Indian Coal Mines Research Articles

Effect of Variation of Dragline Bench Height and Cut Width on Performance of Tandem Dragline Operations in Large Opencast Coal Mines in India

Effect of Variation of Dragline Bench Height and Cut Width on Performance of Tandem Dragline Operations in Large Opencast Coal Mines in India

Surface deformation monitoring of Raniganj coalfield, India, using advanced InSAR and DGPS

The Raniganj coalfield, which is the oldest coal mine in India, is susceptible to ground subsidence. For the purpose of detecting surface deformation, this work makes use of field surveys, interferometric synthetic aperture radar (InSAR), and Differential GPS (DGPS). The study utilised Sentinel-1 InSAR data spanning from 2017 to 2023. PS-InSAR was used for both ascending and descending datasets, while SBAS-InSAR was used for descending datasets alone. Records show a maximum subsidence rate of −21.18 mm/year. Three surface deformation maps were generated from time-series assessments of individual locations, revealing regions undergoing significant changes. Known mining collapse locations and continuing deformation zones were designated with four differential GPS stations. By analysing the DGPS data with the GAMIT/GLOBK software, we were able to measure surfaces that were undergoing rapid deformation. Using Google Earth Engine (GEE), we generated thermal maps to delve deeper into the coal fire activity. We found coal bed methane (CBM) mining causing substantial subsidence in Kataberia and the surrounding areas. Shyamsundarpur and New Kenda are impacted by mining voids and coal fire-induced subsidence, respectively. The results of this study give the Raniganj region’s decision-making procedures more credibility in terms of minimising and controlling geological dangers.

A Critical Assessment of Boundary Limits of Health Risks Associated with WBV Exposure Based on Field Studies on LHD Vehicles in Indian Underground Coal Mines

Purpose: The mining sector plays a pivotal role in meeting global resource demands, necessitating the extensive use of heavy earth-moving machinery (HEMM). Among these, load-haul-dump (LHD) mining vehicles are vital but expose operators to whole-body vibration (WBV) and shocks during their duties. Research indicates potential health risks associated with occupational WBV exposure, including musculoskeletal disorders. Evaluating these risks typically employs ISO 2631-1:1997, which, however, has limitations in addressing long-term exposure and shock effects. Methods: This study quantifies the health risks of LHD operators in Indian underground coal mines using ISO 2631-5:2018 and compares it to ISO 2631-1:1997. The methods for risk quantification from WBV vary between the two standards, leading to a comprehensive comparison. In addition, a cross-sectional study was undertaken to assess self-reported musculoskeletal pain among LHD operators. Results: The results were compared in accordance with frequency-weighted root mean square (RMS) values, vibration dose values (VDV), daily compressive dose (Sd A), and the risk of injury (RA) factor. The assessment using A(8), VDV, Sd A, and RA produced diverse evaluations, influencing varying perspectives on occupational health despite significant risks. ISO 2631-5:2018 consistently suggested a lower health risk for LHD operators as opposed to ISO 2631-1:1997. Seat effective amplitude transmissibility (SEAT) values showed amplification of vibration in the range of 4-8 Hz. Self-reported musculoskeletal pain indicated the prevalence of discomfort among operators. Conclusion: The study emphasizes a cautious approach when interpreting results and shaping guidelines to ensure sustainable development through the well-being of mining industry workers.

Determination of moisture content in coal using pulsed fast thermal neutron activation technique

The quality of coal is greatly influenced by the residual moisture content, which in turn affects the Gross Calorific Value (GCV) by limiting the maximum energy that can be extracted from a given mass of coal. Various methods have been developed to measure this residual moisture, including gravimetric techniques, near-infrared spectroscopy, microwave, and infrared moisture meters. Amongst these, neutron-based techniques offer distinct advantages for bulk and rapid characterization, making them suitable for online monitoring. This article presents the use of a Pulsed Fast Thermal Neutron Activation technique to determine moisture content in various coal samples acquired from Indian coal mines. A 14.1 MeV D-T neutron source coupled with a Bismuth Germanate (BGO) detector and associated electronics have been used. The hydrogen content in the sample has been used as an indicator for the moisture and the technique has been calibrated with samples of known moisture content. The results obtained for the coal samples demonstrate a remarkable agreement with the findings of proximate analysis. A minimum quantity of 2% moisture by weight has been detected with a relative error of 0.4%.

Review of soil environment quality in India near coal mining regions: current and future predictions.

Production and utilization of coal are one of the primary routes of accumulation of Toxic Elements (TEs) in the soil. The exploration of trends in the accumulation of TEs is essential to establishing a soil pollution strategy, implementing cost-effective remediation, and early warnings of ecological risks. This study provides a comprehensive review of soil concentrations and future accumulation trends of various TEs (Cr, Ni, Pb, Co, Cu, Cd, Zn, Fe, Mn, and As) in Indian coal mines. The findings revealed that average concentrations of Cr, Mn, Ni, Cu, Zn, Pb, and Co surpass India's natural background soil levels by factors of 2, 4.05, 5.32, 1.77, 9.6, and 6.15, respectively. Geo-accumulation index values revealed that 27.3%, 14.3%, and 7.7% of coal mines are heavily polluted by Ni, Co, and Cu, respectively. Also, the Potential Ecological Risk Index indicates that Cd and Ni are primary contaminants in coal mines. Besides, the health risk assessment reveals oral ingestion as the main exposure route for soil TMs. Children exhibit a higher hazard index than adults, with Pb and Cr being major contributors to their non-carcinogenic risk. In addition, carcinogenic risks exist for females and children, with Cr and Cu as primary contributors. Multivariate statistical analysis revealed that TEs (except Cd) accumulated in the soil from anthropogenic sources. The assessment of future accumulation trends in soil TE concentrations reveals dynamic increases that significantly impact both the ecology and humans at elevated levels. This study signifies a substantial improvement in soil quality and risk management in mining regions.

A multi-criteria decision framework to evaluate sustainable alternatives for repurposing of abandoned or closed surface coal mines

Surface coal mines, when abandoned or closed, pose significant environmental and socioeconomic challenges. Repurposing these sites is crucial for sustainable land use and responsible resource management. This study presents a comprehensive decision framework tailored to the Indian mining context, utilizing a hybrid approach combining the analytic hierarchy process (AHP) and technique for order preference by similarity to an ideal solution (TOPSIS) methodology. The proposed framework assesses and ranks alternative repurposing options by considering a multi-criteria evaluation, including ecological, economic, social, and regulatory factors. AHP is employed to determine the relative importance of these criteria, reflecting the unique priorities and perspectives of stakeholders involved in the repurposing process. TOPSIS then identifies the optimal alternatives based on their overall performance against the established criteria. This hybrid methodology contributes to informed decision-making in the sustainable repurposing of abandoned surface coal mines in India. It aids in identifying the most viable and environmentally responsible alternatives, promoting efficient land use and resource conservation while addressing the challenges associated with abandoned mine sites. The methodology’s applicability extends globally to industries facing similar repurposing challenges, facilitating the transition toward a more sustainable and responsible land reclamation and resource management approach. The methodology is implemented using real mine data and demonstrates the analysis for evaluation among multiple alternatives such as solar parks, fish farming, eco-resorts, forestry, and museums. In our study, eco-resorts show more promise based on the significant potential for local economic development, provision of local employment, long-term revenue generation, potential for upskilling local youth in management, gardening, construction, and animal husbandry, and serving as a site for exhibitions of various arts and crafts.

Prediction of rock fragmentation in a fiery seam of an open-pit coal mine in India

Spontaneous combustion of coal increases the temperature in adjoining overburden strata of coal seams and poses a challenge when loading blastholes. This condition, known as hot-hole blasting, is dangerous due to the increased possibility of premature explosions in loaded blastholes. Thus, it is crucial to load the blastholes with an appropriate amount of explosives within a short period to avoid premature detonation caused by high temperatures of blastholes. Additionally, it will help achieve the desired fragment size. This study tried to ascertain the most influencial variables of mean fragment size and their optimum values adopted for blasting in a fiery seam. Data on blast design, rock mass, and fragmentation of 100 blasts in fiery seams of a coal mine were collected and used to develop mean fragmentation prediction models using soft computational techniques. The coefficient of determination (R2), root mean square error (RMSE), mean absolute error (MAE), mean square error (MSE), variance account for (VAF) and coefficient of efficiency in percentage (CE) were calculated to validate the results. It indicates that the random forest algorithm (RFA) outperforms the artificial neural network (ANN), response surface method (RSM), and decision tree (DT). The values of R2, RMSE, MAE, MSE, VAF, and CE for RFA are 0.94, 0.034, 0.027, 0.001, 93.58, and 93.01, respectively. Multiple parametric sensitivity analyses (MPSAs) of the input variables showed that the Schmidt hammer rebound number and spacing-to-burden ratio are the most influencial variables for the blast fragment size. The analysis was finally used to define the best blast design variables to achieve optimum fragment size from blasting. The optimum factor values for RFA of S/B, ld/B and ls/ld are 1.03, 1.85 and 0.7, respectively.

Living with coal in India: A temporal study of livelihood changes

This article asks what it is like for the rural poor to live with coal over time as mines expand and agriculture and forest-dependent ways of living inevitably become more restricted. Research on the expansion of open pit coal mining in India shows a widespread inability to appropriately compensate the rural poor for lost land and access to common property resources. Yet it is simultaneously clear that the growth of coal extraction over time ensures increased community dependence on mainly informal, coal-based livelihoods. What then happens over the long-term for people who live in and around the coalfields? Drawing on evidence from 2011 to 2022, this article explores longer term changes for mine-affected people next to major coal mines in Telangana state, India. Specifically, it examines a) the acquisition of forest and agricultural lands for the expanding mines, b) the operating mines and their environmental implications, but also improved job opportunities, and c) mine closure as an opportunity to rehabilitate the landscape and return the land for alternative community uses post mining. The results add to the understanding of the long-term changes that large-scale mining brings to rural communities, and the challenges to a just transition once coal mining inevitably comes to an end.

Evaluation of Social Externalities in Indian Coal Mining Industry - A Concept

Concept of externality is century old. The action of one consumer or a firm should not affect the well-being of another consumer or a firm with whom there is no direct business relationship. Nevertheless, in reality, our economic activities control natural systems directly or indirectly, and definitely has some externalities. This arises when an individual or a firm takes an action but does not take account of the external cost or benefits that are being generated because of lack of any incentive. In this paper, an attempt has been made to identify the social externalities of coal mining in India.

A Scientific Exploration of Blast-Induced Ground Vibration Mitigation Strategies for Sustainable Coal Mining in India

A Scientific Exploration of Blast-Induced Ground Vibration Mitigation Strategies for Sustainable Coal Mining in India

The spatial and economic footprint of the coal industry on rural livelihoods in Jharkhand, India

The socio-economic dimensions of coal mining in India form a complex picture of inter-linked livelihoods and economic dependencies. In this article, we contribute to sharpening this understanding through an analysis of household reliance on coal-related livelihoods. Through a telephone survey of 2000 households, stratified by proximity to active coal mines (within 5 km, 5–10 km, and 10–20 km), we provide new evidence of the spatial nature of formal and informal coal-related employment. Our findings indicate a pronounced concentration of coal-related livelihoods within a 5 km radius of active mines, whereas approximately half of the households in each distance stratum are reliant on casual labour incomes. This work sheds light on the concentrated spatial footprint of extractive industries and broader challenges of employment informality relevant to necessary just transition and rural development policies in India.

Machine learning approach for the prediction of mining-induced stress in underground mines to mitigate ground control disasters and accidents

The bord and pillar method is commonly employed in Indian underground coal mines, and the extraction rate varies between 30 and 65%. During pillar extraction, pillars are subjected to severe stress conditions. Due to this, the natural state of stress equilibrium is disturbed, resulting in severe strata control problems leading to sudden, unpredictable failure such as a premature collapse of pillars, severe roof or side fall, and sometimes leading to serious/fatal injury or burial of machinery. This paper deals with the prediction of mining-induced stress during pillar extraction using Machine Learning (ML) techniques like Random Forest and Multilayer Perceptron. The various factors used for the formulation of the models for predicting the mining-induced stresses are Depth of the workings (H), Panel width/length (W/L), Pillar width/working height (w/h), Goaf length, and Area of extraction. This paper highlights the importance of operational parameters rather than geological parameters. The Correlation coefficient (R2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${R}^{2}$$\\end{document}) of mining-induced stresses for the case studies discussed in the paper is 0.85 for Random Forest and 0.76 for Multilayer Perceptron, which shows Random Forest results have a comparative edge over Multilayer perceptron. With this developed prediction models, the stress conditions of pillars can be predicted.Graphic abstract

Time Series Forecasting of Indian Coal Mines Fatal Accidents

Time Series Forecasting of Indian Coal Mines Fatal Accidents

Soil pollution in Indian coal mines, available remediation techniques and rock dust application: A review

Soil pollution in Indian coal mines, available remediation techniques and rock dust application: A review

Hydro-Mechanically Coupled Numerical Modelling of Protective Water Barrier Pillars in Underground Coal Mines in India

Hydro-Mechanically Coupled Numerical Modelling of Protective Water Barrier Pillars in Underground Coal Mines in India

Analysis of Bottleneck using Mine Production Index and Ishikawa Diagram: A case of Indian Coal Mine

The traditional way of coal production and management is still predominant in the Indian coal mining industry which has led to a widespread waste of resources both materials and humans. Operational loss of the mining machinery and equipment is one of the key factors for the low performance and productivity of mines. This research presents an application of the integrated approach of the Mine Production Index and Ishikawa Diagram in an Indian coal mine to study the bottleneck equipment in the mining operation among the fleet of the shovel, dumper, and dozer. Mine Production Index (MPI) identifies the bottleneck equipment in the mining operation, and Ishikawa Diagram presents the Root Cause Analysis of bottleneck equipment. The fuzzy Analytic Hierarchy Process (FAHP) is used to determine weights for MPI calculation using information gathered from a group of 11 experts through Structured interviews. The study found that the dozer fleet is the bottleneck equipment and the ineffectiveness of the dozer fleet can be grouped into 4 categories as enumerated on the Ishikawa diagram. The study proposes that the ineffectiveness of the dozer fleet can be improved with an increase in its performance rate. The study is based on the judgments of the experts for the case mine, which may limit the external validity. This paper is an original contribution to the analysis of mining equipment using the Mine Production Index and Ishikawa Diagram in an Indian coal mine.

Hard coal mining in India and the opportunities for application of foregoing demethanization in Moonidih colliery

Hard coal mining in India and the opportunities for application of foregoing demethanization in Moonidih colliery

Mineralogical variations and geochemical distribution of rare earths and Yttrium (REY) in coal and overburden rocks of some Indian coal mines of Gondwana coalfield

Mineralogical variations and geochemical distribution of rare earths and Yttrium (REY) in coal and overburden rocks of some Indian coal mines of Gondwana coalfield

Electrical resistivity tomography technique coupled with numerical modelling: A case study for stability analysis

AbstractCavity due to underground old mine workings is one of the major threats to the coal mines and the overlying subsurface and surface properties, which need to be protected. The detection of old mine workings and stability assessment of overlying strata are common problems in most of the Indian coalfields. Several coal mines in India are loss‐making, mainly due to different types of mine hazards. Khandra mine is one such mine at Raniganj Coalfield, Eastern Coalfields Ltd., a subsidiary of Coal India Limited. In the present study, 2‐dimensional and 3‐dimensional electrical resistivity tomography were carried out for detailed subsurface characterization. It supports delineating underground workings, including the nature of voids/cavities (air or water‐filled). Excessive distortions were reported in electrical resistivity tomography application, especially at the near‐surface, owing to large resistivity variations. Refinement of the model by half‐unit electrode spacing was attempted here to reduce the distortions with minimum possible absolute errors. 3‐Dimensional resistivity volumetric model was also developed with the help of five electrical resistivity tomography parallel profiles for better apprehension of the subsurface. Analysis provided important inputs for stability analysis using 3‐dimensional numerical modelling. The physico‐mechanical properties of the overlying strata, pre‐excavation in situ stresses, boundary conditions and the mine geometry simulation were incorporated for understanding the stability analysis. Stability analysis was carried out using the finite difference technique. The analysis of 3‐dimensional numerical modelling indicated that two distinct layers comprising (i) laterite/part of the course to medium‐grained sandstone and (ii) developed galleries of R‐IX seam exhibited a very low safety factor below 1.0, indicating potholing/subsidence susceptibility. The other three layers comprising parts of fine‐grained sandstone exhibited a relatively higher safety factor of around 2.0, indicating moderately stable zones, but not on a long‐term basis. Parts of Siduli stream embankments need suitable retaining walls to avoid water inundation for the stability of the area.

IOT Powered Smart Strata Monitoring System for early and precise detection of Convergence in Underground Coal Mines

Roof fall, bed separation and convergence are one of the serious life-threatening problems faced by the miners in all the underground coal mines since early mining age to current mining situations. Most of the statistics regarding fatal accidents and trapped miners in underground coal mines are the results of sudden roof fall due to bed separation of overlying strata in the underground mine galleries or roadways. In Indian underground coal mines, many of fatalities were seen over the years although this rate has been gradually decreasing since past decade only by implementing some of physical and mechanical methods to detect or monitor strata convergence. With the advancement of technology, sensors become an extensive part of everyday life. Various researchers are trying to monitor, detect and prevent fatalities due to roof fall in real time scenario in underground coal mines with the use of sensors, IOT and other technology. The main aim is to Install a non-invasive laser proximity sensor in the hole drilled into the roof where the necessity arises to remotely monitor the convergence in the strata under bad roof conditions in underground coal mines and monitor them remotely with an automated display showing the details of the bed separation, roof convergence and detailed information about the roof condition remotely. Key Word: Internet of Things, Strata Monitoring, Roof Fall, Convergence, Real time, Display device, Proximity sensors, Remote Monitoring.