- Email: [email protected]
Gas sorption capacity, gas sorption rates and nanoporosity in coals
International Journal of Coal Geology 200 (2018) 77–86
Contents lists available at ScienceDirect
International Journal of Coal Geology journal homepage: www.elsevier.com/locate/coal
Gas sorption capacity, gas sorption rates and nanoporosity in coals a,⁎
a
a
Ali Kiani , Richard Sakurovs , Mihaela Grigore , Anna Sokolova a b
T
b
CSIRO Energy, 11 Julius Avenue, North Ryde 2113, Australia ANSTO, New Illawarra Road, Lucas Heights, NSW 2234, Sydney, Australia
A R T I C LE I N FO
A B S T R A C T
Keywords: Bituminous coal Rates of gas sorption Methane Carbon dioxide Porosity Macerals
Bituminous coals from a wide range of sources (including Australia, New Zealand, Europe, China, South America, Canada, the US and South Africa) were characterised by their capacity for gas sorption, rate of gas sorption of CO2 and CH4, and their nanoporosity (pore size distribution less than 50 nm radius) in order to identify the relationships between them. The following new relationships were established: The rate of gas sorption was unrelated to the capacity for gas sorption. The rate of gas sorption for CH4 and CO2 increased exponentially with the amount of total and accessible porosity in the size range 8–50 nm (with no influence of coal origin on the relationship being discerned), suggesting that the extent of porosity of coals in this size range controls the rates of gas sorption in coals. In contrast, the capacity for gas sorption was only weakly related to pore numbers in this size range, which shows that the number of 8–50 nm pores do not control capacity for gas sorption. Moreover, this difference in relationship shows the number of pores of the size where gas is sorbed predominantly (< 5 nm) does not correlate strongly with the number of larger pores. Both the number of pores and rates of gas sorption tended to increase with inertinite content but the relationship with inertinite content differed for coals from different sources. The inertinite-rich coals from Australia (except those from the Illawarra region) had both the greatest porosity and gas penetration rates, whereas in coals sourced from other regions, although the gas penetration rate increased with inertinite content, the effect was not so strong. The rates of sorption in the inertinite-rich coals also tended to decrease with increasing rank below 0.9% Rv,max. In contrast to the results obtained with kinetic studies, we found no overall trend of capacity for gas sorption with maceral composition, though the Australian bituminous coals generally had greater capacity than the other bituminous coals examined. This suggests that not only the number of 8–50 nm pores in coals sourced from Australia (not those from the Illawarra region) and elsewhere are different, the number density of accessible < 5 nm pores (not directly measurable in coals by SANS) may also be systematically different between these coals. The relationships developed in this study have important implications in predicting coal structure, fundamental understanding of gas transport through coal beds, and explaining the variation of coking properties of coals sourced from Australia and elsewhere.
1. Introduction
of sorption varied from 2 to 10 (Harpalani et al., 2006). Difference in the capacity for maximum sorption of CO2 and CH4 has been attributed to the different critical temperatures of these gases (Sakurovs et al., 2010). A number of studies investigated the effects of coal properties on sorption behaviour at high pressures (Ozdemir et al., 2004; Saghafi et al., 2007; Day et al., 2008); they found a minimum in capacity for sorption versus rank. Different groups have found different relationships between capacity for sorption and maceral composition, and regional effects have been proposed as one cause for this variation (Sakurovs et al., 2018; Day et al., 2008). A second critical characteristic is the rate at which gas is sorbed and
In recent years, attention has been attracted toward gas flow in coals due to the increasing demand for enhanced production of coal bed methane and reducing fugitive gas emission from coal industries. CO2 injection into coals also needs a thorough understanding of gas behaviour in coals (Wang et al., 2014; Seidle, 2011). This behaviour depends on the characteristics of the coal and gas. One important characteristic of coal is its capacity for gas sorption. This has been extensively investigated (Goodman et al., 2007; Busch et al., 2007; Busch and Gensterblum, 2011). It was found that coals absorbed CO2 more strongly than CH4, however the ratio of the extent ⁎
Corresponding author. E-mail address: [email protected] (A. Kiani).
https://doi.org/10.1016/j.coal.2018.10.012 Received 17 July 2018; Received in revised form 28 October 2018; Accepted 29 October 2018 Available online 30 October 2018 0166-5162/ Crown Copyright © 2018 Published by Elsevier B.V. All rights reserved.
International Journal of Coal Geology 200 (2018) 77–86
A. Kiani et al.
characterisation was supplied, for commercial reasons. All samples were crushed to < 1 mm with minimum fines based on the standard procedure suggested by Staib (2013) (the petrographic properties of coals can therefore be assumed unchanged); the 0.5–1.0 mm fraction was used for characterisation by neutron scattering, capacity for gas sorption and kinetics of sorption. The samples were stored in sealed containers at −18 °C.
released from coals. This also has been extensively examined (Busch and Gensterblum, 2011). There is evidence that the rate of penetration of a gas into coal particles varies significantly, even within a given coal particle. Using X-ray CT, the CO2 diffusion rate in a bituminous coal sample was found to vary significantly in different parts of the sample; the penetration rate was higher in the inertinite component than in the vitrinite component (Karacan, 2003). Using Infra-Red Spectroscopy, Mastalerz et al. (2012) observed that the inertinite part of coals was saturated much faster than the other parts. In another study, Mayo et al. (2018) applied the micro-computed tomography (micro-CT) to study the gas uptake in coals using Kr, Xe and CO2. They found that the CO2 uptake rate was greater than the other gases in all cases, and the diffusion rates varied significantly between different coals. Staib et al. (2015a,b) suggested that the diffusion in coals was dispersive (that is, in some regions in coals diffusion was faster than in others) due to the pore size distribution in coals varying on a microscale. With this assumption they found that only two fitting parameters were required to characterise the sorption curve in coals: k, an average diffusion rate and β, which indicated the degree of dispersion of sorption rates. Keshavarz et al. (2017) introduced another fitting parameter to the model based on the fact that, due to the very slow equilibration in many coals, the amount of gas adsorbed at the end of the experiment (indicated as Mend) was less than the equilibrium value (indicated as Minf). The equation used is:
Mt / Mend = (Minf / Mend ){1–exp[−(kt ) β]}
2.2. Methods 2.2.1. Kinetics of gas sorption Kinetics of gas sorption were measured in a SETARAM PCTPro™ rig. The temperature of samples was maintained at 23 °C by using a temperature controller and insulating the sample holder. Helium gas was used to calibrate the volume of the sample cell and check the system for any leaks. An evacuation pump was also used to evacuate the system and sample from any contamination when required. The whole process was automated and controlled using the apparatus operating software. Fig. 1 shows the schematic diagram of the sorption rig. For each experiment, the coal sample was placed in a vacuum oven at a temperature of 60 °C under a vacuum pressure of −101.6 kPa for a minimum of 48-h evacuation. About 1 g subsample was taken from the main sample, weighed and loaded into the rig. The sample cell was charged with helium gas up to a pressure of around 5 bar to check the system for any leaks. Using the evacuation pump, the sample was then evacuated for a further 48 h under a vacuum pressure of −101.6 kPa. After this stage, the free volume of the sample holder was measured using helium, and this was used later to calculate the amount of gas sorbed by coals. After the helium measurement, the sample was evacuated for another 10 h. The gas was introduced at 1.5 bar intervals and at each step the sample was given at least 48 h to reach equilibration. It was previously shown (Keshavarz et al., 2017) that the sorption results were independent on pressure in this low-pressure range. The second step was chosen for the kinetics results presented here since it showed the greatest repeatability of the three. Experimental time, the mass of adsorbed gas, the gas pressure inside the sample holder, and the sample and reservoirs temperatures were recorded by a data acquisition system and used for analysis. The modified stretched exponential model (Equation 1) was applied to the experimental data to determine the fitting parameters (Minf/Mend, k and β). The Excel Solver Routine was used to obtain these sorption parameters by minimising the Sum of Squared Residuals (SSR) of the fit to the sorption data. The root mean square of residuals (RMSR) was calculated for each experiment to indicate the quality of fitting. The reproducibility of kinetic measurements was tested for a number of coals. The sorption rate parameter (k) had an associated percentage error (~ < 20% for CH4 and ~ < 10% for CO2). If kβ values (the term in Eq. 1) for different repeats is considered, a much smaller error (< 10% and < 5% for CH4 and CO2, respectively) is obtained. The error associated with β was found to be generally small (< 5%).
(1)
where Mend and Minf are the sorption amount obtained at the pressure and temperature of sorption kinetic tests. The sorption parameters (k and β) were found to vary significantly with coal characteristics such as rank, composition, geological source, and preparation conditions such as particle size and temperature. Previous studies of the effect of coal rank and composition on sorption kinetics have not agreed about the nature of the trends found (Crosdale et al., 1998; Adeboye and Bustin, 2013; Keshavarz et al., 2017). The lack of consistency has been attributed to regional effects: coals sourced from different basins showed different trends (Sakurovs et al., 2018). Small Angle Neutron Scattering (SANS) has been used to measure both closed and open porosity of coals on a nanometre size scale. The accessibility of pores varied with the physical and chemical properties of coals (rank, maceral composition, porosity, origin etc.). It was found that the accessibility of pores to CO2 and CH4 increased with increasing total porosity of coals, as interconnectivity of pores was more likely to be facilitated in high porosity coals (Melnichenko et al., 2012). Sakurovs et al., 2012 using SANS, concluded that the fraction of 8 nm pores that were accessible to CH4 increased with increasing inertinite content. More recently, Sakurovs et al. (2018) showed strong regional variations in nanoporosity of inertinites that was not due to the submaceral composition or geological age of the coals. They suggested that these differences in nanoporosity can be the reason of variations in gas sorption behaviour of coals sourced from different regions. In this study, we combined the information presented in previous publications (Day et al., 2008; Sakurovs et al., 2018) with new data to establish new relationships between kinetics of gas sorption, capacity for gas sorption and porosity of coals. The importance of these relationships in the context of coal structure, the enhanced coal bed methane processes and coking behaviour of coals is discussed. Bituminous coals with a wide range of characteristics sourced from a number of regions including Australia, New Zealand, Canada, the USA, Europe, Africa, Asia and South America were examined.
2.2.2. Capacity for gas sorption Sorption isotherms for CH4 and CO2 were measured in a high pressure gravimetric system at a constant temperature of 55 °C and different pressures up to 16 MPa following the procedure of Day et al. (2008). The capacity of maximum sorption and the heat of sorption were determined from the isotherms fitted using a modified DubininRaduschkevich equation (Sakurovs et al., 2010). 2.2.3. Porosity The SANS technique was applied to characterise coal porosity. In this technique, the intensity of scattered neutrons off materials as a function of scattering angle is used to determine pore size distributions (Melnichenko et al., 2012). The fraction of pores in materials accessible to fluids as a function of pore size can also be determined by comparing the SANS patterns (intensity of scattered neutrons) obtained from the
2. Experimental 2.1. Materials A total of 52 bituminous coals from a range of sources were studied. Data are shown in Table 1. Samples were de-identified and limited 78
International Journal of Coal Geology 200 (2018) 77–86
A. Kiani et al.
Table 1 The origin, physical and petrographic properties of the coal samples investigated. Data availability of different tests for each coal sample is shown by Y. The data obtained from Day et al., 2008 and Sakurovs et al., 2018 are denoted as Ya and Yb. Coal sample
Australia
Australia-Illawarra
USA
South America Canada South Africa
Europe
New Zealand China
Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52
Density (g/ cm3)
Ash (% db⁎)
Rv,max⁎ (%)
Vitrinite (vol.% mmf⁎)
Inertinite (vol.% mmf)
Liptinite (vol.% mmf)
Sorption rates
Sorption amount
1.422 1.391 1.344 1.316 1.331 1.313 1.376 1.365 1.505 1.293 1.473 1.357 1.348 1.367 – 1.350 1.519 1.552 1.365 1.471 1.319 1.329 1.416 1.625 1.368 1.375 – 1.481 1.357 1.312 1.324 1.381 1.363 1.446 1.372 1.330 1.405 1.387 1.418 1.504 1.546 1.641 1.593 1.365 1.363 1.353 1.295 1.387 1.386 1.408 1.407 1.370
7.7 8.3 5.1 7.2 7.4 5.6 8.4 10.0 18.7 6.1 21.3 6.4 7.4 8.8 7.1 12.0 17.6 20.8 11.4 25.5 4.9 5.8 9.1 8.9 9.8 16.9 5.1 4.1 5.3 9.0 4.8 15.5 8.6 6.5 17.0 9.1 10 16.9 22.8 27.0 25.2 5.7 5.8 3.6 2.5 24.8 10.13 9.49 9.72 9.72
0.69 0.9 1.03 0.99 0.89 0.95 1.63 1.08 0.8 0.7 0.77 1.29 1.16 1.43 1.18 0.79 0.81 0.62 0.8 0.8 0.8 0.8 0.48 1.93 1.21 1.27 1.29 1.40 1.61 0.98 0.9 1.29 1.68 0.46 0.76 0.85 0.84 1.05 1.22 1.28 0.7 0.7 0.74 1.34 1.22 0.55 1.11 0.81 0.91 1.49 1.27 0.99
29.7 33.9 63.6 90.9 88.7 82.7 83.9 74.3 20.2 68.3 61.8 59.1 69.1 76.7 56.8 84.2 10.6 23.9 64.0 40.3 64.3 59.5 58.9 48.3 85.4 48.7 32.6 28.1 81.7 72.5 89.4 87.3 89.0 85.0 82.2 69.9 80.0 84.5 66.7 71.7 42.0 25.0 24.1 35.6 47.6 89.8 95.5 28.7 59.5 46.0 51.8 56.7
66.4 63.8 34.7 8.4 9.1 13.2 16.1 23.4 74.8 17.6 33.4 40.7 29.8 23.3 43.2 11.7 84.4 74.5 34.3 58.4 32.7 39.2 38.3 51.7 14.3 50.9 68.4 71.9 18.2 20.5 7.1 12.7 10.0 10.0 14.9 17.7 16.0 15.1 33.3 27.2 53.0 71.0 69.9 61.1 48.2 4.6 2.5 64.6 34.9 54.0 46.60 39.2
3.9 2.3 1.7 0.7 2.2 4.1 0 2.3 5 14.1 4.8 0.2 1.1 0.0 0.0 4.1 5.0 1.6 1.6 1.3 3.0 1.3 2.8 0.0 0.3 0.4 0 0.0 0.1 7.0 3.5 0.0 1.0 5.0 2.9 12.4 4.0 0.4 0.0 1.1 5.0 4.0 6.0 3.3 4.2 5.6 2.0 6.7 5.6 0.0 1.60 4.10
Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y
Ya Ya Ya Ya Ya Ya Ya Ya Y Ya Ya Y Ya Ya
Y Y Y Y Y Y Y
Y
Y Y Y Y Y Y Y Y Y Y
Y Y Y Y Y Y Y Y Y Ya Ya Y Ya Ya Ya Y Ya Ya Y Y Y Y Y Y Y Y Y Ya Ya Y Ya Y Y Y Y Y
SANS
Yb Y Yb Yb Y Yb Y Yb Y Y Yb Y Y Y
Yb Y Y Yb Y Y Yb
Y Y Y Y Yb Yb Yb Yb Y Yb
⁎ max = maximum vitrinite reflectance; mmf = mineral matter free; db = dry basis. Note that maceral analysis were performed at CSIRO with Australian standards AS 2856.1 and AS 2856.2, and vitrinite reflectance were measured according to AS 2856.3.
3. Results and discussion
indigenous coal sample and the coal saturated by a gas or liquid, using the technique of “contrast matching” (Melnichenko et al., 2012). The porosity data here was obtained using a time-of-flight SANS instrument, BILBY (Sokolova et al., 2016) at ANSTO in Sydney, Australia. The scattering intensity from each sample was measured in air and then after addition of a 50:50 hexane-d-hexane mixture following the procedures detailed in Sakurovs et al., 2018. This was used to determine the relative number of all of the pores, and pores inaccessible to hexane, over the pore size range 8–50 nm. The scattering intensity is used as a proxy indicator of the relative numbers of pores at each pore size. Accessible pores are given by the difference between scattering intensity in the dry coal and that in the solvent.
Table 2 lists the sorption kinetics data obtained for the coals examined in this study. Table 2 shows that the RMSR values for CO2 are generally smaller than those for CH4, which is due to the faster and greater sorption and hence better fit quality for CO2 than CH4. 3.1. Relationships between rate of sorption, capacity for sorption and coal porosity 3.1.1. Sorption by coals for CH4 and CO2 The ratio of sorption rates for CO2 and CH4 was found to differ significantly between the coals. Fig. 2 shows CO2 and CH4 sorption 79
International Journal of Coal Geology 200 (2018) 77–86
A. Kiani et al.
Fig. 1. A schematic diagram of the SETARAM sorption rig process. Table 2 Kinetics of sorption of CH4 and CO2. Coal sample
Australia
Australia-Illawarra
USA
South America South Africa
Europe New Zealand China
CH4
Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 25 26 27 29 30 31 32 37 40 41 42 43 44 45 47 48 49 50
CO2
Minf/Mend
k (hr-1)
β
RMSR
Minf/Mend
k (hr-1)
β
RMSR
0.98 0.98 1.14 1.29 1.48 1.23 1.55 2.86 0.99 1.08 1.26 1.33 1.40 1.32 1.00 1.57 1.19 2.05 1.34 1.67 1.29 1.21 1.27 1.68 1.90 1.05 1.03 1.01 1.98 1.02 1.41 1.61 4.16 1.28
249.5 5.33 0.587 0.093 0.020 0.098 0.037 0.015 39.52 0.076 0.161 0.161 0.093 0.107 2.819 0.021 0.048 0.012 0.036 0.017 0.046 0.050 0.065 0.022 0.011 0.596 1.318 0.628 0.009 0.139 0.034 0.031 0.003 0.051
0.34 0.30 0.25 0.43 0.45 0.53 0.43 0.40 0.34 0.53 0.30 0.25 0.29 0.44 0.30 0.41 0.48 0.41 0.58 0.48 0.53 0.57 0.41 0.48 0.45 0.30 0.28 0.36 0.42 0.48 0.49 0.54 0.40 0.42
0.0092 0.0182 0.0138 0.0057 0.0065 0.0125 0.0153 0.0090 0.0104 0.0057 0.0111 0.0244 0.0175 0.0090 0.0165 0.0058 0.0061 0.0051 0.0082 0.0026 0.0116 0.0094 0.0075 0.0101 0.0064 0.0197 0.0129 0.0176 0.0125 0.0079 0.0091 0.0064 0.0096 0.0075
1.00 0.99 1.08 1.01 1.11 1.01 1.02 1.05
615.70 43.12 2.68 1.69 0.18 0.52 0.81 0.62 103.0 0.77 2.33 5.16 3.30 0.83 20.14 0.83 0.71 0.41 0.37 0.38 0.21 0.16 1.94 0.36 0.47 3.99 5.37 1.44 0.56 3.01 0.35 0.49 0.087 2.18
0.42 0.26 0.25 0.44 0.45 0.51 0.43 0.43 0.33 0.50 0.31 0.27 0.31 0.38 0.25 0.46 0.46 0.41 0.49 0.48 0.49 0.47 0.43 0.47 0.46 0.23 0.30 0.32 0.42 0.47 0.48 0.47 0.38 0.45
0.0090 0.0128 0.0104 0.0021 0.0051 0.0039 0.0025 0.0026
1.02 1.01 1.03 1.03 1.06 1.01 1.02 1.03 1.07 1.03 1.01 1.05 1.09 1.00 1.02 1.02 1.03 1.00 1.02 1.07 1.00 1.01 1.011 1.23 1.00
0.0031 0.0058 0.0075 0.0063 0.0066 0.0083 0.0078 0.0050 0.0038 0.0023 0.0040 0.0042 0.0052 0.0075 0.0087 0.0075 0.0054 0.0039 0.0069 0.0056 0.0033 0.0064 0.0039 0.0047 0.0047
values of β for CO2 and CH4 were close, which was consistent with the findings of Keshavarz et al. (2017) and Staib et al. (2015b) who previously suggested that this parameter was a characteristic of the coal and should be the same for all gases. Because the coals from the Illawarra region in New South Wales, Australia behaved differently to the other Australian coals, the coals named as from Australia in this paper exclude those sourced from the Illawarra region.
curves for two coals whose ratios of sorption rates for the two gases was very different. Fig. 2 also shows that the rate of sorption by coals for CO2 were faster than that for CH4. Table 2 and Fig. 3 show that the sorption rates (k) of CH4 and CO2 varied between different coals by over six orders of magnitude. Fig. 4 shows the other kinetic parameter, the dispersion of sorption rate, β, calculated for CO2 and CH4 sorption in the all coals investigated. The 80
International Journal of Coal Geology 200 (2018) 77–86
A. Kiani et al.
Fig. 4. Dispersion of sorption rate (β) for CO2 versus that for CH4 obtained from all coals investigated.
Fig. 5. The ratio of sorption rates of CO2 to CH4 versus the sorption rate of CH4. Fig. 2. Sorption curves of CO2 and CH4 for (a) Coal 16 with sorption rates ratio of 39 and (b) Coal 6 with sorption rates ratio of 5.
Fig. 6. Capacities for sorption of all coals investigated versus their rates of sorption for CO2. Fig. 3. Sorption rates of all coals investigated for CH4 versus those for CO2 (data from Table 2).
pores. Fig. 6 illustrates the sorption capacities of all coals for CO2 versus their sorption rates. Except for one coal that had both high sorption capacity and high sorption rate, there was only a weak trend of increasing sorption rate with sorption capacity, indicating the two are not strongly correlated. Thus, the structures in coal that control the amount
Fig. 5 shows the ratio of sorption rates (CO2 /CH4) versus the sorption rate of CH4. The ratio was greater at slow sorption rates. This suggests that the coals that have more restricted flow have finer pores that preferentially allow the CO2 to penetrate than the coals with larger 81
International Journal of Coal Geology 200 (2018) 77–86
A. Kiani et al.
Table 3 Relative numbers of total pores and accessible pores for different sizes of pores Coal sample
Australia
Australia-Illawarra
USA
South America Canada South Africa
Europe
Total pores
Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal
2 3 4 5 10 12 13 15 25 26 27 29 31 32 36 37 38 39 40 41 42 43 44 45
Accessible pores
50 nm
25 nm
12 nm
8 nm
50 nm
25 nm
12 nm
8 nm
547.73 508.40 129.32 208.39 314.20 451.34 419.37 723.83 203.43 134.13 169.71 200.31 192.90 392.29 394.69 235.10 407.63 284.87 196.69 412.89 517.46 346.40 324.29 277.52
36.23 38.12 8.74 17.62 27.27 30.98 30.20 50.65 12.32 8.94 10.16 16.21 16.89 24.80 34.80 17.08 28.37 17.10 13.56 34.50 40.93 28.41 25.28 24.69
3.21 4.35 0.765 1.99 2.91 2.79 2.84 4.88 1.15 0.881 0.891 1.28 1.66 2.27 3.33 1.72 2.44 1.50 1.30 3.75 4.38 2.55 2.31 2.0
0.84 1.01 0.23 0.452 0.60 0.53 0.61 0.92 0.233 0.218 0.184 0.27 0.43 0.44 0.76 0.37 0.44 0.30 0.28 0.85 0.96 0.67 0.51 0.41
350.28 333.96 52.27 72.53 7.92 303.59 289.56 486.50 86.64 56.45 59.59 58.86 45.71 202.068 93.68 53.82 185.67 208.89 68.26 141.53 265.34 123.45 112.58 43.27
20.23 21.91 2.38 4.80 0.68 17.36 19.37 27.65 3.92 2.95 2.51 2.05 2.69 10.27 4.80 2.97 9.59 11.76 2.94 10.67 19.40 9.19 5.59 0.95
2.58 2.15 0.137 0.47 0.11 1.32 1.81 2.13 0.27 0.276 0.15 0.062 0.18 0.82 0.49 0.24 0.65 0.93 0.27 1.15 2.05 0.87 0.39 0.05
0.49 0.42 0.028 0.074 0.012 0.22 0.34 0.36 0.045 0.060 0.06 0.00 0.065 0.143 0.084 0.027 0.110 0.150 0.049 0.290 0.429 0.225 0.054 0.0006
of sorption are not strongly correlated to the structures in coal that control the rate of sorption, in bituminous coals. The Australian coals excluding those from the Illawarra region generally show greater capacity for sorption than the other coals for the same rate of sorption.
3.1.2. Sorption properties and coal porosity Table 3 lists the total and accessible porosity of some of the coals investigated in this study. It should be noted here that due to the competitive beam time at ANSTO, the porosity test using SANS was conducted only for some coals. Fig. 7 shows that the total number of 50 nm pores correlated with the number of accessible 50 nm pores, for all coals investigated. Similar trends are obtained between the total number of pores and number of accessible pores for the other pore sizes. The total number of 50 nm pores are therefore used to exemplify the relationships between porosity and rates and amount of sorption. Fig. 8a shows the rates of sorption of CO2 into the coals from Australia and other regions (USA/Europe, South Africa, China and South America) against the total number of 50 nm pores of these coals
Fig. 8. Rates of gas sorption of (a) CO2 and (b) CH4 in coals from different regions versus the total number of 50 nm pores in the coals.
Fig. 7. Total number of 50 nm pores versus the number of 50 nm accessible pores. 82
International Journal of Coal Geology 200 (2018) 77–86
A. Kiani et al.
Fig. 10. Capacities for maximum sorption of CH4 and CO2 in coals from different regions versus the total number of 50 nm pores.
3.2. Relationships between gas sorption and coal properties 3.2.1. Effect of maceral composition Sakurovs et al., 2018 indicated that the number of pores in the range of 8–50 nm increased with increasing inertinite content for nonIllawarra Australian coals. Considering the exponential relationship between gas sorption rates and the number of pores, an exponential relationship between the sorption rates and inertinite content is also expected. Fig. 11a shows the sorption rates of CH4 and CO2 into the Australian coals versus their inertinite content. The rates increased exponentially with increasing inertinite content. Fig. 11b shows that, in contrast, the relationship between the sorption rates and inertinite content for non-Australian coals was much weaker. If the trend lines in Fig. 11a are extrapolated to 100% vitrinite, and 100% inertinite, the ratio of sorption rate parameters (k) of CO2 and 0.1549 × exp (9.65) 0.1549 CH4 are, respectively, as 0.0065 = 23.8, and 0.0065 × exp (12.03) = 2.2 . This is consistent with Figs. 4 and 5: greater sorption rate ratios are observed for the coals containing fewer larger pores. Even though the gas sorption rates were sensitive to maceral composition in the Australian coals (Fig. 11a), the capacity for maximum sorption was found to be independent of the inertinite content. Fig. 12 shows the capacity for maximum sorption of different coals for CO2 and CH4 plotted against inertinite content. Fig. 12 also shows that the capacity for maximum gas sorption of Australian coals was generally greater than that of coals from elsewhere regardless of their inertinite content. Therefore, the difference between the capacities for gas sorption of Australian coals and other regions was more likely due to differences in numbers of accessible < 5 nm pores.
Fig. 9. Dispersion of sorption rates (β) in coals versus the total number of 50 nm pores (relative values) in the coals from different regions for (a) CO2 and (b) CH4
obtained using SANS. Fig. 8b shows the corresponding rates of sorption for CH4. These figures show that the rates of sorption of CO2 and CH4 increased exponentially with the total number of these pores. Results from Australian and non-Australian coals showed the same trend. Fig. 9 shows that the dispersion of sorption rates (β) for different coals decreased with increasing number of 50 nm pores. We attribute this relationship to variation in the pore size and number in the coals. When the total number of pores in the 8–50 nm size range was small, the diffusion of gas in the smaller pores dominated the penetration rates and hence the dispersion of sorption rate was narrow (β was large). With increasing the total number of pores and hence the total number of open 8–50 nm pores, the distribution of pore sizes was broader and hence, the dispersion of sorption rates was broader (β was smaller). Fig. 10 shows the relationship between the capacity for maximum sorption of the coals from Australia and other regions (South Africa, China and US/Europe) for CH4 and CO2 and their number of 50 nm pores. In contrast to the significant variation of rates of sorption with the number of nanopores (8–50 nm), the capacity for maximum sorption was not sensitive to the number of these pores. Since it is believed that most gas in coal is adsorbed in pores < 5 nm (White et al., 2005), the lack of correlation between capacity for sorption and numbers of 8–50 nm pores indicates that the numbers of sub nanometre size (< 5 nm) pores in coal is independent of the numbers of pores in the 850 nm size range.
3.2.2. Effect of rank Rank also affects gas behaviour in coal (Crosdale et al., 1998; Adeboye and Bustin, 2013; Keshavarz et al., 2017). Fig. 13 shows the sorption data for all coals investigated versus their rank. The rates of gas sorption in the non-Illawarra Australian coals with less than 70% vitrinite content generally decreased with increasing rank. Rank had no discernible effect on the sorption rate of the vitrinite-rich Australian coals (vit > 70%) over the rank range investigated, and for coals from other sources above Rmax of 1%. This suggests that for this series of coals, rank may affect the gas diffusion properties of inertinite more than it does vitrinite. However, this would need further characterisation of high volatile inertinite rich bituminous coals since in this data set there was a fortuitous correlation between rank and inertinite for the five coals investigated that had high inertinite. The total number of 8nm pores shows a weak trend with coal rank; as the rank increases the total number of pores decreases. However, a 83
International Journal of Coal Geology 200 (2018) 77–86
A. Kiani et al.
Fig. 11. Rates of sorption of CH4 and CO2 for (a) the Australian coals excluding Illawarra ones, and (b) the non-Australian coals, versus inertinite content.
Fig. 12. Capacities for maximum gas sorption of (a) CO2 and (b) CH4 in coals from different regions versus their inertinite content.
larger set of coals of a wide range of rank would be necessary to confirm this trend (Fig. 14). Fig. 15 shows the capacity for maximum sorption of all coals investigated here for CO2 and CH4 versus their rank. The sorption capacity of gases generally tended to decrease with increasing rank. It is clear that the Australian coals posed greater sorption capacities than the other coals. The trends are similar to those observed previously. In this paper, it has been established that the capacity for sorption and the rate of sorption are unrelated, and hence the number of 8-50 nm pores in coals is unrelated to the number of finer pores. This suggests that the mechanisms by which these differently sized pores are formed is independent. The models used to predict coal structure therefore need to consider both size ranges to get a full picture of the structure of their coal. Since it is the 8-50 nm pores that appear to control the rate of sorption, models of coal structure would need to take careful consideration of this size range to explain gas transport through coal matrix. In previous studies, several transport models were developed based on different interpretations of coals pores structure (Bhatia, 1987). It was clear that a single distribution model cannot be applied to many cases. For example, a model suggested by Ruckenstein et al. (1971) neglecting concentration gradient and transport in macro pores was found to fit well the data of Nandi and Walker (1970), however this model was suggested to show some degree of deviation from other experimental data due to this assumption (Bhatia, 1987). Recent studies have also shown that the gas sorption in coal matrix
has only little effect on the long-term gas production, while it has significant importance in short-term production (Sawyer et al., 1987; Reid et al., 1992). Therefore if the rates of sorption obtained here are consistent with those obtained on larger scale extraction processes, the results suggest that inertinite-rich coal seams in Australia excluding Illawarra would have generally high (initial) rates of methane extraction, but the total amount extractable is not relatable to the initial extraction rate. The inertinite-rich coals from other sources (e.g. Illawarra) would not be so extractable, which agrees with the findings of Black and Aziz (2008). It is noted that the diffusion of gas through cleats is another determining factor specifically in long-term gas production in enhanced coal bed methane processes, and can limit the gas flow (Pillalamarry et al., 2011; Harpalani, 1996; Keshavarz et al., 2017). In those cases, where movement of gas through the cleats is slow, even the fast desorption of CH4 from coal matrix would have no considerable effect on the gas production amount. The results of this work also show that the ratio of sorption rates between CO2 and CH4 varies significantly (2–20) between different coals. In the cases of CO2-ECBM, the ratio of rates can affect the CH4 production and CO2 sequestration, and therefore cannot be simply considered the same for different coals. For example, if the ratio of sorption rates for CO2 and CH4 is not large enough, CO2 spreads into the coal seam due to the pressure gradient and reaches the exit point without efficiently displacing of CH4 (Keshavarz et al., 2017). Furthermore, the exponential relationships found for the CO2 and CH4 84
International Journal of Coal Geology 200 (2018) 77–86
A. Kiani et al.
Fig. 13. The variation of sorption rates of (a) CO2 and (b) CH4 versus rank for all coals investigated. Note that the coals marked Australia exclude coals from the Illawarra region.
that predicted by models developed based on coals sourced from Eastern US and Europe (Diessel, 1983; Diez et al., 2002; Gransden et al., 1991). One explanation for this difference is that the Australian and Western Canadian coals have more fusible inertinite than the other coals. However, Diessel and Wolff-Fischer (1987) later found considerable amount of fusible inertinite in Carboniferous coals as well. Therefore, a major difficulty with this explanation is that there is no proffered and testable causal explanation of how the presence of fusible inertinite from Australian and Canadian coals improve coke strength but those from other sources do not. The work presented here suggests some two testable explanations of why these coals from these different origins differ in their ability to make stronger coke from low fluidity coal. - The difference in behaviour of these coals are due to the difference in the microstructure of their non-fusible inertinites. We established here that inertinites in coals sourced from Australia excluding Illawarra have substantially greater nanoporosity (size 8–50 nm) and permeability to methane than inertinites sourced from elsewhere. Therefore, during coking, these inertinites may allow more ready escape of volatile material from the plastic layer. This would result in decreased swelling and coking pressure. If the volatiles released were low molecular materials that had no other effect on coke properties, the properties of the product coke would be otherwise unaffected. In other coals, release of the low molecular weight gases reduces swelling but has no effect on coke properties. This idea is testable as adding inertinites from Illawarra to coking
Fig. 14. Total number of pores less than 8 nm in all coals investigated versus rank.
sorption rates with inertinite contents, and the greater ratio of their sorption rates for the vitrinite-rich coals can be applied to the more accurate modelling of gas transport in different coals. Another motivation for this work was to identify regional differences in coals sourced from Australia and elsewhere. This is to explain the well-known finding that low fluidity coals sourced from Australia and Western Canada can produce cokes that are better in quality than
Fig. 15. (a) CO2 and (b) CH4 capacity for sorption of coals investigated versus their rank. 85
International Journal of Coal Geology 200 (2018) 77–86
A. Kiani et al.
Research Program (number: C24060).
coal blends should reduce dilatation, but inertinites sourced from elsewhere should not reduce dilatation to the same extent when added to blends. But their impact on coke properties should be similar. - The systematic differences in capacity for gas sorption between coals from Australia and other sources that is independent of maceral composition suggests that there may be systematic differences in the nanostructure of vitrinites from these sources. The coking properties of vitrinite-rich coals from different sources could be systematically different as well.
References Adeboye, O.O., Bustin, R.M., 2013. Variation of gas flow properties in coal with probe gas, composition and fabric: examples from western Canadian sedimentary basin. Int. J. Coal Geol. 108, 47–52. Bhatia, S.K., 1987. Modelling the pore structure of coal. AICHE J. 33 (10), 1707. Black, D.J., Aziz, N., 2008. Improving UIS gas drainage I underground coal mines. In: Coal Operators’ Conference. University of Wollongong & The Australian Institute of Mining and Metallurgy, pp. 186–196. Busch, A., Gensterblum, Y., 2011. CBM and CO2-ECBM related sorption processes in coal: a review. Int. J. Coal Geol. 87 (2), 49–71. Busch, A., Gensterblum, Y., Krooss, B.M., 2007. High-pressure sorption of nitrogen, carbon dioxide and their mixtures on Argonne premium coals. Energy Fuel 21, 1640–1645. Crosdale, P.J., Beamish, B.B., Valix, M., 1998. Coalbed methane sorption related to coal composition. Int. J. Coal Geol. 35 (1), 147–158. Day, S., Duffy, G., Sakurovs, R., Weir, S., 2008. Effect of coal properties on CO2 sorption capacity under supercritical conditions. IJGGC 2, 342–352. Diessel, C.F.K., 1983. Carbonization reactions of inertinite macerals in Australian coals. Fuel 62, 883–892. Diessel, C.F.K., Wolff-Fischer, E., 1987. Coal and coke petrographic investigations into the fusibility of Carboniferous and Permian coking coals. Int. J. Coal Geol. 9, 87–108. Diez, M.A., Alvarez, R., Barriocanal, C., 2002. Coal for metallurgical coke production: predictions of coke quality and future requirements for cokemaking. Int. J. Coal Geol. 50, 389–412. Goodman, A.L., Busch, A., Bustin, M., Chikatamarla, L., Day, S., Duffy, G.J., Fitzgerald, J.E., Gasem, K.A.M., Gensterblum, Y., Hartman, C., Jing, C., Krooss, B.M., Mohammed, S., Pratt, T., Robinson, R.L., Romanov, V., Sakurovs, R., Schroeder, K., White, C.M., 2007. Interlaboratory comparison. II. CO2 isotherms measured on moisture-equilibrated Argonne premium coals at 55 C and 15 MPa. Int. J. Coal Geol 72, 153–164. Gransden, J.F., Jorgensen, J.G., Manery, N., Price, J.T., Ramey, N.J., 1991. Applications of microscopy to coke making. Int. J. Coal Geol. 19, 77–107. Harpalani, S. 1996. Personal communication. Harpalani, S., Prusty, B.K., Dutta, P., 2006. Methane/CO2 sorption modeling for coalbed methane production and CO2 sequestration. Energy Fuel 20 (4), 1591–1599. Karacan, C.Ö., 2003. Heterogeneous sorption and swelling in a confined and stressed coal during CO2 injection. Energy Fuel 17, 1595–1608. Keshavarz, A., Sakurovs, R., Grigore, M., Sayyafzadeh, M., 2017. Effect of maceral composition and coal rank on gas diffusion in Australian coals. Int. J. Coal Geol. 173, 65–75. Mastalerz, M., Goodman, A., Chirdon, D., 2012. Coal lithotypes before, during, and after exposure to CO2: insights from direct Fourier transform infrared investigation. Energy Fuel 26, 3586–3591. Mayo, S., Josh, M., Kasperczyk, D., Kear, J., Zhang, J., Dautriat, J., Pervukhina, M., Clennell, M., Sakurovs, R., Sherwood, N., Maksimenko, A., Hall, C., 2018. Dynamic micro-CT study of gas uptake in coal using Xe, Kr and CO2. Fuel 212, 140–150. Melnichenko, B.Y., He, L., Sakurovs, R., Kholodenko, L.A., Blach, T., Mastalerz, M., Radlinski, P.A., Cheng, G., Mildner, D.F.R., 2012. Accessibility of pores to methane and carbon dioxide. Fuel 91, 200–208. Nandi, S.P., Walker, P.L., 1970. Activated diffusion of methane in coal. Fuel 49, 309–323. Ozdemir, E., Badie, I.M., Schroeder, k., 2004. CO2 capacity of Argonne premium coals. Fuel 83, 1085–1094. Pillalamarry, M., Harpalani, S., Liu, S., 2011. Gas diffusion behaviour of coal and its impact on production from coalbed methane reservoirs. Int. J. Coal Geol. 86, 342–348. Reid, G.W., Towler, B.F., Harris, H.G., 1992. Paper SPE 24360 Presented at the SPE Rocky Mountain Regional Meeting, Casper, Wyoming, 18–21 May 1992. pp. 425–432. Ruckenstein, E., Vaidyanathan, A.S., Youngquist, G.R., 1971. Sorption by solids with bidisperse pore structures. Chem. Eng. Sci. 26 (9), 1305–1318. Saghafi, A., Faiz, M., Robert, D., 2007. CO2 storage and gas diffusivity properties of coals from Sydney Basin. Aust. Int. J. Coal Geol. 70, 240–254. Sakurovs, R., Day, S., Weir, S., 2010. Relationships between the critical properties of gases and their high pressure sorption behaviour on coals. Energy Fuel 24, 1781–1787. Sakurovs, R., He, L., Melnichenko, Y.B., Radlinski, A.P., Blach, T., Lemmel, H., Mildner, D.F.R., 2012. Pore size distribution and accessible pore size distribution in bituminous coals. Int. J. Coal Geol. 100, 51–64. Sakurovs, R., Koval, L., Grigore, M., Sakolova, A., Ruppert, L.F., Melnichenko, Y.B., 2018. Nanometre-sized pores in coal: variations between coal basins and coal origin. Int. J. Coal Geol. https://doi.org/10.1016/j.coal.2017.11.010. Sawyer, W.K., Zuber, M.D., Kuuskra, V.A., Horner, D.M., 1987. Proceedings of the Coalbed Methane Symposium, Tuscaloosa, 16–19 November 1987. pp. 295–307. Seidle, J., 2011. Fundamentals of Coalbed Methane Reservoir Engineering. PennWell Books. Sokolova, A., Christoforidis, J., Eltobaji, A., Barnes, J., Darmann, F., Whitten, A.E., de Campo, L., 2016. BILBY: time-of-flight small angle scattering instrument. Neutron News 27, 9–13. Staib, G., 2013. Dispersive Diffusion of Gas in Coal: An Experimental Investigation into the Fundamentals of Gas Sorption and Diffusion in Coal. Griffith University. Staib, G., Sakurovs, R., Gray, E.M.A., 2015a. Dispersive diffusion of gases in coals. Part I: model development. Fuel 143, 612–619. Staib, G., Sakurovs, R., Gray, E.M.A., 2015b. Dispersive diffusion of gases in coals. Part II: an assessment of previously proposed physical mechanisms of diffusion in coal. Fuel 143, 620–629. Wang, K., Zang, J., Feng, Y., Wu, Y., 2014. Effects of moisture on diffusion kinetics in Chinese coals during methane desorption. J. Nat. Gas Sci. Eng. 21, 1005–1014. White, C.M., Smith, D.H., Jones, K.L., Goodman, A.L., Jikich, S.A., LaCount, R.B., DuBose, S.B., Ozdemir, E., Morsi, B.I., Schroeder, K.T., 2005. Sequestration of carbon dioxide in coal with enhanced coalbed methane recovery – a review. Energy Fuel 19, 659–724.
In this study we have restricted our attention to coals from Australia, Canada, the US and Europe. Whether other coals behave as Australian/Canadian coals or US/European coals or differently again remains to be established. 4. Conclusions The sorption extent and rate of coals for CO2 and CH4 was examined for a wide range of coals, sourced from different regions and basins. The sorption results were compared with the porosity data obtained from the small angle neutron scattering method (SANS). It was concluded that: - The rate of sorption of methane and carbon dioxide by coals increased exponentially with the total number of nanopores in the range of 8-50 nm. For the coals from Australia, except from the Illawarra region, rates of sorption increased exponentially with inertinite content, because they contained many pores in the 8-50 nm size range. - The ratio of sorption rates (k) of CO2 and CH4 was found to vary significantly between the coals and was smaller for coals with faster penetration rates. - The rates of gas sorption in the Australian coals with less than 70% vitrinite content generally decreased with increasing rank, while no discernible effect was obtained on the rate of sorption for the vitrinite-rich Australian coals. - The pore size distribution in 8–50 nm size range was not related to the capacity for maximum sorption. Hence the numbers of 8–50 nm pores in coals was independent of the number of < 5 nm pores. Overall, kinetics of sorption and the capacity for maximum sorption were not strongly correlated. - The capacity for maximum sorption of coals was found to be largely independent of inertinite content. However the capacity for maximum sorption of Australian coals were found greater than those of elsewhere regardless of inertinite content. This may indicate that the numbers of < 5 nm pores in Australian coals were systematically different from other coals sourced elsewhere. - The capacity for maximum sorption of coals generally decreased with increasing rank to a rank of 1% Rv,max and then levelled off. The variation of β with maceral composition was greater for coals from Australia than other sources, mainly due to the greater pore accessibility of inertinite in Australian coals. The dispersion of sorption rates β, was found almost the same for CO2 and CH4, indicating that the gas penetrated the same part of the coals. The relationships found in this paper can aid in a better fundamental understanding of adsorptiondesorption processes in coals, which has important implementations in predicting coal structure, modelling ECBM, and explaining the variation between coking properties of different coals. Acknowledgement This project was partially funded by the Australian Coal Association
86
Contents lists available at ScienceDirect
International Journal of Coal Geology journal homepage: www.elsevier.com/locate/coal
Gas sorption capacity, gas sorption rates and nanoporosity in coals a,⁎
a
a
Ali Kiani , Richard Sakurovs , Mihaela Grigore , Anna Sokolova a b
T
b
CSIRO Energy, 11 Julius Avenue, North Ryde 2113, Australia ANSTO, New Illawarra Road, Lucas Heights, NSW 2234, Sydney, Australia
A R T I C LE I N FO
A B S T R A C T
Keywords: Bituminous coal Rates of gas sorption Methane Carbon dioxide Porosity Macerals
Bituminous coals from a wide range of sources (including Australia, New Zealand, Europe, China, South America, Canada, the US and South Africa) were characterised by their capacity for gas sorption, rate of gas sorption of CO2 and CH4, and their nanoporosity (pore size distribution less than 50 nm radius) in order to identify the relationships between them. The following new relationships were established: The rate of gas sorption was unrelated to the capacity for gas sorption. The rate of gas sorption for CH4 and CO2 increased exponentially with the amount of total and accessible porosity in the size range 8–50 nm (with no influence of coal origin on the relationship being discerned), suggesting that the extent of porosity of coals in this size range controls the rates of gas sorption in coals. In contrast, the capacity for gas sorption was only weakly related to pore numbers in this size range, which shows that the number of 8–50 nm pores do not control capacity for gas sorption. Moreover, this difference in relationship shows the number of pores of the size where gas is sorbed predominantly (< 5 nm) does not correlate strongly with the number of larger pores. Both the number of pores and rates of gas sorption tended to increase with inertinite content but the relationship with inertinite content differed for coals from different sources. The inertinite-rich coals from Australia (except those from the Illawarra region) had both the greatest porosity and gas penetration rates, whereas in coals sourced from other regions, although the gas penetration rate increased with inertinite content, the effect was not so strong. The rates of sorption in the inertinite-rich coals also tended to decrease with increasing rank below 0.9% Rv,max. In contrast to the results obtained with kinetic studies, we found no overall trend of capacity for gas sorption with maceral composition, though the Australian bituminous coals generally had greater capacity than the other bituminous coals examined. This suggests that not only the number of 8–50 nm pores in coals sourced from Australia (not those from the Illawarra region) and elsewhere are different, the number density of accessible < 5 nm pores (not directly measurable in coals by SANS) may also be systematically different between these coals. The relationships developed in this study have important implications in predicting coal structure, fundamental understanding of gas transport through coal beds, and explaining the variation of coking properties of coals sourced from Australia and elsewhere.
1. Introduction
of sorption varied from 2 to 10 (Harpalani et al., 2006). Difference in the capacity for maximum sorption of CO2 and CH4 has been attributed to the different critical temperatures of these gases (Sakurovs et al., 2010). A number of studies investigated the effects of coal properties on sorption behaviour at high pressures (Ozdemir et al., 2004; Saghafi et al., 2007; Day et al., 2008); they found a minimum in capacity for sorption versus rank. Different groups have found different relationships between capacity for sorption and maceral composition, and regional effects have been proposed as one cause for this variation (Sakurovs et al., 2018; Day et al., 2008). A second critical characteristic is the rate at which gas is sorbed and
In recent years, attention has been attracted toward gas flow in coals due to the increasing demand for enhanced production of coal bed methane and reducing fugitive gas emission from coal industries. CO2 injection into coals also needs a thorough understanding of gas behaviour in coals (Wang et al., 2014; Seidle, 2011). This behaviour depends on the characteristics of the coal and gas. One important characteristic of coal is its capacity for gas sorption. This has been extensively investigated (Goodman et al., 2007; Busch et al., 2007; Busch and Gensterblum, 2011). It was found that coals absorbed CO2 more strongly than CH4, however the ratio of the extent ⁎
Corresponding author. E-mail address: [email protected] (A. Kiani).
https://doi.org/10.1016/j.coal.2018.10.012 Received 17 July 2018; Received in revised form 28 October 2018; Accepted 29 October 2018 Available online 30 October 2018 0166-5162/ Crown Copyright © 2018 Published by Elsevier B.V. All rights reserved.
International Journal of Coal Geology 200 (2018) 77–86
A. Kiani et al.
characterisation was supplied, for commercial reasons. All samples were crushed to < 1 mm with minimum fines based on the standard procedure suggested by Staib (2013) (the petrographic properties of coals can therefore be assumed unchanged); the 0.5–1.0 mm fraction was used for characterisation by neutron scattering, capacity for gas sorption and kinetics of sorption. The samples were stored in sealed containers at −18 °C.
released from coals. This also has been extensively examined (Busch and Gensterblum, 2011). There is evidence that the rate of penetration of a gas into coal particles varies significantly, even within a given coal particle. Using X-ray CT, the CO2 diffusion rate in a bituminous coal sample was found to vary significantly in different parts of the sample; the penetration rate was higher in the inertinite component than in the vitrinite component (Karacan, 2003). Using Infra-Red Spectroscopy, Mastalerz et al. (2012) observed that the inertinite part of coals was saturated much faster than the other parts. In another study, Mayo et al. (2018) applied the micro-computed tomography (micro-CT) to study the gas uptake in coals using Kr, Xe and CO2. They found that the CO2 uptake rate was greater than the other gases in all cases, and the diffusion rates varied significantly between different coals. Staib et al. (2015a,b) suggested that the diffusion in coals was dispersive (that is, in some regions in coals diffusion was faster than in others) due to the pore size distribution in coals varying on a microscale. With this assumption they found that only two fitting parameters were required to characterise the sorption curve in coals: k, an average diffusion rate and β, which indicated the degree of dispersion of sorption rates. Keshavarz et al. (2017) introduced another fitting parameter to the model based on the fact that, due to the very slow equilibration in many coals, the amount of gas adsorbed at the end of the experiment (indicated as Mend) was less than the equilibrium value (indicated as Minf). The equation used is:
Mt / Mend = (Minf / Mend ){1–exp[−(kt ) β]}
2.2. Methods 2.2.1. Kinetics of gas sorption Kinetics of gas sorption were measured in a SETARAM PCTPro™ rig. The temperature of samples was maintained at 23 °C by using a temperature controller and insulating the sample holder. Helium gas was used to calibrate the volume of the sample cell and check the system for any leaks. An evacuation pump was also used to evacuate the system and sample from any contamination when required. The whole process was automated and controlled using the apparatus operating software. Fig. 1 shows the schematic diagram of the sorption rig. For each experiment, the coal sample was placed in a vacuum oven at a temperature of 60 °C under a vacuum pressure of −101.6 kPa for a minimum of 48-h evacuation. About 1 g subsample was taken from the main sample, weighed and loaded into the rig. The sample cell was charged with helium gas up to a pressure of around 5 bar to check the system for any leaks. Using the evacuation pump, the sample was then evacuated for a further 48 h under a vacuum pressure of −101.6 kPa. After this stage, the free volume of the sample holder was measured using helium, and this was used later to calculate the amount of gas sorbed by coals. After the helium measurement, the sample was evacuated for another 10 h. The gas was introduced at 1.5 bar intervals and at each step the sample was given at least 48 h to reach equilibration. It was previously shown (Keshavarz et al., 2017) that the sorption results were independent on pressure in this low-pressure range. The second step was chosen for the kinetics results presented here since it showed the greatest repeatability of the three. Experimental time, the mass of adsorbed gas, the gas pressure inside the sample holder, and the sample and reservoirs temperatures were recorded by a data acquisition system and used for analysis. The modified stretched exponential model (Equation 1) was applied to the experimental data to determine the fitting parameters (Minf/Mend, k and β). The Excel Solver Routine was used to obtain these sorption parameters by minimising the Sum of Squared Residuals (SSR) of the fit to the sorption data. The root mean square of residuals (RMSR) was calculated for each experiment to indicate the quality of fitting. The reproducibility of kinetic measurements was tested for a number of coals. The sorption rate parameter (k) had an associated percentage error (~ < 20% for CH4 and ~ < 10% for CO2). If kβ values (the term in Eq. 1) for different repeats is considered, a much smaller error (< 10% and < 5% for CH4 and CO2, respectively) is obtained. The error associated with β was found to be generally small (< 5%).
(1)
where Mend and Minf are the sorption amount obtained at the pressure and temperature of sorption kinetic tests. The sorption parameters (k and β) were found to vary significantly with coal characteristics such as rank, composition, geological source, and preparation conditions such as particle size and temperature. Previous studies of the effect of coal rank and composition on sorption kinetics have not agreed about the nature of the trends found (Crosdale et al., 1998; Adeboye and Bustin, 2013; Keshavarz et al., 2017). The lack of consistency has been attributed to regional effects: coals sourced from different basins showed different trends (Sakurovs et al., 2018). Small Angle Neutron Scattering (SANS) has been used to measure both closed and open porosity of coals on a nanometre size scale. The accessibility of pores varied with the physical and chemical properties of coals (rank, maceral composition, porosity, origin etc.). It was found that the accessibility of pores to CO2 and CH4 increased with increasing total porosity of coals, as interconnectivity of pores was more likely to be facilitated in high porosity coals (Melnichenko et al., 2012). Sakurovs et al., 2012 using SANS, concluded that the fraction of 8 nm pores that were accessible to CH4 increased with increasing inertinite content. More recently, Sakurovs et al. (2018) showed strong regional variations in nanoporosity of inertinites that was not due to the submaceral composition or geological age of the coals. They suggested that these differences in nanoporosity can be the reason of variations in gas sorption behaviour of coals sourced from different regions. In this study, we combined the information presented in previous publications (Day et al., 2008; Sakurovs et al., 2018) with new data to establish new relationships between kinetics of gas sorption, capacity for gas sorption and porosity of coals. The importance of these relationships in the context of coal structure, the enhanced coal bed methane processes and coking behaviour of coals is discussed. Bituminous coals with a wide range of characteristics sourced from a number of regions including Australia, New Zealand, Canada, the USA, Europe, Africa, Asia and South America were examined.
2.2.2. Capacity for gas sorption Sorption isotherms for CH4 and CO2 were measured in a high pressure gravimetric system at a constant temperature of 55 °C and different pressures up to 16 MPa following the procedure of Day et al. (2008). The capacity of maximum sorption and the heat of sorption were determined from the isotherms fitted using a modified DubininRaduschkevich equation (Sakurovs et al., 2010). 2.2.3. Porosity The SANS technique was applied to characterise coal porosity. In this technique, the intensity of scattered neutrons off materials as a function of scattering angle is used to determine pore size distributions (Melnichenko et al., 2012). The fraction of pores in materials accessible to fluids as a function of pore size can also be determined by comparing the SANS patterns (intensity of scattered neutrons) obtained from the
2. Experimental 2.1. Materials A total of 52 bituminous coals from a range of sources were studied. Data are shown in Table 1. Samples were de-identified and limited 78
International Journal of Coal Geology 200 (2018) 77–86
A. Kiani et al.
Table 1 The origin, physical and petrographic properties of the coal samples investigated. Data availability of different tests for each coal sample is shown by Y. The data obtained from Day et al., 2008 and Sakurovs et al., 2018 are denoted as Ya and Yb. Coal sample
Australia
Australia-Illawarra
USA
South America Canada South Africa
Europe
New Zealand China
Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52
Density (g/ cm3)
Ash (% db⁎)
Rv,max⁎ (%)
Vitrinite (vol.% mmf⁎)
Inertinite (vol.% mmf)
Liptinite (vol.% mmf)
Sorption rates
Sorption amount
1.422 1.391 1.344 1.316 1.331 1.313 1.376 1.365 1.505 1.293 1.473 1.357 1.348 1.367 – 1.350 1.519 1.552 1.365 1.471 1.319 1.329 1.416 1.625 1.368 1.375 – 1.481 1.357 1.312 1.324 1.381 1.363 1.446 1.372 1.330 1.405 1.387 1.418 1.504 1.546 1.641 1.593 1.365 1.363 1.353 1.295 1.387 1.386 1.408 1.407 1.370
7.7 8.3 5.1 7.2 7.4 5.6 8.4 10.0 18.7 6.1 21.3 6.4 7.4 8.8 7.1 12.0 17.6 20.8 11.4 25.5 4.9 5.8 9.1 8.9 9.8 16.9 5.1 4.1 5.3 9.0 4.8 15.5 8.6 6.5 17.0 9.1 10 16.9 22.8 27.0 25.2 5.7 5.8 3.6 2.5 24.8 10.13 9.49 9.72 9.72
0.69 0.9 1.03 0.99 0.89 0.95 1.63 1.08 0.8 0.7 0.77 1.29 1.16 1.43 1.18 0.79 0.81 0.62 0.8 0.8 0.8 0.8 0.48 1.93 1.21 1.27 1.29 1.40 1.61 0.98 0.9 1.29 1.68 0.46 0.76 0.85 0.84 1.05 1.22 1.28 0.7 0.7 0.74 1.34 1.22 0.55 1.11 0.81 0.91 1.49 1.27 0.99
29.7 33.9 63.6 90.9 88.7 82.7 83.9 74.3 20.2 68.3 61.8 59.1 69.1 76.7 56.8 84.2 10.6 23.9 64.0 40.3 64.3 59.5 58.9 48.3 85.4 48.7 32.6 28.1 81.7 72.5 89.4 87.3 89.0 85.0 82.2 69.9 80.0 84.5 66.7 71.7 42.0 25.0 24.1 35.6 47.6 89.8 95.5 28.7 59.5 46.0 51.8 56.7
66.4 63.8 34.7 8.4 9.1 13.2 16.1 23.4 74.8 17.6 33.4 40.7 29.8 23.3 43.2 11.7 84.4 74.5 34.3 58.4 32.7 39.2 38.3 51.7 14.3 50.9 68.4 71.9 18.2 20.5 7.1 12.7 10.0 10.0 14.9 17.7 16.0 15.1 33.3 27.2 53.0 71.0 69.9 61.1 48.2 4.6 2.5 64.6 34.9 54.0 46.60 39.2
3.9 2.3 1.7 0.7 2.2 4.1 0 2.3 5 14.1 4.8 0.2 1.1 0.0 0.0 4.1 5.0 1.6 1.6 1.3 3.0 1.3 2.8 0.0 0.3 0.4 0 0.0 0.1 7.0 3.5 0.0 1.0 5.0 2.9 12.4 4.0 0.4 0.0 1.1 5.0 4.0 6.0 3.3 4.2 5.6 2.0 6.7 5.6 0.0 1.60 4.10
Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y
Ya Ya Ya Ya Ya Ya Ya Ya Y Ya Ya Y Ya Ya
Y Y Y Y Y Y Y
Y
Y Y Y Y Y Y Y Y Y Y
Y Y Y Y Y Y Y Y Y Ya Ya Y Ya Ya Ya Y Ya Ya Y Y Y Y Y Y Y Y Y Ya Ya Y Ya Y Y Y Y Y
SANS
Yb Y Yb Yb Y Yb Y Yb Y Y Yb Y Y Y
Yb Y Y Yb Y Y Yb
Y Y Y Y Yb Yb Yb Yb Y Yb
⁎ max = maximum vitrinite reflectance; mmf = mineral matter free; db = dry basis. Note that maceral analysis were performed at CSIRO with Australian standards AS 2856.1 and AS 2856.2, and vitrinite reflectance were measured according to AS 2856.3.
3. Results and discussion
indigenous coal sample and the coal saturated by a gas or liquid, using the technique of “contrast matching” (Melnichenko et al., 2012). The porosity data here was obtained using a time-of-flight SANS instrument, BILBY (Sokolova et al., 2016) at ANSTO in Sydney, Australia. The scattering intensity from each sample was measured in air and then after addition of a 50:50 hexane-d-hexane mixture following the procedures detailed in Sakurovs et al., 2018. This was used to determine the relative number of all of the pores, and pores inaccessible to hexane, over the pore size range 8–50 nm. The scattering intensity is used as a proxy indicator of the relative numbers of pores at each pore size. Accessible pores are given by the difference between scattering intensity in the dry coal and that in the solvent.
Table 2 lists the sorption kinetics data obtained for the coals examined in this study. Table 2 shows that the RMSR values for CO2 are generally smaller than those for CH4, which is due to the faster and greater sorption and hence better fit quality for CO2 than CH4. 3.1. Relationships between rate of sorption, capacity for sorption and coal porosity 3.1.1. Sorption by coals for CH4 and CO2 The ratio of sorption rates for CO2 and CH4 was found to differ significantly between the coals. Fig. 2 shows CO2 and CH4 sorption 79
International Journal of Coal Geology 200 (2018) 77–86
A. Kiani et al.
Fig. 1. A schematic diagram of the SETARAM sorption rig process. Table 2 Kinetics of sorption of CH4 and CO2. Coal sample
Australia
Australia-Illawarra
USA
South America South Africa
Europe New Zealand China
CH4
Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 25 26 27 29 30 31 32 37 40 41 42 43 44 45 47 48 49 50
CO2
Minf/Mend
k (hr-1)
β
RMSR
Minf/Mend
k (hr-1)
β
RMSR
0.98 0.98 1.14 1.29 1.48 1.23 1.55 2.86 0.99 1.08 1.26 1.33 1.40 1.32 1.00 1.57 1.19 2.05 1.34 1.67 1.29 1.21 1.27 1.68 1.90 1.05 1.03 1.01 1.98 1.02 1.41 1.61 4.16 1.28
249.5 5.33 0.587 0.093 0.020 0.098 0.037 0.015 39.52 0.076 0.161 0.161 0.093 0.107 2.819 0.021 0.048 0.012 0.036 0.017 0.046 0.050 0.065 0.022 0.011 0.596 1.318 0.628 0.009 0.139 0.034 0.031 0.003 0.051
0.34 0.30 0.25 0.43 0.45 0.53 0.43 0.40 0.34 0.53 0.30 0.25 0.29 0.44 0.30 0.41 0.48 0.41 0.58 0.48 0.53 0.57 0.41 0.48 0.45 0.30 0.28 0.36 0.42 0.48 0.49 0.54 0.40 0.42
0.0092 0.0182 0.0138 0.0057 0.0065 0.0125 0.0153 0.0090 0.0104 0.0057 0.0111 0.0244 0.0175 0.0090 0.0165 0.0058 0.0061 0.0051 0.0082 0.0026 0.0116 0.0094 0.0075 0.0101 0.0064 0.0197 0.0129 0.0176 0.0125 0.0079 0.0091 0.0064 0.0096 0.0075
1.00 0.99 1.08 1.01 1.11 1.01 1.02 1.05
615.70 43.12 2.68 1.69 0.18 0.52 0.81 0.62 103.0 0.77 2.33 5.16 3.30 0.83 20.14 0.83 0.71 0.41 0.37 0.38 0.21 0.16 1.94 0.36 0.47 3.99 5.37 1.44 0.56 3.01 0.35 0.49 0.087 2.18
0.42 0.26 0.25 0.44 0.45 0.51 0.43 0.43 0.33 0.50 0.31 0.27 0.31 0.38 0.25 0.46 0.46 0.41 0.49 0.48 0.49 0.47 0.43 0.47 0.46 0.23 0.30 0.32 0.42 0.47 0.48 0.47 0.38 0.45
0.0090 0.0128 0.0104 0.0021 0.0051 0.0039 0.0025 0.0026
1.02 1.01 1.03 1.03 1.06 1.01 1.02 1.03 1.07 1.03 1.01 1.05 1.09 1.00 1.02 1.02 1.03 1.00 1.02 1.07 1.00 1.01 1.011 1.23 1.00
0.0031 0.0058 0.0075 0.0063 0.0066 0.0083 0.0078 0.0050 0.0038 0.0023 0.0040 0.0042 0.0052 0.0075 0.0087 0.0075 0.0054 0.0039 0.0069 0.0056 0.0033 0.0064 0.0039 0.0047 0.0047
values of β for CO2 and CH4 were close, which was consistent with the findings of Keshavarz et al. (2017) and Staib et al. (2015b) who previously suggested that this parameter was a characteristic of the coal and should be the same for all gases. Because the coals from the Illawarra region in New South Wales, Australia behaved differently to the other Australian coals, the coals named as from Australia in this paper exclude those sourced from the Illawarra region.
curves for two coals whose ratios of sorption rates for the two gases was very different. Fig. 2 also shows that the rate of sorption by coals for CO2 were faster than that for CH4. Table 2 and Fig. 3 show that the sorption rates (k) of CH4 and CO2 varied between different coals by over six orders of magnitude. Fig. 4 shows the other kinetic parameter, the dispersion of sorption rate, β, calculated for CO2 and CH4 sorption in the all coals investigated. The 80
International Journal of Coal Geology 200 (2018) 77–86
A. Kiani et al.
Fig. 4. Dispersion of sorption rate (β) for CO2 versus that for CH4 obtained from all coals investigated.
Fig. 5. The ratio of sorption rates of CO2 to CH4 versus the sorption rate of CH4. Fig. 2. Sorption curves of CO2 and CH4 for (a) Coal 16 with sorption rates ratio of 39 and (b) Coal 6 with sorption rates ratio of 5.
Fig. 6. Capacities for sorption of all coals investigated versus their rates of sorption for CO2. Fig. 3. Sorption rates of all coals investigated for CH4 versus those for CO2 (data from Table 2).
pores. Fig. 6 illustrates the sorption capacities of all coals for CO2 versus their sorption rates. Except for one coal that had both high sorption capacity and high sorption rate, there was only a weak trend of increasing sorption rate with sorption capacity, indicating the two are not strongly correlated. Thus, the structures in coal that control the amount
Fig. 5 shows the ratio of sorption rates (CO2 /CH4) versus the sorption rate of CH4. The ratio was greater at slow sorption rates. This suggests that the coals that have more restricted flow have finer pores that preferentially allow the CO2 to penetrate than the coals with larger 81
International Journal of Coal Geology 200 (2018) 77–86
A. Kiani et al.
Table 3 Relative numbers of total pores and accessible pores for different sizes of pores Coal sample
Australia
Australia-Illawarra
USA
South America Canada South Africa
Europe
Total pores
Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal Coal
2 3 4 5 10 12 13 15 25 26 27 29 31 32 36 37 38 39 40 41 42 43 44 45
Accessible pores
50 nm
25 nm
12 nm
8 nm
50 nm
25 nm
12 nm
8 nm
547.73 508.40 129.32 208.39 314.20 451.34 419.37 723.83 203.43 134.13 169.71 200.31 192.90 392.29 394.69 235.10 407.63 284.87 196.69 412.89 517.46 346.40 324.29 277.52
36.23 38.12 8.74 17.62 27.27 30.98 30.20 50.65 12.32 8.94 10.16 16.21 16.89 24.80 34.80 17.08 28.37 17.10 13.56 34.50 40.93 28.41 25.28 24.69
3.21 4.35 0.765 1.99 2.91 2.79 2.84 4.88 1.15 0.881 0.891 1.28 1.66 2.27 3.33 1.72 2.44 1.50 1.30 3.75 4.38 2.55 2.31 2.0
0.84 1.01 0.23 0.452 0.60 0.53 0.61 0.92 0.233 0.218 0.184 0.27 0.43 0.44 0.76 0.37 0.44 0.30 0.28 0.85 0.96 0.67 0.51 0.41
350.28 333.96 52.27 72.53 7.92 303.59 289.56 486.50 86.64 56.45 59.59 58.86 45.71 202.068 93.68 53.82 185.67 208.89 68.26 141.53 265.34 123.45 112.58 43.27
20.23 21.91 2.38 4.80 0.68 17.36 19.37 27.65 3.92 2.95 2.51 2.05 2.69 10.27 4.80 2.97 9.59 11.76 2.94 10.67 19.40 9.19 5.59 0.95
2.58 2.15 0.137 0.47 0.11 1.32 1.81 2.13 0.27 0.276 0.15 0.062 0.18 0.82 0.49 0.24 0.65 0.93 0.27 1.15 2.05 0.87 0.39 0.05
0.49 0.42 0.028 0.074 0.012 0.22 0.34 0.36 0.045 0.060 0.06 0.00 0.065 0.143 0.084 0.027 0.110 0.150 0.049 0.290 0.429 0.225 0.054 0.0006
of sorption are not strongly correlated to the structures in coal that control the rate of sorption, in bituminous coals. The Australian coals excluding those from the Illawarra region generally show greater capacity for sorption than the other coals for the same rate of sorption.
3.1.2. Sorption properties and coal porosity Table 3 lists the total and accessible porosity of some of the coals investigated in this study. It should be noted here that due to the competitive beam time at ANSTO, the porosity test using SANS was conducted only for some coals. Fig. 7 shows that the total number of 50 nm pores correlated with the number of accessible 50 nm pores, for all coals investigated. Similar trends are obtained between the total number of pores and number of accessible pores for the other pore sizes. The total number of 50 nm pores are therefore used to exemplify the relationships between porosity and rates and amount of sorption. Fig. 8a shows the rates of sorption of CO2 into the coals from Australia and other regions (USA/Europe, South Africa, China and South America) against the total number of 50 nm pores of these coals
Fig. 8. Rates of gas sorption of (a) CO2 and (b) CH4 in coals from different regions versus the total number of 50 nm pores in the coals.
Fig. 7. Total number of 50 nm pores versus the number of 50 nm accessible pores. 82
International Journal of Coal Geology 200 (2018) 77–86
A. Kiani et al.
Fig. 10. Capacities for maximum sorption of CH4 and CO2 in coals from different regions versus the total number of 50 nm pores.
3.2. Relationships between gas sorption and coal properties 3.2.1. Effect of maceral composition Sakurovs et al., 2018 indicated that the number of pores in the range of 8–50 nm increased with increasing inertinite content for nonIllawarra Australian coals. Considering the exponential relationship between gas sorption rates and the number of pores, an exponential relationship between the sorption rates and inertinite content is also expected. Fig. 11a shows the sorption rates of CH4 and CO2 into the Australian coals versus their inertinite content. The rates increased exponentially with increasing inertinite content. Fig. 11b shows that, in contrast, the relationship between the sorption rates and inertinite content for non-Australian coals was much weaker. If the trend lines in Fig. 11a are extrapolated to 100% vitrinite, and 100% inertinite, the ratio of sorption rate parameters (k) of CO2 and 0.1549 × exp (9.65) 0.1549 CH4 are, respectively, as 0.0065 = 23.8, and 0.0065 × exp (12.03) = 2.2 . This is consistent with Figs. 4 and 5: greater sorption rate ratios are observed for the coals containing fewer larger pores. Even though the gas sorption rates were sensitive to maceral composition in the Australian coals (Fig. 11a), the capacity for maximum sorption was found to be independent of the inertinite content. Fig. 12 shows the capacity for maximum sorption of different coals for CO2 and CH4 plotted against inertinite content. Fig. 12 also shows that the capacity for maximum gas sorption of Australian coals was generally greater than that of coals from elsewhere regardless of their inertinite content. Therefore, the difference between the capacities for gas sorption of Australian coals and other regions was more likely due to differences in numbers of accessible < 5 nm pores.
Fig. 9. Dispersion of sorption rates (β) in coals versus the total number of 50 nm pores (relative values) in the coals from different regions for (a) CO2 and (b) CH4
obtained using SANS. Fig. 8b shows the corresponding rates of sorption for CH4. These figures show that the rates of sorption of CO2 and CH4 increased exponentially with the total number of these pores. Results from Australian and non-Australian coals showed the same trend. Fig. 9 shows that the dispersion of sorption rates (β) for different coals decreased with increasing number of 50 nm pores. We attribute this relationship to variation in the pore size and number in the coals. When the total number of pores in the 8–50 nm size range was small, the diffusion of gas in the smaller pores dominated the penetration rates and hence the dispersion of sorption rate was narrow (β was large). With increasing the total number of pores and hence the total number of open 8–50 nm pores, the distribution of pore sizes was broader and hence, the dispersion of sorption rates was broader (β was smaller). Fig. 10 shows the relationship between the capacity for maximum sorption of the coals from Australia and other regions (South Africa, China and US/Europe) for CH4 and CO2 and their number of 50 nm pores. In contrast to the significant variation of rates of sorption with the number of nanopores (8–50 nm), the capacity for maximum sorption was not sensitive to the number of these pores. Since it is believed that most gas in coal is adsorbed in pores < 5 nm (White et al., 2005), the lack of correlation between capacity for sorption and numbers of 8–50 nm pores indicates that the numbers of sub nanometre size (< 5 nm) pores in coal is independent of the numbers of pores in the 850 nm size range.
3.2.2. Effect of rank Rank also affects gas behaviour in coal (Crosdale et al., 1998; Adeboye and Bustin, 2013; Keshavarz et al., 2017). Fig. 13 shows the sorption data for all coals investigated versus their rank. The rates of gas sorption in the non-Illawarra Australian coals with less than 70% vitrinite content generally decreased with increasing rank. Rank had no discernible effect on the sorption rate of the vitrinite-rich Australian coals (vit > 70%) over the rank range investigated, and for coals from other sources above Rmax of 1%. This suggests that for this series of coals, rank may affect the gas diffusion properties of inertinite more than it does vitrinite. However, this would need further characterisation of high volatile inertinite rich bituminous coals since in this data set there was a fortuitous correlation between rank and inertinite for the five coals investigated that had high inertinite. The total number of 8nm pores shows a weak trend with coal rank; as the rank increases the total number of pores decreases. However, a 83
International Journal of Coal Geology 200 (2018) 77–86
A. Kiani et al.
Fig. 11. Rates of sorption of CH4 and CO2 for (a) the Australian coals excluding Illawarra ones, and (b) the non-Australian coals, versus inertinite content.
Fig. 12. Capacities for maximum gas sorption of (a) CO2 and (b) CH4 in coals from different regions versus their inertinite content.
larger set of coals of a wide range of rank would be necessary to confirm this trend (Fig. 14). Fig. 15 shows the capacity for maximum sorption of all coals investigated here for CO2 and CH4 versus their rank. The sorption capacity of gases generally tended to decrease with increasing rank. It is clear that the Australian coals posed greater sorption capacities than the other coals. The trends are similar to those observed previously. In this paper, it has been established that the capacity for sorption and the rate of sorption are unrelated, and hence the number of 8-50 nm pores in coals is unrelated to the number of finer pores. This suggests that the mechanisms by which these differently sized pores are formed is independent. The models used to predict coal structure therefore need to consider both size ranges to get a full picture of the structure of their coal. Since it is the 8-50 nm pores that appear to control the rate of sorption, models of coal structure would need to take careful consideration of this size range to explain gas transport through coal matrix. In previous studies, several transport models were developed based on different interpretations of coals pores structure (Bhatia, 1987). It was clear that a single distribution model cannot be applied to many cases. For example, a model suggested by Ruckenstein et al. (1971) neglecting concentration gradient and transport in macro pores was found to fit well the data of Nandi and Walker (1970), however this model was suggested to show some degree of deviation from other experimental data due to this assumption (Bhatia, 1987). Recent studies have also shown that the gas sorption in coal matrix
has only little effect on the long-term gas production, while it has significant importance in short-term production (Sawyer et al., 1987; Reid et al., 1992). Therefore if the rates of sorption obtained here are consistent with those obtained on larger scale extraction processes, the results suggest that inertinite-rich coal seams in Australia excluding Illawarra would have generally high (initial) rates of methane extraction, but the total amount extractable is not relatable to the initial extraction rate. The inertinite-rich coals from other sources (e.g. Illawarra) would not be so extractable, which agrees with the findings of Black and Aziz (2008). It is noted that the diffusion of gas through cleats is another determining factor specifically in long-term gas production in enhanced coal bed methane processes, and can limit the gas flow (Pillalamarry et al., 2011; Harpalani, 1996; Keshavarz et al., 2017). In those cases, where movement of gas through the cleats is slow, even the fast desorption of CH4 from coal matrix would have no considerable effect on the gas production amount. The results of this work also show that the ratio of sorption rates between CO2 and CH4 varies significantly (2–20) between different coals. In the cases of CO2-ECBM, the ratio of rates can affect the CH4 production and CO2 sequestration, and therefore cannot be simply considered the same for different coals. For example, if the ratio of sorption rates for CO2 and CH4 is not large enough, CO2 spreads into the coal seam due to the pressure gradient and reaches the exit point without efficiently displacing of CH4 (Keshavarz et al., 2017). Furthermore, the exponential relationships found for the CO2 and CH4 84
International Journal of Coal Geology 200 (2018) 77–86
A. Kiani et al.
Fig. 13. The variation of sorption rates of (a) CO2 and (b) CH4 versus rank for all coals investigated. Note that the coals marked Australia exclude coals from the Illawarra region.
that predicted by models developed based on coals sourced from Eastern US and Europe (Diessel, 1983; Diez et al., 2002; Gransden et al., 1991). One explanation for this difference is that the Australian and Western Canadian coals have more fusible inertinite than the other coals. However, Diessel and Wolff-Fischer (1987) later found considerable amount of fusible inertinite in Carboniferous coals as well. Therefore, a major difficulty with this explanation is that there is no proffered and testable causal explanation of how the presence of fusible inertinite from Australian and Canadian coals improve coke strength but those from other sources do not. The work presented here suggests some two testable explanations of why these coals from these different origins differ in their ability to make stronger coke from low fluidity coal. - The difference in behaviour of these coals are due to the difference in the microstructure of their non-fusible inertinites. We established here that inertinites in coals sourced from Australia excluding Illawarra have substantially greater nanoporosity (size 8–50 nm) and permeability to methane than inertinites sourced from elsewhere. Therefore, during coking, these inertinites may allow more ready escape of volatile material from the plastic layer. This would result in decreased swelling and coking pressure. If the volatiles released were low molecular materials that had no other effect on coke properties, the properties of the product coke would be otherwise unaffected. In other coals, release of the low molecular weight gases reduces swelling but has no effect on coke properties. This idea is testable as adding inertinites from Illawarra to coking
Fig. 14. Total number of pores less than 8 nm in all coals investigated versus rank.
sorption rates with inertinite contents, and the greater ratio of their sorption rates for the vitrinite-rich coals can be applied to the more accurate modelling of gas transport in different coals. Another motivation for this work was to identify regional differences in coals sourced from Australia and elsewhere. This is to explain the well-known finding that low fluidity coals sourced from Australia and Western Canada can produce cokes that are better in quality than
Fig. 15. (a) CO2 and (b) CH4 capacity for sorption of coals investigated versus their rank. 85
International Journal of Coal Geology 200 (2018) 77–86
A. Kiani et al.
Research Program (number: C24060).
coal blends should reduce dilatation, but inertinites sourced from elsewhere should not reduce dilatation to the same extent when added to blends. But their impact on coke properties should be similar. - The systematic differences in capacity for gas sorption between coals from Australia and other sources that is independent of maceral composition suggests that there may be systematic differences in the nanostructure of vitrinites from these sources. The coking properties of vitrinite-rich coals from different sources could be systematically different as well.
References Adeboye, O.O., Bustin, R.M., 2013. Variation of gas flow properties in coal with probe gas, composition and fabric: examples from western Canadian sedimentary basin. Int. J. Coal Geol. 108, 47–52. Bhatia, S.K., 1987. Modelling the pore structure of coal. AICHE J. 33 (10), 1707. Black, D.J., Aziz, N., 2008. Improving UIS gas drainage I underground coal mines. In: Coal Operators’ Conference. University of Wollongong & The Australian Institute of Mining and Metallurgy, pp. 186–196. Busch, A., Gensterblum, Y., 2011. CBM and CO2-ECBM related sorption processes in coal: a review. Int. J. Coal Geol. 87 (2), 49–71. Busch, A., Gensterblum, Y., Krooss, B.M., 2007. High-pressure sorption of nitrogen, carbon dioxide and their mixtures on Argonne premium coals. Energy Fuel 21, 1640–1645. Crosdale, P.J., Beamish, B.B., Valix, M., 1998. Coalbed methane sorption related to coal composition. Int. J. Coal Geol. 35 (1), 147–158. Day, S., Duffy, G., Sakurovs, R., Weir, S., 2008. Effect of coal properties on CO2 sorption capacity under supercritical conditions. IJGGC 2, 342–352. Diessel, C.F.K., 1983. Carbonization reactions of inertinite macerals in Australian coals. Fuel 62, 883–892. Diessel, C.F.K., Wolff-Fischer, E., 1987. Coal and coke petrographic investigations into the fusibility of Carboniferous and Permian coking coals. Int. J. Coal Geol. 9, 87–108. Diez, M.A., Alvarez, R., Barriocanal, C., 2002. Coal for metallurgical coke production: predictions of coke quality and future requirements for cokemaking. Int. J. Coal Geol. 50, 389–412. Goodman, A.L., Busch, A., Bustin, M., Chikatamarla, L., Day, S., Duffy, G.J., Fitzgerald, J.E., Gasem, K.A.M., Gensterblum, Y., Hartman, C., Jing, C., Krooss, B.M., Mohammed, S., Pratt, T., Robinson, R.L., Romanov, V., Sakurovs, R., Schroeder, K., White, C.M., 2007. Interlaboratory comparison. II. CO2 isotherms measured on moisture-equilibrated Argonne premium coals at 55 C and 15 MPa. Int. J. Coal Geol 72, 153–164. Gransden, J.F., Jorgensen, J.G., Manery, N., Price, J.T., Ramey, N.J., 1991. Applications of microscopy to coke making. Int. J. Coal Geol. 19, 77–107. Harpalani, S. 1996. Personal communication. Harpalani, S., Prusty, B.K., Dutta, P., 2006. Methane/CO2 sorption modeling for coalbed methane production and CO2 sequestration. Energy Fuel 20 (4), 1591–1599. Karacan, C.Ö., 2003. Heterogeneous sorption and swelling in a confined and stressed coal during CO2 injection. Energy Fuel 17, 1595–1608. Keshavarz, A., Sakurovs, R., Grigore, M., Sayyafzadeh, M., 2017. Effect of maceral composition and coal rank on gas diffusion in Australian coals. Int. J. Coal Geol. 173, 65–75. Mastalerz, M., Goodman, A., Chirdon, D., 2012. Coal lithotypes before, during, and after exposure to CO2: insights from direct Fourier transform infrared investigation. Energy Fuel 26, 3586–3591. Mayo, S., Josh, M., Kasperczyk, D., Kear, J., Zhang, J., Dautriat, J., Pervukhina, M., Clennell, M., Sakurovs, R., Sherwood, N., Maksimenko, A., Hall, C., 2018. Dynamic micro-CT study of gas uptake in coal using Xe, Kr and CO2. Fuel 212, 140–150. Melnichenko, B.Y., He, L., Sakurovs, R., Kholodenko, L.A., Blach, T., Mastalerz, M., Radlinski, P.A., Cheng, G., Mildner, D.F.R., 2012. Accessibility of pores to methane and carbon dioxide. Fuel 91, 200–208. Nandi, S.P., Walker, P.L., 1970. Activated diffusion of methane in coal. Fuel 49, 309–323. Ozdemir, E., Badie, I.M., Schroeder, k., 2004. CO2 capacity of Argonne premium coals. Fuel 83, 1085–1094. Pillalamarry, M., Harpalani, S., Liu, S., 2011. Gas diffusion behaviour of coal and its impact on production from coalbed methane reservoirs. Int. J. Coal Geol. 86, 342–348. Reid, G.W., Towler, B.F., Harris, H.G., 1992. Paper SPE 24360 Presented at the SPE Rocky Mountain Regional Meeting, Casper, Wyoming, 18–21 May 1992. pp. 425–432. Ruckenstein, E., Vaidyanathan, A.S., Youngquist, G.R., 1971. Sorption by solids with bidisperse pore structures. Chem. Eng. Sci. 26 (9), 1305–1318. Saghafi, A., Faiz, M., Robert, D., 2007. CO2 storage and gas diffusivity properties of coals from Sydney Basin. Aust. Int. J. Coal Geol. 70, 240–254. Sakurovs, R., Day, S., Weir, S., 2010. Relationships between the critical properties of gases and their high pressure sorption behaviour on coals. Energy Fuel 24, 1781–1787. Sakurovs, R., He, L., Melnichenko, Y.B., Radlinski, A.P., Blach, T., Lemmel, H., Mildner, D.F.R., 2012. Pore size distribution and accessible pore size distribution in bituminous coals. Int. J. Coal Geol. 100, 51–64. Sakurovs, R., Koval, L., Grigore, M., Sakolova, A., Ruppert, L.F., Melnichenko, Y.B., 2018. Nanometre-sized pores in coal: variations between coal basins and coal origin. Int. J. Coal Geol. https://doi.org/10.1016/j.coal.2017.11.010. Sawyer, W.K., Zuber, M.D., Kuuskra, V.A., Horner, D.M., 1987. Proceedings of the Coalbed Methane Symposium, Tuscaloosa, 16–19 November 1987. pp. 295–307. Seidle, J., 2011. Fundamentals of Coalbed Methane Reservoir Engineering. PennWell Books. Sokolova, A., Christoforidis, J., Eltobaji, A., Barnes, J., Darmann, F., Whitten, A.E., de Campo, L., 2016. BILBY: time-of-flight small angle scattering instrument. Neutron News 27, 9–13. Staib, G., 2013. Dispersive Diffusion of Gas in Coal: An Experimental Investigation into the Fundamentals of Gas Sorption and Diffusion in Coal. Griffith University. Staib, G., Sakurovs, R., Gray, E.M.A., 2015a. Dispersive diffusion of gases in coals. Part I: model development. Fuel 143, 612–619. Staib, G., Sakurovs, R., Gray, E.M.A., 2015b. Dispersive diffusion of gases in coals. Part II: an assessment of previously proposed physical mechanisms of diffusion in coal. Fuel 143, 620–629. Wang, K., Zang, J., Feng, Y., Wu, Y., 2014. Effects of moisture on diffusion kinetics in Chinese coals during methane desorption. J. Nat. Gas Sci. Eng. 21, 1005–1014. White, C.M., Smith, D.H., Jones, K.L., Goodman, A.L., Jikich, S.A., LaCount, R.B., DuBose, S.B., Ozdemir, E., Morsi, B.I., Schroeder, K.T., 2005. Sequestration of carbon dioxide in coal with enhanced coalbed methane recovery – a review. Energy Fuel 19, 659–724.
In this study we have restricted our attention to coals from Australia, Canada, the US and Europe. Whether other coals behave as Australian/Canadian coals or US/European coals or differently again remains to be established. 4. Conclusions The sorption extent and rate of coals for CO2 and CH4 was examined for a wide range of coals, sourced from different regions and basins. The sorption results were compared with the porosity data obtained from the small angle neutron scattering method (SANS). It was concluded that: - The rate of sorption of methane and carbon dioxide by coals increased exponentially with the total number of nanopores in the range of 8-50 nm. For the coals from Australia, except from the Illawarra region, rates of sorption increased exponentially with inertinite content, because they contained many pores in the 8-50 nm size range. - The ratio of sorption rates (k) of CO2 and CH4 was found to vary significantly between the coals and was smaller for coals with faster penetration rates. - The rates of gas sorption in the Australian coals with less than 70% vitrinite content generally decreased with increasing rank, while no discernible effect was obtained on the rate of sorption for the vitrinite-rich Australian coals. - The pore size distribution in 8–50 nm size range was not related to the capacity for maximum sorption. Hence the numbers of 8–50 nm pores in coals was independent of the number of < 5 nm pores. Overall, kinetics of sorption and the capacity for maximum sorption were not strongly correlated. - The capacity for maximum sorption of coals was found to be largely independent of inertinite content. However the capacity for maximum sorption of Australian coals were found greater than those of elsewhere regardless of inertinite content. This may indicate that the numbers of < 5 nm pores in Australian coals were systematically different from other coals sourced elsewhere. - The capacity for maximum sorption of coals generally decreased with increasing rank to a rank of 1% Rv,max and then levelled off. The variation of β with maceral composition was greater for coals from Australia than other sources, mainly due to the greater pore accessibility of inertinite in Australian coals. The dispersion of sorption rates β, was found almost the same for CO2 and CH4, indicating that the gas penetrated the same part of the coals. The relationships found in this paper can aid in a better fundamental understanding of adsorptiondesorption processes in coals, which has important implementations in predicting coal structure, modelling ECBM, and explaining the variation between coking properties of different coals. Acknowledgement This project was partially funded by the Australian Coal Association
86