Source Rock Properties, Depositional Environment and Kerogen Degradation Kinetics of Lower Permian Shales from the Ib River Sub-Basin, Mahanadi Basin, Eastern India

Lower Permian organic-rich shales and coals from the Ib River sub-Basin, part of the Mahanadi Basin in Eastern India, were studied using Rock-Eval pyrolysis, kerogen kinetics, biomarker, and organic carbon isotopic analyses to investigate the source rock characteristics, depositional environment, and thermal degradation kinetics of the sedimentary organic matter (OM). The samples are organically rich (>5 wt% total organic carbon [TOC]) and possess higher hydrocarbon generation potential (>54 mgHC/g rock). The primary contributors to the OM supply were identified as terrestrial plants, supplemented by emergent aquatic plants, resulting in a Type II–III kerogen. The broader activation energy indicates OM input from heterogeneous sources, whereas the earlier and faster kerogen transformation ratio (TR), along with a high hydrocarbon generation rate (HGR), suggests excellent kerogen quality. Despite the samples’ favorable source rock characteristics, their relatively low Tmax values (<435°C) indicate immaturity, limiting their potential for natural hydrocarbon production. Marine incursions have been identified in the Barakar Formation of the Ib River sub-Basin, accompanied by climatic fluctuations (inferred from Paq, average chain length [ACL], and δ13C) that correspond to alternating dry and wet periods during the deposition of various lithotypes. The samples exhibit an abundance of even lower n-alkanes, indicating that the OM inputs are derived from aquatic vegetation rather than microbial activity. The gammacerane index (GI) averages ∼0.29 for the Barakar Formation and ∼0.24 for the Karharbari Formation, indicating greater water stratification and higher salinity in the Barakar Formation compared to the Karharbari Formation. Likewise, other key parameters such as tricyclic terpanes (TTs) and polyaromatic hydrocarbons (fluorenes [FLs], dibenzothiophenes [DBTs], and DBFs) differentiate certain Barakar samples as being deposited in a saline lacustrine environment, whereas the other Barakar samples and all Karharbari samples indicate a swampy, oxic environment. The pristane (Pr)/phytane (Ph) ratio supports this conclusion, indicating a reducing to oxidizing depositional setting for the Barakar Formation, while suggesting an oxic environment for the Karharbari Formation. Integrating all parameters, we conclude that the Barakar Formation was influenced by marine activities during Permian Period. Drawing on our research and prior studies, we propose two scenarios for marine interaction in the Ib River sub-Basin during the Permian Period: Either the region was covered by an extended marine embayment or marine influence extended to the NW-SE slope of the basin, notably affecting the Rewa region in the northwest

Threshold-based inventory for flood susceptibility assessment of the world’s largest river island using multi-temporal SAR data and ensemble machine learning algorithms

Majuli is the world’s largest inhabited river island and is highly prone to flood hazards, resulting in significant damage to houses and agriculturally based livelihoods. Considering its cultural heritage and unique landscape, it is necessary to prepare a flood susceptibility map (FSM) to reduce the annual damage. Therefore, the primary aim of this research is to prepare and improve the precision of FSM using microwave satellite images and six robust ensemble machine learning models. In the three main stages of FSM, each stage contributes to achieving optimal accuracy. In the first stage, a threshold-based flood inventory map has been prepared from six years of multi-temporal SAR images. In the second stage, preliminarily seventeen flood conditioning variables such as elevation, slope, profile curvature, terrain ruggedness index, topographic wetness index, distance from streams, rainfall, land cover land use, normalized difference vegetation index, distance from road, geomorphology and lithology have been prepared, but after utilizing the Boruta algorithm and multicollinearity analysis, twelve key flood-influencing variables have been selected for flood modelling. In the final stage, six robust ensemble machine learning models namely random forest, rotation forest, stochastic gradient boosting, boosted regression tree, deep boost and logit boost have been applied and subsequently compared to determine the best model. The performance of the models is evaluated with various statistical measurements, including the area under curve (AUC), sensitivity, specificity, kappa index and overall accuracy values. The results revealed that the random forest model outperformed the other models in terms of model fitness (AUC = 1) and predictive capability (0.99). Additionally, the very highly vulnerable pixels of the FSM are validated with the twenty flood locations from the field surveys, showing that the accuracy of the FSM is 100%. The FSM indicates that around 50% of the study region has a very high and high susceptibility to future flood occurrences

Major ion and stable isotope geochemistry of coalmine water of Talcher coalfield, Mahanadi Basin, India: implication to solute acquisition process and elemental flux

The major ion and stable isotope geochemistry of coalmine water of Talcher coalfield was investigated to identify prominent hydrogeochemical processes controlling mine water composition and estimate annual elemental flux. Mine water samples from opencast and underground coalmines were analysed for EC, pH, TDS, TH, major ions and stable isotopes i.e. δ18O and δ2H. Coalmine water exhibited a wide range of pH values, from highly acidic to alkaline, and were dominated by SO42− and Ca2+ in their total anionic (TZ−) and cationic (TZ+) composition respectively. Ca-Mg-SO4 was the most dominant hydrochemical facies. High contribution of Ca2+and Mg2+ and SO42− towards the TZ+ and TZ− and low HCO3−/(HCO3−+SO42−) ratio suggested a major role of sulphide oxidation in determining coalmine water chemistry. A slight deviation in the regression line towards right side of the Global Meteoric Water Line and Local Meteoric Water Line in the bivariate plot of δ18O vs δ2H implied that water experienced evaporation to some extent and originated mainly from atmospheric precipitation. Most of the mine water were undersaturated with respect to carbonate and sulphide phases. Talcher coal mines annually delivered 47.06 × 106 m3 mine water and 28.481 × 103 tonnes of solute loads into nearby drainage

Elemental Composition and Petrographic Analysis of Coal in the Sohagpur Coalfield With Implications for Environmental Management

This paper aims to provide an overview of the geochemistry and mineralogical characterisation of coal within the Sohagpur coalfield, located in the Burhar–Amlai Sub Basin of Madhya Pradesh, India. The study involves the determination of proximate and ultimate analysis components, major elements, and trace elements by using various techniques, including x-ray diffraction (XRD), x-ray fluorescence (XRF), oranic petrography, Fourier transform infrared spectroscopy (FTIR) and Scanning Electron Microscopy–Energy Dispersive Spectroscopy (SEM-EDS). Petrological studies identify the types of macerals and minerals associated in coals, assess their concentration, and examine their association with elements found in the coal samples. Our research also delves into the environmental implications of these elements, particularly those considered environmentally sensitive, such as As, Cd, Co, Cr, Mn, Ni, Pb, Th and U. These findings are crucial for understanding the potential environmental impact associated with the utilisation of coal. This study identified several major sources of these elements within the coal, including silicate minerals (Quartz and Feldspar), oxides (Haematite, Rutile and Anatase), sulphides (Pyrite and Marcasite), sulphates (Gypsum) and carbonates (Calcite). Recognising these sensitive components is vital as they require mitigation or elimination before coal utilisation to minimise environmental risks. Our study delivers a valuable understanding of the geochemical composition and mineralogical characteristics of coal in the Sohagpur coalfield, highlighting the importance of environmental considerations in the utilisation of these resources

Paleodepositional environment and source rock potential of Paleogene lignite and shale horizons in the Saurashtra Basin, Western India

Coal is formed from ancient plants through biochemical and physicochemical stages. Lignite gives a low amount of energy compared to higher rank coal. The Eocene Khadsaliya Formation lignite (Surkha mine) and shale (Khadsaliya mine) sediments were collected to investigate their evolution, maturity, and source rock potential. The main objectives of this study were to update and verify previous claim of possible hydrocarbon showings and to gain new insights about the petroleum potential and paleodepositional conditions using different geochemical analysis approach. The primary methodology employed in this study is the pyrolysis technique and complemented by petrographic analysis. Petrographic indices indicate that Khadsaliya shale and Surkha lignite were deposited in limnic and limno-telmatic conditions, respectively, with slow subsidence rates under mesotrophic hydrological condition. Significant concentration of corpogelinite indicates highly varying water table and low oxygen levels during peat accumulation. At the same time, the presence of funginite, framboidal pyrite, and relatively high sulfur in some studied samples shows marine water influence in the basin. The reflectance values (0.37%–0.57%) reveal that organic matter (OM) in Surkha lignites is immature, while immature to marginally mature in Khadsaliya shale. Furthermore, the pyrolysis data like Tmax (385°C–430 °C) and production index (PI 0.02–0.13) also indicate immature to marginally mature OM. Oxygen index (OI) versus hydrogen index (HI), Tmax versus HI, and Total organic carbon (TOC) versus S2 plots of lignite and shale of Khadsaliya Formation indicate that the OM is mainly type III kerogen and can act as fair to good source rock. The distribution of n-alkene/n-alkane doublets, o-Xylene, and 2,3-dimethylthiophene in the Py–GC pyrogram exhibits that most studied shale and lignite samples have type III kerogen and the capability to produce mainly gas

Photothermal conversion and geochemical characterization of sulfur-rich lignite for non-conventional energy applications

Lignite has emerged as a critical material in contemporary energy portfolios, particularly in electricity generation. However, this work explores lignite’s potential beyond conventional uses, exploring on its energy conversion applications. In a pioneering move, lignite samples have been directly utilized as materials for photothermal conversion applications, along with a description of their geochemical features, such as sulfur compositions, forms, and microscopic characteristics. Among the twenty lignite samples that were geologically studied, two sulfur-rich samples (CS-1 and CS-2) were chosen to explore their photothermal conversion performance. The powder-XRD diffraction patterns of CS-1 and CS-2 reveal the presence of the hexagonal phase of carbon C1 with kaolinite (Al2Si2O5(OH)4). Their XPS spectra indicate that both organic and metal-bonded sulfide moieties are present in the lignite samples. CS-1 and CS-2 were implemented under 1 Sun irradiation, and it was found that CS-2 exhibits superior light-absorbing properties, resulting in enhanced water evaporation rates. In addition, the photothermal imaging also shows a temperature increase to 58.2 °C within 10 min for lignite-coated membranes, compared to 31 °C for the blank under similar conditions. These findings can be leveraged to explore lignite’s untapped potential in various technological domains, propelling the global transition towards cleaner energy solutions

Spatio-temporal variation, integrated quantification of source attribution, and health risk assessment of metal trace element contamination in coal mining soils of the Eastern Raniganj basin, India

Metal trace element (TE) contamination from coal mining has severely impacted soil quality and human health in the Eastern Raniganj basin, India. To determine the most TE-polluted locations, potential TE sources, and associated health risks, this study integrated Positive Matrix Factorization (PMF) and Human Health Risk (HHR) models. Eighty-three surface soil samples were collected and analyzed for 12 TEs (Fe, Al, Cr, Co, Ni, As, Mn, Cd, Pb, V, Cu, and Zn) during the post-monsoon season. All measured TEs, except As, exceeded their geochemical background values, with mean Pollution Load Index of 2.13 and Ecological Risk Index of 529.9, indicating severe contamination. Pearson correlation analysis suggested a substantial positive correlation (r > +0.6) amongst Cr, V, Co, Ni, Cu, Pb, Zn, and PLI, indicating homologous characteristics. The PMF model distinguished five pollution sources, with coal mining being the primary contributor. The integrated PMF-HHR model highlighted that factor F5 (coal mining operations, contributing 32.3 % of total variance) posed risks to both children and adults, with a total hazard index of 4.92E+ 01 for adults and 3.50E+ 02 for children. Ingestion and dermal contact were key exposure pathways for adults, while all three pathways affected children. The total cancer risk for children (2.37E-01) and adults (3.40E-02) indicated carcinogenic risks (CR) and Cr being common in all factors increasing the CR in children via different routes. This study provides a robust framework for understanding the spatio-temporal TE variation and HHR in coal mining regions, serving a reference for future mitigation strategies

Methodology in early detection of conveyor belt fire in coal transportation

Thermal power units are a major source of power generation in India. Belt conveyor is the leading transportation system in a thermal power plant. Belt conveyor fire in a thermal power plant breaks the chain of the transportation system, stops the feeding to the boiler, and often leads to closure of the plant, and thereby impacts the production for several months incurring huge losses. The main aim of this study is to design a model for early detection of belt conveyor fire and its automatic fire suppression system. The proposed model incorporates safety devices and sensors which shall be activated whenever it is necessary. Based on coal characteristics, threshold limit values (TLV) of sensors are defined. Proximate analysis, critical oxidation temperature, fire ladder, and differential scanning calorimetry (DSC) studies were conducted to characterize the five coal samples used in this study collected from Talwandi Sabo Power Ltd. (TSPL), Mansa, Punjab, India. For the coal samples used in this study (with an average moisture content of 7.59 wt %), the average critical oxidation temperature was observed to be 81.3 ⁰C. Further, the fire ladder study indicates that gas sensors like CO and H2 should be installed in the belt conveyor route. Based on laboratory and field investigations an automated model for early detection of fire was proposed which incorporates safety devices, temperature, and gas sensors, and fire suppression mechanisms

Seismic interpretation for comprehending rock characteristics in underground coal mines – some investigations

Proper scaling of roof falls in underground coal mines demands both extensive experience and skilled techniques. Roof falls are responsible for approximately 40% of mining fatalities. There are several causes for the triggering of roof falls, such as laminated strata, slip planes in the roof, moist roof conditions and clay bands, etc. However, the primary contributors are thin-layered strata and the plane of weaknesses present in the development galleries. The roof fall becomes even more hazardous in wide gallery openings and where there is a time lag in supporting the exposed strata. For the past 30 years, the CMRI-ISM RMR classification system has been extensively employed in underground coal mines to evaluate roof conditions and devise suitable support systems for both development and depillaring headings. Even though it is a very well-proven method of support design, it can be challenging at times to assess the risk of roof fall due to the lack of information on roof rocks. Detecting rock mass conditions at shallow depths can be made easier with the seismic refraction technique. The main objective is to acquire a better understanding of the roof condition affected due to solid blasting during the development of galleries, stress release through delamination, and the presence of weak zones in the coal mine roof. In this study, the P-wave velocity was determined along the gallery roof for different layer thickness, uniaxial compressive strength, structural features, density, and groundwater condition, and a relationship was developed. The roof condition was further correlated with respect to roof fall height, and a relationship was framed between P-wave velocity and roof fall height, and also between P-wave velocity and depth of the damage in the mine roof. If the roof fall height and depth of damage are known, the support design can be done accordingly to restrict the occurrence of roof falls. Support design nomogram with roof bolts was also suggested based on P-wave velocity. The outcome of this seismic study also aids in deciding site-specific support design