Petrographic Composition of the Coal Within the Benue Trough, Nigeria, With a Consideration of the Paleodepositional Setting

The petrographic composition of coals hosted in the Benue Trough, Nigeria are presented and discussed in terms of paleodepositional setting that influenced the coal-bearing formations. The Benue Trough is a failed arm of the triple ‘RRr’ junction of an inland sedimentary basin that extends in a NE -SW direction from the Gulf of Guinea in the south, to the Chad Basin in the north. A total of twenty-nine (29) coal samples were obtained from 19 coal localities in the Upper (UBT), Middle (MBT), and Lower Benue Trough (LBT). The proximate data indicates the coal samples have a high volatile matter content, low ash yield, and high calorific value (24.82 MJ/Kg, on average). The sulphur values are generally low (average of 0.94 %). The coal samples are generally high in vitrinite, with an average of 59.3% by volume (mineral-matter free). Variation was noted in the inertinite content for the three sub-region samples. Liptinite macerals were not commonly observed in the studied samples and are absent in the MBT samples. The MBT coal samples reported a higher gelification index than the UBT and the LBT samples. Comparison of the array of coal facies models show the MBT samples are different from the UBT and LBT samples, concurring with the characterisation data. In view of the modified equations and the plots used, interpreting depositional environment accurately from just a single model is quite challenging.


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This study unpacks the petrographic composition, and makes use of complementary chemical data, to interpret the paleodepositional setting prevailing during peatification and coalification in the Benue Trough, Nigeria, making use of various coal facies models. The petrographic composition of coal samples reveals the complexity of coal in terms of its discrete microscopic organic (maceral) and inorganic (mineral) components, and their relationships. Chemical data (proximate and ultimate), and calorific value (CV) augment the petrographic data for an enhanced understanding of the coal facies models used.
The LBT is divided into the Anambra Basin and Abakaliki Syncline, which were formed in the late Cretaceous Period.
They are associated with the separation of the African and South American continents and the subsequent opening of the South Atlantic Ocean (Murat, 1972;Obaje et al., 1998;Ogala et al., 2012). During the filling of the Benue-Abakaliki sector of the Trough in Albian-Santonian times, the proto-Anambra Basin was a platform (Murat, 1972;Benkhelil, 1989;Obaje et al., 1998;Ogala et al., 2012). The Anambra Basin contains 6 km of sedimentary sequences of Cretaceous age and is the structural link between the Cretaceous Benue Trough and the Tertiary Niger Delta (Mohammed, 2005). Slow subsidence followed by a regression in Maastrichtian times, during which deltaic forests and floodplain developed, resulted in the coal measures of the Mamu, Ajali and Nsukka Formations; Awgu Formation and the Agbani sandstone; Odukpani Formation and Agala sandstone (Obaje et al., 1998;Ogala et al., 2012).

Sampling
Twenty-nine grab coal samples (Table 2), sampled at depths ranging from 1 m to 3 m, were obtained from 19 coal localities (Figure 2) (7 samples from UBT, 9 from the MBT, and 13 from the LBT). Each sample had a mass between 2-5 kg. Samples originated from surface excavations where various seams outcropped; the excavations include active mines, borehole cuttings, river cuttings (weathered surfaces were removed prior to sampling), and an old mine shaft.
Access to sample localities was a challenge, in view of persistent attacks by Boko Haram terrorists and Fulani herdsmen.

Sample preparation
The coal samples were milled to -1 mm at the School of Chemical and Metallurgy Engineering Coal Laboratory, University of the Witwatersrand (Wits). Each sample was split for petrography (approximately 50g) and the remainder milled to -212 μm for chemical analyses (proximate, ultimate, CV) and elemental and mineral composition (total sulphur, XRD, XRF, and ICP-MS). The data pertaining to the mineralogy and geochemistry of the coal samples will be reported in future publications. For coal petrography, the particles were mixed with epoxy resin and hardener, and moulded as 30 mm block mounts. Each block surface was ground and polished for petrographic analysis in line with ISO 7404-2:2015, using a Struers Tegra-Force polisher with a final polish of 0.04μm.

Complementary analyses
Proximate analysis was performed following ASTM D3172-13 (2013) using a Perkin Elmer Thermogravimetric Analyzer at Wits. Ultimate analysis was undertaken at Bureau Veritas, Centurion, South Africa, following SANS 17247 (2006) andISO 17247 (2005). Gross calorific value was determined using a dry-cal bomb calorimeter at Wits (SANS 1928(SANS , 2009 Yttrium-Aluminium Gallium YAG (% Ro = 0.90 and zero reflectance). The calibration was checked between each sample, and a minimum of 100 readings were taken on collotelinite, avoiding poorly polished or pitted vitrinite.

Complementary analyses
The proximate and ultimate data are presented in Table 3 and Figure 3. The relatively low ash yields observed in the LBT samples agreed with data presented by Ogala et al. (2012). The CV values for the UBT and LBT samples are higher than for the MBT samples, representing higher grade coals. The moisture content is high in some of the coal samples, indicative of low rank coal, possibly lignite to sub-bituminous coal. Samples 01 and 17 have very high ash yields, 69.2% and 79.0%, respectively. These samples are omitted from the average calculations in Table 3, as they are considered not to be coal (ISO11760, 2005). The sulphur contents are generally less than 1%, except for a few samples (16, 17, 04, 08 18 and 20) with values above the 1% (Table 3). Despite being grab samples, proximate and ultimate data indicates that the samples represent coals generally of high quality.
The trends observed in the proximate data ( Figure 3) could suggest differences in depositional environments, with the LBT samples show more consistent good quality coals.

Vitrinite reflectance
Variation was observed in the coal rank for the three sub-region of the Benue Trough ( Figure 4). The reflectance values, on average, place the UBT samples in the medium rank D bituminous coal category (ECE-UN, 1998). The LBT samples fall into the low rank A sub-bituminous category, and the MBT samples as medium rank C bituminous coals (Table 4), with the exception of sample 09 which is classified as lignite Samples 01 -07 are from the same locality but different coal seam, sampled along a river channel (River Dep) represented as horizons A-G (Table 2); no weathering effect was determined. Three locations in the UBT contain coals in the medium rank C category, but all samples in the LBT region are low rank. Thus, implying differing coalification processes between the three subbasins. Owing to the variations in coal rank reported, the study included the maceral terminology recommended by the ICCP for huminite (ICCP 2001;Sýkorová et al., 2005;ICCP 1998ICCP , 2001Pickel et al., 2017).

Maceral and mineral composition 8
The maceral composition varies through the sub-regions of the Benue Trough as shown in Figure 5 and Tables 5-7.
The samples show a dominance in vitrinite, with varying proportions of the inertinite and liptinite. Liptinite was poorly distributed in the UBT and LBT samples, and generally missing in the MBT except for sample 09 that shows a higher liptinite content. Samples from both the UBT and LBT contain funginite, which is also generally absent in the MBT samples.
Based on the vitrinite reflectance values and moisture content, five of the samples (15,16,09,28,29) were classified as lignite (Table 8). These are described using the huminite classification system (Sýkorová et al., 2005;ISO 7404-5 2009) for adherence to petrographic norms (Table 8), and are also described using the classification for bituminous coal for ease of comparison with the other samples of the study. The LBT samples were dominated by densinite, equivalent to collodetrinite in higher rank coals. It is worth noting that collodetrinite is also the dominant maceral in the higher rank coal samples (Tables 5, 6, 7).
The observable mineral matter shows a similar trend to the ash yield (proximate analysis), with the MBT samples containing the highest mineral matter compared to the UBT and LBT samples. The dominant minerals observed are clays and quartz, with limited pyrite in the LBT samples possible detrital zircon was observed in the MBT samples studied, but further studies are required. The total sulphur data is in agreement with the findings by Ogala et al. (2012).

Microlithotype composition
The microlithotype composition is plotted in Figure 7 and Table 9. Vitrite is dominant in the majority of the samples.
The MBT samples are primarily vitrite-rich, whereas the UBT and the LBT samples show varied composition.
Duroclarite is abundant in UBT and LBT samples, and is apparently absent in the MBT samples. Clarodurite and vitrinertoliptite are poorly distributed in the UBT and LBT samples. Carbominerite in the samples is dominated by carbargillite/clays and carbosilicate/quartz (Table 9).              Most models used in coal facies analysis are TPI, GI, GWI, and VI (Diessel, 1986) which are based on quantitative amounts of coal constituents such as macerals to determine paleoenvironments. TPI and GI have been more widely used to infer peat depositional environment than the GWI and VI. In order to interpret the depositional environments for the coal samples, GI and TPI model were carefully considered for the facies studies as proposed by other scholars, namely: Diessel (1986);Calder et al. (1991); Müller et al. (1992); Silva and Kalkreuth (2005); Sahay (2011); Stock et al. (2016). The TPI and GI values were calculated using the formulae expressed by Diessel (1986) in Equations 1 and 2, and were further modified by other scholars: Silva and Kalkreuth (2005); Sahay (2011) modified the indices to include the liptinite as expressed in Equations 3 and 4.  UBT  MBT  LBT  Locality sample  L1 L2  L3  L4  L1  L2  L3  L1  L2  L3  L4  L5  L6  L7  L8  L9  L10  L11  L12  Group  Sample Number  11  12  13  14  15  16  17  01  02  03  04  05  06  07  08  09  10  18  19  20  21  22  23  24  25  26  27  28 Calder et al. (1991) by considering the ash yield divided by 2 as seen in Equation 8. The coal facies model based on Diessel (1986) and Stock et al. (2016) formulae were plotted in Figures   9, 10. Variation is noted in the TPI and GI values based on the Diessel (1986) and Sahay (2011) formulae, due to limited liptinite macerals in the MBT region (Figures 9, 10; Table 10). TPI values are low for the coal samples suggesting a predominance of herbaceous plant in the mire or large scale destruction of wood because of extensive huminification and mineralization (Diessel, 1992). However, limited samples are noted for high TPI values due to non-destruction of the wood (well preserved plant material). The MBT samples are noted for high GI values, suggesting an increased in moisture in the mire with higher rate of subsidence and a decreased in oxidation (Table 10). However, few of the UBT and LBT samples show similarity in high GI values. Based on the tree density coal facies diagram and using Sahay (2011) formula, the plots show a positive tree density (Figure 10), while Diessel (1986) formula show variation in distribution ( Figure 9; Table 10). Calder et al. (1991) and Stock et al. (2016) values for VI and GWI shows no disparity (Figures 9, 10; Table 10).

Sub-Basin
The UBT samples reveal a transitional paleoenvironment ranging from transgressive and regressive, back-barrier marsh to wet-forest-swamp and lower delta plain environment due to their vitrinite-rich content with variability in inertinite content (Figures 9, 10). The wide range of depositional environment is a reflection of the different coal seams. The samples plot fall within a wet forest swamp and upper delta plain (Calder et al., 1991;Stock et al., 2016)  influenced in an in-situ crystallization in the ancient peat than the UBT and LBT samples (Ward, 2002;Finkelman et al., 2019;Dai et al., 2020). The MBT samples paleo mire ranges from ombrotrophic, mesotrophic and rheotrophic hydrological conditions in a bog setting (Figures 11, 12). The peat swamp was noted for detrital sediments (rich in kaolin) transported into the peat swamp from the surrounding basement rocks. Spears (1987) suggested that the precipitation of kaolinite in the pores and cells of coal macerals can be attributed to changes of pH conditions in the peat swamp.
The LBT samples demonstrate a pattern of deposition ranging from a dry-forest-swamp to regressive-back-barrier, related to the higher inertinite content ( Figure 9) with a few samples plotting in the transgressive-limnic-back-barrier setting. The LBT samples show an ombrotrophic to mesotrophic hydrological conditions in limnic setting (Calder et al., 1991;Stock et al., 2016). Sample 26 has the highest VI (3.2) value, implying a high level of preserved material structured (swamp forest) (Figures 9, 10, 11, 12; Table 10). Teichmüller (1989) observed that wet conditions of peat formation are normally distinguished by high GI and high TPI indices for wet condition, while low GI and low TPI indices by dry conditions. TPI values for the studied coal samples are generally low suggesting either a predominance of herbaceous plant in the mire or large scale destruction of wood due extensive huminification and mineralization (Diessel, 1992). However, some samples are noted for high TPI values due to non-destruction of the wood (well preserved plant material). Despite the distinct geographical regions and different coal seams most samples show similar depositional settings based on the TPI and GI values ( Figure 12; Table   10).

1. Coal facies concept.
Coal is heterogeneous in composition, and likewise the coal samples from the Benue Trough are characterized by different qualities as a result of the depositional environments. The UBT samples showed varied depositional setting (back barrier to wet forest swamp to terrestrial environment) which influences its maceral distribution. The MBT samples (marsh to lower delta plain) developed in a wet condition as indicted by the high vitrinite and mineral matter content. LBT samples ranged from limnicback barrier -wet /dry forest swampterrestrial environment in a wet to dry environment. In comparison, the coal samples did not show much differences in their depositional environment as the     samples are from different distinct geographical regions (example, samples 15 and 16 (UBT); 18 and 26 (LBT) Figure   2). They are noted for high TPI, and VI with low GI, for samples 15 and 16 (UBT); 18 and 26 (LBT) are indication of high inertinite content in a dry condition. The high TPI values indicates a balanced ratio of plant growth and peat accumulation with a rise in the water level due to basin subsidence.

Conclusion.
The study presents the petrographic composition and infers the depositional conditions that influenced the coal-bearing formations hosted within the Benue Trough, Nigeria. The entire geology within the Benue Trough occurs in a failed arm of the triple RRr junction, an inland sedimentary basin that influenced the coal composition. In view of the modified equations and the plots used, interpreting depositional environment accurately from just a single model is quite challenging. Therefore, combination of published models based on the petrographic indices is highly recommended.

Acknowledgements.
The support of the Department of Science and Innovation through its funding agency, the National Research Foundation, and the Centre of Excellence for Integrated Mineral and Energy Resource Analysis (DSI-NRF CIMERA) towards this research is hereby acknowledged. Opinions expressed and conclusions arrived at, are those of the author(s) and are not necessarily to be attributed to the CoE, DSI or NRF. The authors would like to thank DSI-NRF CIMERA for financial support during the PhD studies. Thank you to the University of Johannesburg Geology Department for access to the petrographic microscope and other analytical facilities, and the University of the Witwatersrand for allowing me access to the Coal and Gemin Laboratories for general coal characterisation analyses. I remain forever grateful to University of Jos-Nigeria for releasing me for this study on coal petrology. This paper forms part of the PhD study underway at the University of Johannesburg, South Africa.

Authors Contributions:
Mangs Ayuba Danmangu carried out this project in partial fulfillment of his PhD programme at the University of Johannesburg, South Africa, under the supervision of Prof NJ Wagner, co-supervised by Prof UA Lar. Marvin Ofentse Moroeng have provided major contributions to the design of the work and gave extensive suggestions on the data analysis and interpretation, as well as on the English language editing of the paper.

Conflicts of Interest:
The authors declare no conflict of interest.