International Journal of Coal Geology xxx (2013) xxx–xxx

COGEL-02129; No of Pages 11

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International Journal of Coal Geology

j ourna l homepage: www.e lsev ie r .com/ locate / i j coa lgeo

Application of BIB–SEM technology to characterize macropore morphology in coal

S. Giffin a, R. Littke a,⁎, J. Klaver b, J.L. Urai b

a Institute of Geology and Geochemistry of Petroleum and Coal, Energy and Mineral Resources Group (EMR), RWTH Aachen University, Lochnerstrasse 4-20, Haus B,52056 Aachen, Germanyb Structural Geology, Tectonics and Geomechanics, Energy and Mineral Resources Group (EMR), RWTH Aachen University, Lochnerstrasse 4-20, 52056, Aachen, Germany

⁎ Corresponding author. Tel.: +49 241 809 5748; faxE-mail address: Ralf.Littke@emr.rwth-aachen.de (R.

0166-5162/$ – see front matter © 2013 Elsevier B.V. Allhttp://dx.doi.org/10.1016/j.coal.2013.02.009

Please cite this article as: Giffin, S., et al., AppCoal Geology (2013), http://dx.doi.org/10.101

a b s t r a c t

a r t i c l e i n f o

Article history:Received 21 December 2012Received in revised form 18 February 2013Accepted 19 February 2013Available online xxxx

Keywords:Coal porosityBroad-ion-beam millingSEM imagingPore morphologyPore size distributionVitrinite maceralInertinite maceral

We use broad ion beam (BIB) milling to prepare low-relief polished surfaces of coal samples for high-resolutionSEM imaging, in a study of the morphology and distribution of macro- and mesopores. Results show that theBIB-sections of a few square millimeters are not large enough to be statistically representative so that porositywas investigated as a function of maceral type. For a vitrinite maceral type, we found comparably little visiblemacroporosity within the resolution limits of the SE detector. Less than 2% of all themeso- andmacropores stud-ied were found in vitrinites. Pore morphology in an inertinite maceral is dependent on the original maceral.Fusinite yields large, elongated pores (often filled with mineral phases), while macrinite shows comparativelysmaller, rounder pores. The distribution of pore sizes follows a similar power law at different magnifications.Our results show that micropores and macropores in coal belong to different populations, with different sizedistributions and morphologies. BIB–SEM imaging is a useful tool to study meso- and macropore morphology,especially in the size range between 10 nm and 10 μm, but more maceral types should be characterized for abetter characterization of maceral porosity at different stages of coalification.

© 2013 Elsevier B.V. All rights reserved.

1. Introduction

Coal is a naturally fractured reservoir, and the nature of these frac-tures plays an important role in the development and production ofcoalbed methane. Natural gas flow in a coalbed is commonly modeledin two phases (Karacan and Okandan, 2000; Yao and Liu, 2009). First,adsorbed gas in the coal matrix must diffuse to the fracture, or cleat,network. Once the gas molecules reach the cleat network, the secondphase of flow, namely viscous flow, becomes the dominant parameter.Assessing the structural features of the coalmatrix and cleat network fa-cilitates in characterizing coal as a porous medium for natural gasrecovery.

Coal is an extremely heterogeneous material that can be character-ized by its matrix structure and the pores within this structure. Porosityevaluation would be improved by a better understanding of its micro-structural controls. For example, Gamson et al. (1993) described twotypes of matrix porosity: 1, pores found within the macerals and 2,pores located in betweenmacerals, clays, ormineralmatter. Other stud-ies have shown that the relative abundance of micro-, meso-, andmacropores is related to organic composition and coal type (Clarksonand Bustin, 1999; Gan et al., 1972; Harris and Yust, 1976; Unsworth etal., 1989). Micropores are less than 2 nm in diameter, while mesoporescover a range of 2–50 nm in diameter; macropores are greater than

: +49 241 809 2152.Littke).

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lication of BIB–SEM technology6/j.coal.2013.02.009

50 nm in width (Rouquerol et al., 1994). Micropores make up thebulk of coal porosity, butmesopores andmacropores can contribute sig-nificantly to the total pore volume (Clarkson and Bustin, 1996; Gan etal., 1972). Microporosity is contained in vitrinite-rich coals, determinedby adsorption techniques (Clarkson and Bustin, 1996), but little workhas been done to visually prove that vitrinite macerals contain veryfew meso- or macropores.

Porosity in coal is often described by the pore volume distribution,determined by either mercury porosimetry, gas adsorption, liquid ad-sorption, or varied optical methods, used to ultimately determine thetotal porosity for a certain class of pore size. Integrating the results ofseveral methods is still not without limitations. For example, gas ad-sorption and mercury porosimetry only provide information regard-ing connected pores with minimum pore and throat radii (Prinz andLittke, 2005). Scattering and diffraction, such as small angle neutronscattering (SANS), compute pore size distributions based on a spher-ical pore geometry, and porosity is the sum of both open and closedpores (Prinz et al., 2004; Radlinski et al., 2004). The pore size distribu-tion results obtained by nuclear magnetic resonance (NMR) are diffi-cult to interpret (Yao et al., 2010a) or require a sample specific fittingparameter (Yao et al., 2010b). Since nitrogen adsorption is often usedto examine the meso- and macropore size distributions (Gan et al.,1972; Gensterblum et al., 2009; Prinz et al., 2004), this paper usesthe pore size distribution from individual macerals and comparesthe results to nitrogen adsorption.

Coal is known to display anisotropic characteristics. Massarotto etal. (2003) studied the effects of anisotropy on coal permeabilities and

to characterize macropore morphology in coal, International Journal of

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found that the investigated coals displayed a greater permeability inthe face cleat direction. Coal permeability is more strongly influencedby flow through the cleats than through the pore systems. Neverthe-less, cleats and pores are still affected by the same paleo-tectonic set-tings. In a recent work quantifying pore size distributions using SAXSand SANS, Radlinski et al. (2004) showed that pores perpendicular tobedding are smaller than those in the bedding plane. In this study, wewill quantify pore sizes in the bedding plane and perpendicular to itusing visual techniques.

The characterization of pore morphology, e.g. size distributions orshapes, has recently become the focus of various studies. SEM imagingcan provide important information on pore structures. However,pores located in a rough surface, due to mechanical polishing or evenwith resin-enhancement, are often difficult to interpret (Desbois et al.,2011). Better results have recently been obtained combining eitherfocused ion beam (FIB) or broad ion beam (BIB) sample preparationwith high resolution scanning electron microscopy (SEM) to obtaindetailed images of clear pore structures (Chalmers et al., 2012;Curtis et al., 2010, 2012; Desbois et al., 2009; Houben et al., 2013;Loucks et al., 2009). These studies investigated the porosity of gasshales or claystones. As of yet, little attention has been given to theapplication of the two methods to coals. This paper utilizes BIB sam-ple preparation with SEM imaging on macerals in coal to investigatethe pore size distribution of meso- and macropores, which are a partof the fluid pathway when determining reservoir permeability, aswell as the pore shape, which plays a role in many volumetric reser-voir calculations.

2. Methods

2.1. Sample background and selection

Samples with varying degrees of coalification from within theRuhr and Munsterland basins were first selected to test applicabilityof using BIB-milling in combination with SEM imaging to study poremorphology in coals. The original Ibbenbüren and Prosper Hanielcoal samples were derived from mining activity, while the originalBeustfeld sample was from a core. The samples, as used in thisstudy, were selected from particles, and thus the original bedding re-lationship is ambiguous.

A second set of coal samples was taken from Well 1 in theMunsterland basin, Germany, to evaluate the role of lithotype onpore size and shape and the role of pore size and shape relative tobedding. The term lithotype is purely a macroscopic description of acoal section 3 to 10 mm thick (Taylor et al., 1998); however, thisterm will be used throughout the paper to reference the source ofthe individual samples. The two lithotypes (bright coal, dull coal)are closely related in depth (Table 1), thus ruling out any potential in-fluences due to a different maturity or compaction history. All of thesamples represent Carboniferous coals of tropical origin (see Böckeret al. (2013), Jasper et al. (2009), and Littke and ten Haven (1989)

Table 1List of samples that were BIB-polished and viewed under the SEM. Vitrinite reflectanceand maceral analysis are bulk parameters for the entire bed from which the sampleswere selected. VRr = random vitrinite reflectance. Sample label symbols: D = dulllithotype; B = bright lithotype; II = parallel to bedding; ⊥ = perpendicular to bedding.

Site location Samplelabel

Depth[m]

VR,[%]

Maceral analysis

Vitrinite[%]

Inertinite[%]

Liptinite[%]

Ibbenbüren Ibbenbüren 1500 3.29 99 1 0Beustfeld Beustfeld 545 2.44 83 17 0ProsperHaniel

Prosper Haniel 915 0.86 57 31 12

Well 1 Inertinite 891 1.02 63 25 12Well 1 Vitrinite 891 1.02 63 25 12

Please cite this article as: Giffin, S., et al., Application of BIB–SEM technologyCoal Geology (2013), http://dx.doi.org/10.1016/j.coal.2013.02.009

and references within for depositional conditions). The burial historyof the coal-bearing Carboniferous succession has been summarizedby Karg et al. (2005). Characteristics of the studied coal samples aregiven in Table 1.

To ensure that the areas selected for the pore analysis of maceraltype were actually of the desired maceral group, i.e. vitrinite orinertinite, sample areas of a core were first polished and then examinedunder the optical microscope (Fig. 1A, step 1). An image of the core slicewas acquired and used as a guide to maceral selection (Fig. 1A, heavyblack box). The maceral was BIB polished and SEM images were ac-quired of the maceral, as viewed parallel to the bedding plane (step2). Then the sample was rotated 90°. This surfacewas then BIB polishedand examined under the SEM; thus, allowing us to investigate the samemaceral perpendicular to bedding (step 3).

Based on core slice images (e.g. Fig. 1A, step 1), the specific maceraltype of each maceral group can be identified. For the bright lithotypechosen from Well 1, a fusinite particle was chosen to represent theinertinite maceral group and a telocollinite was chosen to representthe vitrinite maceral group. For the dull lithotype from this well,macrinite was the inertinite maceral chosen and telocollinite was thevitrinite maceral chosen.

All BIB-milled and examined sections are listed in Table 2. Sample la-beling is based first by site location (Ibbenbüren, Beustfeld, ProsperHaniel, andWell 1). Second, to distinguish between the different samplesections from Well 1, the samples are labeled by maceral group(inertinite or vitrinite). In the parentheses, the lithotype in which thesamplewas selected is listed (D = dull lithotype, B = bright lithotype),followed by the image's relationship to bedding (II = parallel to bed-ding; ⊥ = perpendicular to bedding) and subsequently the magnifica-tion at which the image was examined (2kx, 5kx, etc.).

2.2. Sample preparation, image acquisition and processing

A detailed description of the maceral sample preparation forBIB-milling/SEM imaging is as follows: the coal sample was dried inan oven (air drying under b1 bar to prevent oxidation at 65 °C) for12 h. Subsequently, the vitrinite and inertinite samples were cut outof the coal core with a mini rotary saw blade. The samples were notembedded in epoxy. These samples were then ground and polishedwith silicon carbide sandpaper, which also aids in preparing parallelsurfaces for mounting the sample to a sample holder. After thispreliminary preparation, the samples were stored in an exicatorwith silica gel to prevent hydration.

The sample size is dictated by the capacity of the BIB machine(JEOL SM-09010), which polishes a cross-section of about 2 mm2,using an argon beam for about eight hours of milling under a vacuum(10−3–10−4 Pa, 6 kV and 150 μA). The milling process removesabout 100 μm of material and creates a cross-section with a topogra-phy of about ±5 nm (Klaver et al., 2012). The BIB-polished sampleswere gold sputtered to prevent electrostatic charging and subse-quently imaged with a Zeiss Supra 55, utilizing a high-resolution sec-ondary electron (SE) and back-scatter electron (BSE) detectors atRWTH Aachen University. Typical porous areas to study the poreswithin the BIB-polished cross sections were selected (Table 2). Thefinal image of these areas is a mosaic, created by taking hundreds ofpictures at magnifications of either 2000, 5000, 10,000, 20,000, or30,000× using 10–20% overlap. The BSE detector was additionallyused to create several mosaics to gain information about the relativematerial density and mineralogy. An energy dispersive X-ray spectro-scope (EDX) was attached to the SEM for elemental analysis.

When using FIB–SEM or BIB–SEM, artifacts like local compositionor phase changes as well as redeposition of the sputtered materialcan occur. No action was taken to prevent such artifacts, but for ex-ample, redeposition of the sputter material was also not observed inthe studied samples. Bassim et al. (2012) studied the effect of FIBmilling on lignite coal and found that only minor chemical changes

to characterize macropore morphology in coal, International Journal of

Fig. 1. (A) Schematic of sample selection and orientation. Dashed lines indicate bedding planes (not to scale). Dotted lines signify BIB polished sections. Heavy black boxes are par-allel to bedding; double-dashed boxes are perpendicular to bedding. Solid grey areas of the cubes represent non-imaged sections. (B) Visualization of BIB-milled surface (SEMimage; (a)) on sample vitrinite (B/II) and vitrinite (B/⊥/5) with its comparable micrograph (oil immersion, reflected light (b)). The pores in sample vitrinite (B/⊥/5) and vitrinite(B/⊥/20) are most likely not located in the telocollinte but instead in an underlying, different maceral type. (The micrograph is analogous to the SEM image. Dotted lines contain theBIB-milled surface. Solid grey areas of the cubes represent non-imaged sections.)

Table 2Statistics of the mosaics with detectible pores, i.e. those mosaics used in the pore analysis. The samples vitrinite (D/II) and vitrinite (D/⊥) as well as vitrinite (B/II) are not listed inthe table, since they contained practically no detectible pores. In addition to the sample label symbols (Table 1), a number after the bedding orientation indicates the level ofmagnification times 1000. A letter after the magnification (i.e. 20a or 20b) indicates two different mosaics taken at the same magnification.

Sample label Magnification Total no.of pores

No. of pores > p.p.r.a No. of imagesin mosaic

Mosaic area [nm2] Pixel size [nm] Practical pore resolution(eq. diameter)b [nm]

Ibbenbüren (−/−/10) 10 kx 182 109 132 5.12 · 1010 29.3 113.5Beustfeld (−/−/30) 30 kx 3898 2383 168 7.5 · 109 9.8 38.0Prosper Haniel (−/−/20) 20 kx 73 23 104 6.51 · l09 14.7 56.9Inertinite (D/II/20) 20 kx 5121 3427 224 2.53 · 1010 14.7 56.9Inertinite (D/⊥/20a) 20 kx 2431 2123 120 1.24 · 1010 14.7 56.9Inertinite (D/⊥/20b) 20 kx 1851 1449 156 1.38 · 1010 14.7 56.9Inertinite (B/II/2) 2 kx 1403 940 197 1.20 · 1012 146.7 568.2Inertinite (B/II/10) 10 kx 281 242 180 8.70 · 1010 29.3 113.5Inertinite (B/⊥/5) 5 kx 1213 1139 169 3.18 · 1011 58.6 227.0Inertinite (B/⊥/20) 20kx 56 56 88 1.15 · 1010 14.7 56.9Vitrinite (D/II/2)c 2kx b35 – 136 1.87 · 1014 146.7 –

Vitrinite (D/⊥/2)c 2 kx b20 – 77 l.33 · 1012 146.7 –

Vitrinite (B/II/2)c 2 kx b20 – 126 1.44 · 1012 146.7 –

Vitrinite (B/⊥/5) 5 kx 5183 1504 196 5.06 · 1011 58.6 227.0Vitrinite (B/⊥/20) 20 kx 333 245 56 9.22 · 109 14.7 56.9

– Not determined.a p.p.r.: practical pore resolution.b Pore resolution assumes a minimum of 15 pixels.c Due to low number of visible pores, no high resolution mosaics were created to determine pore size distributions.

3S. Giffin et al. / International Journal of Coal Geology xxx (2013) xxx–xxx

Please cite this article as: Giffin, S., et al., Application of BIB–SEM technology to characterize macropore morphology in coal, International Journal ofCoal Geology (2013), http://dx.doi.org/10.1016/j.coal.2013.02.009

4 S. Giffin et al. / International Journal of Coal Geology xxx (2013) xxx–xxx

were induced. Yao et al. (2011) used atomic force microscopy tostudy the nanostructure of coals. They used anhydrous ethanol to re-move impurities from the surface before observation; this step mayhave been of interest for our study, since a few dust particles were ob-served on our samples' BIB-milled surface. Loucks et al. (2009) usedargon-ion beam milling to eliminate artifacts, such as pits or holesthat could be mistaken for pores, created by conventional polishingtechniques. During milling, surface damage caused by incident ionsis reduced by a shield covering most of the sample (Drobne et al.,2007).

The individual images for the mosaics of the large areas werestitched together using a bicubic interpolation in Autopano 2. Thepores were segmented manually in ArcGIS 9.3. Pores are recognizabledown to a few pixels in size. A practical pore resolution of 15 pixels istaken as the minimum pore resolution, which is the minimum size inwhich all pores are detected.

2.3. Data acquisition

The data format of the segmented pores is an ArcGIS shape file.From this shape file, the geometrical properties of each pore can beobtained, including area, length, width and orientation. Area is calcu-lated from the shape file itself, while length, width and orientationwere derived using a minimum bounding geometry.

In the results section of this paper, frequency diagrams of porearea are used to compare the individual samples. The pore size distri-bution is given as a normalized discrete function (Klaver et al., 2012):

Ni

biSmosaic¼ CS−D

pore ð1Þ

By taking the log of each side, we get:

logNi

biSmosaic

� �¼ −D log Spore

� �þ log Cð Þ ð2Þ

where Ni is the number of pores with a characteristic pore area Sporewithin the bin width bi. Bin width bi doubles with each subsequentbin (1, 2, 4, 8, 16, etc.). Smosaic is the surface area of the respective mo-saic. C is a constant and D is the power-law exponent. The pore sizedistribution is plotted on a log–log graph and the range betweenthe largest pore and the smallest (practical pore size) defines thelimits of the power-law distribution, as presented in Klaver et al.(2012).

In addition, the frequency of pore areas of samples from Well 1 iscompared with their bulk mesopore distribution. The mesopore analy-siswas determined by lowpressure nitrogen adsorption after themeth-od discussed in Prinz et al. (2004) and evaluated using the quenchedsolid density functional theory (QSDFT) presented in Neimark et al.(2009).

3. Results

3.1. Qualitative description of pore morphology

3.1.1. IbbenbürenMuch of the BIB-milled surface of the Ibbenbüren sample contained

little visible porosity. The apparent pores are rounded without anysharp corners. The contact between the pore wall and the BIB-milledsurface is smooth. The pores have a gentle curvature to their shape.

A BSE detector combined with an EDX detector shows that an in-organic component – kaolinite - is present in the coal matrix. Poresappear to be concentrated within the organic material adjacent tothe kaolinite. No pores were observed within the kaolinite. Fig. 2Ashows the relationship between the coal organic porosity and adja-cent kaolinite.

Please cite this article as: Giffin, S., et al., Application of BIB–SEM technologyCoal Geology (2013), http://dx.doi.org/10.1016/j.coal.2013.02.009

3.1.2. BeustfeldMicrocracks are prominent in the BIB-milled surface area of the

Beustfeld sample. The presence of minerals either completely or par-tially filling the cracks indicates that they originated in-situ, and thusnot due to damage or drying effects. Framboidal pyrite occurs inlayers along these cracks, which may be an indication of bedding.

Towards the base of the milled surface area, a layer is perforatedwith many pores. These pores are rather angular with visible porewalls dipping shallowly from the surface into the sample. Oppositepore walls sometimes constrict, either closing off a singular largepore into two smaller ones or leaving a small slit to connect the largerpore cavities. These pores are located primarily in the coal matrix oras a gap between the framboidal pyrite and organic matrix (Fig. 2B).The spatial relationship of the pores to one another is shown inFig. 3(1) and Fig. 3(A).

3.1.3. Prosper HanielThe pores in the Prosper Haniel sample can be divided into two

types: 1) pores in the matrix, and 2) pores associated with theframboidal pyrite grains located along partially open microcracks. Themajority of the BIB-milled surface area of the Prosper Haniel matrixshowed no visible pores; however, there was one cluster of smallpores. The shape of the pores surrounding the pyrite grains outlinesthe cubic nature of pyrite.

The Prosper Haniel sample also contained frambodial pyrites(Fig. 2D). In contrast to sample Beustfeld, the pores in the ProsperHaniel sample are found around each pyrite mineral in the frambodialpyrite group. A gap has formed between the organic matrix and theindividual framboidal pyrites, resulting in a rather porous structureon the whole. This gap may be the result of matrix shrinkage causedby desorbed methane or by drying (Day et al., 2008). However, theopposite can also occur: pyrite can fill the pore space, thus effectivelyreducing total porosity and creating more torturous pathways for gasflow (Fig. 2C).

3.1.4. Well 1The investigated surface area of the inertinite sample series from

Well 1 revealed a variety of pore shapes and sizes. The pores in theinertinite in the dull lithotype, both parallel and perpendicular tobedding, are characterized as angular, small, – compared to the sam-ple in the inertinite in the bright lithotype – and multitudinous(Fig. 3(2)). The BIB-milled surface area perpendicular to beddingappeared to be cross-cut by microcracks, which potentially mark bed-ding planes. Pores in the inertinite sample in the bright lithotype, incontrast, were generally elliptical. These pores also appear to beslightly oriented, stretching from the lower left-hand corner to theupper right-hand corner. Even at the magnification of the whole sur-face area (2000×), the outline of the pore walls was well defined.Often these pores were partially filled; albeit the original pore outlinewas still visible. However, the mineral(s) filling the pores did not sealthem completely.

Fusinite from the inertinite (B/II) sample is shown in Fig. 4. Fig. 4Aand B indicates that a significant proportion of the pores within thefusinite are filled with inorganicmaterial. This agrees with observationsusing the reflected light microscope (Fig. 4C). Higher magnificationreveals that the entire pore is not completely filled (Fig. 4D).

Fig. 4E shows an exemplary pore from the sample inertinite (B/II)along with the corresponding EDX images and interpretation of themineralogy (Fig. 4F). Based on the EDX measurements, the data sug-gests that the inorganic substances are kaolinite, dolomite, and anker-ite. The mineralogy found in the pores of this study's samples issimilar to that in the Ruhr Basin coals studies by Dawson et al. (2012).

The vitrinite sample series showed very little visible porosity. Onlya few very sparsely scattered, small round pores were found. Thesepores were so small in number that the samples are characterizedas having no meso- and macroporosity. The one exception to this in

to characterize macropore morphology in coal, International Journal of

Fig. 2. Images of samples Ibbenbüren, Beustfeld, and Prosper Haniel. The relationship between pores in the organic matrix and their proximity to inorganic components is shown.(A) BSE image showing pores (red) located between clays (light grey areas) in sample Ibbenbüren (−/−/10). (B) BSE image of sample Beustfeld with segmented pores. Majority ofthe pores are in the organic material between the frambodial pyrites and not in between the pyrites (compare to (D)). (C) Euhedral pyrite crystal in pore in sample Prosper Haniel.(D) is a BSE image of frambodial pyrite grains, sample Prosper Haniel.

5S. Giffin et al. / International Journal of Coal Geology xxx (2013) xxx–xxx

the vitrinite series was the sample viewed perpendicular to beddingfrom the bright lithotype (Fig. 1B). In this sampled surface area, nu-merous pores were visible. However, these pores probably do not be-long to a vitrinite maceral. The lower section of the image, whichincludes the porous parts, is within an inertinte maceral. Only thetop part of the BIB-milled section belongs to a vitrinite, even thoughthe whole sample section is labled as a vitrinite.

3.2. Quantitative description of pore shape

3.2.1. Pore length, width, and aspect ratioPore dimensions of length and width for each sample are com-

pared in Fig. 5. In the figure real pore images are shown next an ellip-se of mean pore shape. The ellipse of mean pore shape is a measure ofthe average length and width of the minimum bounding box for allsegmented pores. The average pore length, width, and aspect ratioare based on all the pores greater than the practical pore resolution(equivalent to 15 pixels in size).

With respect to the length and width, all pores compared to oneanother are small (lengths and widths less than one micrometer)and slightly elliptical. The exception is the pores found in the fusinitesample. These pores have lengths greater than or equal to approxi-mately one micrometer.

Aspect ratio is not so strongly dependent onmagnification as the in-dividual dimensions and therefore,makes a good parameter to compareresults from the same sample that were determined at different magni-fications. Aspect ratio is an indicator for the pore roundness. It may alsobe a way to eliminate the effect of magnification on pore dimensions.Ibbenbüren, Beustfeld, and Prosper Haniel have aspect ratios of 2.6,

Please cite this article as: Giffin, S., et al., Application of BIB–SEM technologyCoal Geology (2013), http://dx.doi.org/10.1016/j.coal.2013.02.009

2.7, and 1.6, respectively. The aspect ratio for the inertinite in the dulllithotype does not change much, regardless of the orientation to bed-ding. The inertinite in the bright lithotype has a high aspect ratio paral-lel to bedding, and a comparatively lower aspect ratio perpendicular tobedding. The aspect ratio for the vitrinite in the bright lithotype is sim-ilar to that of inertinite in the dull lithotype.

3.2.2. Pore areaThe distribution of pore area for each mosaic is shown on a log–log

diagram of normalized frequency versus pore area (Fig. 6). The validrange for each linear regression is defined by the filled-in markers, thevariables D and log C, and the dashed lines crossing the x-axis guidethe eye to end-member equivalent pore diameters. The open markersrepresent segmented pores with a size of the practical pore resolution.

The parameters D and log C range for the samples Ibbenbüren,Beustfeld, and Prosper Haniel from 1.47 to 1.81 and −3.90 to −6.98,respectively. The parameters D and log C range for the vitrinite andinertinite sample sections from 1.13 to 1.79 and −4.31 to −8.63,respectively. Formost of the samples, the frequency of pores less than ap-proximately 15 pixels in size decreaseswith decreasing pore size. The ex-ceptions are the samples inertinite (D/⊥/20a), inertinite (D/⊥/20b) andinertinite (D/II/20). These samples showed the greatest frequency ofpores at a size of 90 nm indiameter. This peak indicates the lower bound-ary of the self-similar behavior of the pore size distribution.

For each sample analyzed with different magnifications, the dataalign over the middle range of pore areas, indicating the overlap inmagnification (Krohn and Thompson, 1986). The resulting linear re-gression of the pore size distribution for each magnification or sectionper sample also aligns for the most part.

to characterize macropore morphology in coal, International Journal of

Fig. 3. Comparison of spatial relationship and morphology of pores from the samples Beustfeld, inertinite and vitrinite.

6 S. Giffin et al. / International Journal of Coal Geology xxx (2013) xxx–xxx

Fig. 7 shows the percent distribution of pore volume over pore diam-eter for the nitrogen low-pressure isotherm data (solid line). The data isderived from the bulk coal sample from Well 1. As a comparison, thepercent of pore area for the sample inertinite (B/II/5) is also plottedover pore diameter. The graph shows that there is a minimal overlapin pore diameter between the two methods. Based on the nitrogen ad-sorption results, the majority of the pores are about 2 nm in diameter.However, these are the throats of the accessible pores (Prinz andLittke, 2005), leaving the larger pore cavities, which store and transportgas, uncharacterized. And in turn, BIB–SEM determined pore sizes do

Please cite this article as: Giffin, S., et al., Application of BIB–SEM technologyCoal Geology (2013), http://dx.doi.org/10.1016/j.coal.2013.02.009

not capture pore throat diameters. This could explain the lack in overlapbetween the two methods shown in Fig. 7.

4. Discussion

4.1. Porosity and pore morphology

4.1.1. Maceral type: inertinite versus vitriniteIn all BIB-milled sections but one, essentially no visible pores were

detected in the vitrinite samples, which agrees with the findings of

to characterize macropore morphology in coal, International Journal of

Fig. 4. Fusinite maceral as seen with the BSE (A) and SEM (B) and reflected light microscope under oil immersion (C). (D) A pore (outlined with dashed line) and the remaining porosityafter mineral fill or even secondary porosity after partial dissolution of mineral fill. Color coding in image A: dark grey = organic matrix, light grey = inorganic components; imageC: white = organic fragments; light grey = pore-filling mineral(s). (E) BSE image of pore-filling minerals in sample inertinite (B/II) with an interpretation (F). Color coding in image(E): dark grey = organic matrix; light grey = inorganic components; black = open porosity. Color coding in (F): dotted = dolomite, stripped = kaolinite, checked = ankerite.

7S. Giffin et al. / International Journal of Coal Geology xxx (2013) xxx–xxx

Bustin and Clarkson (1998), Clarkson and Bustin (1997), and Mastalerzet al. (2008a). The low-pressure nitrogen sorption experiment showsthat the majority of coal porosity is located in the micropore range(Fig. 7), which is below the pixel resolution. The few pores that werefound in the vitrinites were associated with either a fracture networkor interspersed between mineral phases. Less than 2% of all the poresstudiedwere found in vitrinite. The amount of porosity in the inertinitesvaried based on maceral type.

The samples Ibbenbüren, Beustfeld, and Prosper Haniel are not ini-tially referenced by a maceral group. However, based on the findingsof the image analysis and a subsequent polishing of the sections to

Please cite this article as: Giffin, S., et al., Application of BIB–SEM technologyCoal Geology (2013), http://dx.doi.org/10.1016/j.coal.2013.02.009

examine them under the microscope, conclusions can be drawn aboutthe investigated macerals. The matrix sections of the Ibbenbüren andProsper Haniel samples contained very few pores, which would fitwith the vitrinite group. Additionally the polished sections for the opti-cal microscope also showed vitrinites. The Beustfeld sample is mostlikely of an internite maceral; it contained a multitude of pores, with asimilar pore morphology and size distribution to the studied macrinitesample (inertinite (D/II and ⊥)).

It is known that the distribution of micropore volume with rank fordry coals decreases down to 1.2–1.4 VRr and then increases (Prinz andLittke, 2005). The majority of the micropore volume is located in

to characterize macropore morphology in coal, International Journal of

Fig. 5. Comparison of pore dimensions for each analyzed sample. The ellipses of mean pore shape, based on the minimum bounding box for all pores, are scaled to one another andare based on the given mean lengths and widths for all pores greater than the practical pore resolution. Aspect ratio is given by length divided by width and is based on all datapoints greater than the practical pore resolution.

8 S. Giffin et al. / International Journal of Coal Geology xxx (2013) xxx–xxx

vitrinites (Harris and Yust, 1976; Unsworth et al., 1989), and a similartrend for the amount of meso- and macropores in vitrinites was foundin this study. Mastalerz et al. (2008b) found that collotelinite positivelyinfluenced the meso- and micropore volume.

Maceral composition is important to determine the adsorbedmethane and thus the potential of the coalbed reservoir (Lambersonand Bustin, 1993). Methane adsorption can be used as an indicatorfor gas storage capacity. Due to the low amount of internal surfacearea of inertinites, they have the lowest methane adsorption capacity(Lamberson and Bustin, 1993). However, the inertinites contained thelargest pores (Fig. 5), which may provide the best transport path-ways, considering that smaller pores may be inaccessible to fluidslike water (Han et al., 2010; Prinz and Littke, 2005).

A combination between a good storage capacity, e.g. microporousvitrinites, and large, open transport pathways, e.g. cleats and connectedmeso- and macroporous inertinites, represents the most promising res-ervoirs for coalbed methane. Given that the high volitale bituminouscoal samples of Well 1 and Prosper Haniel as well as the semi-anthracite Beustfeld sample contain about 55–85% vitrinite and 15–30%inertinite (Table 1), these samples have the best potential for gas storageand transport.

4.1.2. Lithotype: dull versus brightBright and dull lithotypes stem from a difference in depositional en-

vironment and/or accumulation rate or degradation of organicmaterial,where a change from bright to dull lithotypemay represent a transitionfrom woody to herbaceous milieus (Lamberson and Bustin, 1993). Thechange in depositional input, demonstrated by lithotype, has an effecton the total maceral composition, which in turn, affects the dominatingtype of porosity.

Based on Fig. 6 it would appear that the greatest difference in porearea distributions occurs between the lithotypes (i.e. individualmacerals) and not between pores with respect to the bedding orienta-tion. For example, the pores in sample vitrinite (B/⊥) (only labeled asa vitrinite, even though this section probably belongs to an inertinite

Please cite this article as: Giffin, S., et al., Application of BIB–SEM technologyCoal Geology (2013), http://dx.doi.org/10.1016/j.coal.2013.02.009

maceral) that were located in a bright lithotype matched the pore sizedimensions of those in sample inertinite (D/⊥), which were located ina dull lithotype. In a future study, more samples of the same maceraltype in different lithotypes should be investigated.

Porosity as a function of lithotype forwhole coals has beendescribedin the literature.Many of these studies have used sorption techniques todetermine porosity (Clarkson and Bustin, 1997; Crosdale et al., 1998).They found that dull coal lithotypes desorbmore rapidly due to a higherinertinite content, and thus macroporosity than their bright lithotypecounterparts. However, the bright lithotypes (vitrinite-rich coals) con-tain more micropores and thus have a greater gas storage capacitydue to larger surface areas. The visual images of coal pore structurespresented in this paper support the previouslymentioned authors' con-clusions: i.e. there is a higher meso- and macropore volume in dulllithotypes and inertinites.

4.1.3. Orientation to bedding: perpendicular versus parallelPore shape reflects the paleostrain at the time of coalification,

where pore sizes perpendicular to bedding are expected to be smallerthan those in the bedding plane (Radlinski et al., 2004). A trend be-tween the pore dimensions – given by length, width, and axial ratio(Fig. 5) – and the relationship to bedding was not discernible in thisstudy. Nevertheless, pore roundness described by the axial ratiomay lead to a better understanding of pore shape models. For exam-ple, the shape of a low-pressure isotherm provides clues as to theshape of the pores (Sing et al., 1985).

4.2. Pore size distribution in coal

Apractical pore resolution of 15 pixelswas chosen tomodel the poresize distribution in coal. However, this boundary should be the subjectof modification in future works. Pores less than 15 pixels in size weredeemed beyond the resolution of the system, and thus, not all of the vis-ible pores below this size can be potentially captured. Therefore, thepore size distribution begins to decrease in frequency towards smaller

to characterize macropore morphology in coal, International Journal of

Fig. 6. Pore size distribution for all studied samples.

9S. Giffin et al. / International Journal of Coal Geology xxx (2013) xxx–xxx

pore sizes due to resolution limits; an effect known as truncation(Ortega et al., 2006). Another possible explanation for the change to-wards smaller pore sizes may be that there are no SEM visible poresbelow a certain pore diameter. For example, the inertinite samples ex-amined perpendicular to bedding at 20,000× magnification, i.e. thesamples inertinite (B/⊥/20), inertinite (D/⊥/20a), and inertinite (D/⊥/20b), did not contain pores smaller than approximately 60 nm in diam-eter. The smallest pore in the sample inertinite (B/⊥/20) is about

Please cite this article as: Giffin, S., et al., Application of BIB–SEM technologyCoal Geology (2013), http://dx.doi.org/10.1016/j.coal.2013.02.009

100 nm (Fig. 6). The smallest detected pores in these samples are stillabove the practical pore resolution, which was used as a visibilitycut-off.

The power law exponent, i.e. parameter D, gives the slope of the re-gression line for the log-log diagrams of pore frequency versus poresize. The relatively low power law exponent (b2) indicates that thesmall pores within the visible range of the SEM – from 10 nm to>1 μm – contribute less to the total porosity than the larger pores.

to characterize macropore morphology in coal, International Journal of

Fig. 7. Pore size distribution for bulk coal sample fromWell 1 (solid line) using nitrogen adsorption at 77 K and QSDFT (cf. Neimark et al., 2009) and for the sample inertinite (B/II/2)using image quantification techniques (dashed line).

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Nevertheless, the pore size distribution, derived from low-pressure ad-sorption data (Fig. 7), shows that most of the pore volume is due tomi-cropores. In order for themicropores to contribute themost to the totalporosity, the slope of the regression line in this range should be greaterthan the slope of the regression line for the meso-/macropores (deter-mined from the SEM images). Therefore, we interpret that pores inthe meso-/macropore range have a different pore size distribution –

and ensuing power lawexponent and coefficient – than pores in themi-cropore range.

The power law exponent can be further used to assess relationshipsbetween samples. By comparing the D values for all sections of theinertinite samples, the biggest difference is between the inertinite inthe bright lithotype, i.e. fusinite; D ≈ 1.25, and the inertinite in thedull lithotype, i.e. macrinite (D ≈ 1.61). The sample labeled vitrinite(B/⊥) has a an average D of 1.57, which is very similar to the macrinite,which is further evidence that only the top part of the sample is vitrinitewhile the pore-rich areas are located in inertinite.

The pore area distributions for the Posidonia shale (Klaver et al.,2012) using the exact same method as in this study are differentfrom those for the coals. The power law exponent for the rock is ap-proximately 2, while the power law regression for the nanofossil po-rosity showed a dual power-law distribution, with an exponentvarying between 1 and 3. The power law exponents for the inertinitesamples averaged to about 1.5. There is the potential that theinertinites are also governed by a dual power-law; however, thechange in the slope of the regression line occurs at pore diameterssmaller than the resolution capabilities of the SEM.

A dual power law – indicating a bi-modal system – for the studiedinertinites agrees the bulk coal data sets in the literature. Gan et al.(1972), who used mercury porosimetry and nitrogen adsorption todetermine their results, found a bi-modal system. Clarkson andBustin (1999) determined a multi-modal pore system for four coalsfrom the Cretaceous Gates Formation.

5. Conclusions

The state-of-the-art method combining broad-ion beam millingwith a high resolution SEM provides clear images of the meso- andmacroporosity in coals, especially for pore diameters between 10 nmand 1 μm. The small area of the milled surface (ca. 2 mm by 2 mm)

Please cite this article as: Giffin, S., et al., Application of BIB–SEM technologyCoal Geology (2013), http://dx.doi.org/10.1016/j.coal.2013.02.009

allows for the investigation of poreswithin an individualmaceral. How-ever, the areas examined may not be representative of the whole, andthus cannot be easily interpreted from a coal seam standpoint. Never-theless, these semi-quantitative images do provide insight into themacropore diversity of individual macerals and thus the heterogeneityof coals. This study is the first to use BIB-milling to examine a smoothcoal surface, which allows for a definitive characterization of pore mor-phology and their location within individual macerals. The studiedvitrinite samples showed mostly no meso- and macropores, while theintertinite samples contained the meso- and macropores. The applica-tion of BIB–SEM imaging to coals as well as the nature of meso-/macropore morphology is summarized below.

• BIB–SEM imaging provides clear images of pores in individual coalmacerals at high resolutions, i.e. lowermicrometer to upper nanometer.

• Pores were often found in close proximity to mineral matter or themineral matter was pore-filling, like in the fusinite voids. The inorganiccomponents that occurred most often in the samples studied were ka-olinite and framboidal pyrite.

• Themost elongated pores, which also happened to be the largest pores,were found in the fusinite.

• The sample sections that were imaged at both high and lowmagnifica-tions, e.g. 20,000× and 10,000×, yield pore area distributions that arein good agreement; i.e. the pore area distributions from the high-and low-magnification mosaics have overlapping sections on thelog-log plots. The pore area distributions shown in the log–log plotsfollow a power law distribution in the BIB–SEM range.

• More samples of the same maceral type from different settings shouldbe investigated at several different resolutions in the future.

• Pore systems in coals differ from those in organic-rich shales by theirpower law regression parameters.

Acknowledgments

This work is funded by ExxonMobil Production Germany GmbHwithin the framework of the project “RWTH-EMPG Investigation ofCoal Seam Gas: Gas storage and transport processes in coal seams”.The constructive comments of two anonymous reviewers greatlyimproved the original manuscript. The authors would like to thankJ. Yeakel and Y. Gensterblum for the fruitful discussions. U. Wollenberg

to characterize macropore morphology in coal, International Journal of

11S. Giffin et al. / International Journal of Coal Geology xxx (2013) xxx–xxx

is acknowledged for his support with the BIB-milling. We would alsolike to acknowledge S. Fellmin, M. Sartorius, K.A. Wilkins for their helpwith pore segmentation.

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