dotted lines represent static results of different samples. Orange and red plots showing the maximum and minimum r_max in Eq. (2).

(1) The occurrences of light and heavy components are related to different lithofacies. The organic matter distributed within siltstone and silt-lamina is not significantly different. In both silty mudstone and mudstone with massive fabric, the diameter of organic matter is much smaller, and most long-wave fluorescence may represent NSO compounds and partly liptinite maceral group.

(2) The proportion of light components is less than 25% while the proportion of heavy components is less than 5%. The content of light components is notably more than heavy components, and the differentiation of light and heavy components is greatly affected by the pore radius.

(3) The relationship between the content of heavy components and depth is not clear, and the content of light components reaches a peak as depth changes, which corresponds to the process of oil generation.

(4) The relationship between the content of heavy components and mineral content is not easily understood, and the content of light components is positively correlated with the content of quartz and feldspar.

(5) The light and heavy components distributed in the shale samples all satisfy the fractal model. Both the fractal dimensions of light and heavy components distribution resides between 2.2 and 2.5.

Samples were provided by the Daqing Oil Company in China and authors sincerely appreciate their support and input in this study. This study was supported by the Open Fund of the State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Chengdu University of Technology, China (No. PLC20180402), the National Natural Science Foundation of China (No. 41972156), and the National Basic Research Program of China (No. 2016ZX05003-002). The final publication is available at Springer via https://doi.org/10.1007/s12583-020-1345-3.