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The first coal mining in India was started in the seventeenth century with an unplanned way in Raniganj coalfield, the coal capital of India. The coalfield was possessed by several small private companies which were nationalized in 1973. A part plan of Chanch/Victoria Area, Victoria West Colliery, BCCL, Raniganj Coalfield, India, indicates an underground coal mine gallery/goaf in the Begunia Coal-seam that connects to a Light Casting Factory. It was established as “Barakar Iron Works” in the year 1881 by the government at that time. It is understood that the approaching gallery was used for coal supply to the “Light Casting Factory” by the mining of “Begunia Coal-Seam”. Mostly, these are uncharted and very poorly documented with scarce mine plans. So, the present study attempts to explore the location, depth, extension, and condition of the old working gallery through time-lapse monitoring using a combined study comprising of Self-Potential (SP) and Electrical Resistivity Tomography (ERT) techniques. Four SP profiles data along a line and thirteen ERT profiles data in four different lines were collected across the expected site with different station/electrode spacing covering different profile length in four seasons, viz., Summer (May 2016), Monsoon (August 2016), Post-Monsoon (October 2016) and Summer (April 2017). SP data were analysed using simulated annealing (SA) optimization technique for the evaluation of model parameters. The ERT data were acquired using Wenner, Dipole–Dipole and Schlumberger arrays and inversion of the combined data set was performed using the 2.5D ZZRESINV inversion software. Prominent negative SP signature with equivalent low resistivity anomaly have been delineated that possibly indicate the presence of the old mine working/mine gallery. However, the overall results of time-lapse study inferred that the ground is stable. All results are corroborated with available lithology and field photographs.

We present the seismic site characterization study using joint modelling of Horizontal-to-Vertical Spectral-Ratio (HVSR) and Rayleigh wave-phase velocity-dispersion curves obtained from Multi-channel Simulation with One Receiver (MSOR) in a part of Dhanbad, Jharkhand, India. The joint analysis of these two different but complementary datasets puts stronger constraints on the model parameter search space than one dataset and may help us in finding more unique shear-wave velocity model. The microtremor data from 12 observation points were utilized to iteratively search 1D shear-wave velocity profiles in a predefined model search space. These 1D shear-wave velocity models were interpolated to generate a 2D shear-wave velocity profile of the site using the cubic spline method. Our results show that the high peak amplitude value of HVSR is associated with low peak-period values of HVSR at a distance of ~ 60 m from the southern end of the profile; which may indicate the presence of the Basin Edge Effect. We identified four layers based on significant changes in the shear wave velocities to a depth of ~ 60 m. The major impedance contrasts are located at average depths of ~ 13 m, ~ 40 m and ~ 55 m, respectively. These layers from the surface may indicate the presence of soil, highly weathered rock mass, moderately weathered rock and bedrock, respectively. The depth of engineering solid bedrock (Vs > 600 m/s) is found at the depth of 55 m in the south which gradually decreases to a depth of 40 m in the northern end of the profile. The shear-wave velocity (Vs 30) for this area varies between 293 and 357 m/s; which can be classified as “D-type site”. For validation and comparison of our results, the Electrical Resistivity Tomography (ERT) data were also recorded along the same traverse using Wenner and Schlumberger configurations. Our results show a significant amount of correlation between the 2D shear-wave velocity and resistivity profiles obtained from joint analysis of tremor and ERT data.

Aquifer health assessment is essential for sustainable groundwater management, particularly in semi-arid regions with challenging geological conditions. This study presents a novel methodology for assessing aquifer health in the Barakar River Basin, a hard-rock terrain, by integrating tree-based classification, deep learning, and the Soil and Water Assessment Tool (SWAT) model. Employing Random Forest, Decision Tree, and Convolutional Neural Network (CNN) models, the research examines 20 influential factors, including hydrological, water quality, and socioeconomic variables, to classify aquifer health into four categories: Good, Moderately Good, Semi-Critical, and Critical. The CNN model exhibited the highest predictive accuracy, identifying 33% of the basin as having good aquifer health, while Random Forest assessed 27% as Critical heath. Pearson correlation analysis of CNN-predicted aquifer health indicates that groundwater recharge (r = 0.52), return flow (r = 0.50), and groundwater fluctuation (r = 0.48) are the most influential positive factors. Validation results showed that the CNN model performed strongly, with a precision of 0.957, Area Under the Curve–Receiver Operating Characteristic (AUC-ROC) of 0.95, and F1 score of 0.828, underscoring its reliability and robustness. Geophysical Electrical Resistivity Tomography (ERT) field surveys validated these classifications, particularly in high- and low-aquifer health zones. This study enhances understanding of aquifer dynamics and presents a robust methodology with broader applicability for sustainable groundwater management worldwide.

Seepage of water through an underground coal-mine barrier is a common indicator of a potential hydrogeological hazard. The Jharia coalfield has witnessed several deadly inundation events in different underground mines. The present study deals with the mapping of water seepage through an underground coal-mine barrier of the Jogidih Colliery, Jharia coalfield using self-potential (SP) and electrical resistivity tomography (ERT). Initially, numerical analysis of the SP data was carried out using particle swarm optimization (PSO) and simulated annealing (SA) inversion, which indicated the suitability of both PSO and SA, though the PSO algorithm performed better. ERT analysis of a synthetic model similar to the present underground coal-mine environment was also carried out using Wenner, Schlumberger, and dipole–dipole array configurations, which indicated that the dipole–dipole configuration was the most effective. Subsequently, the SP data collected from the underground coal-mine barrier were analyzed using PSO and SA; both designated the presence of seepage within the barrier and provided information concerning its geometry and location. It is argued that these SP anomalies are a direct result of transmutations in the streaming potential produced by preferential drainage through the barrier. Following the SP results, ERT was used for detailed high-resolution imaging of the barrier seepage/leakage drainage. Furthermore, the results obtained from ERT and SP were compared to understand their efficacy in resolving seepage detection complications and result validation. The combined study suggests a cylindrical geometry of seepage from an adjacent sump pit through the coal-mine barrier. Physicochemical analysis of the groundwater in the mining area indicates high sulfate levels.

This study explores the comprehensive approach of utilizing physiographical and geophysical electrical resistivity tomography (ERT) investigation to evaluate and address the challenges associated with abandoned, unplanned water-filled galleries in Chasnala Colliery, located in Jharkhand, India. The integrated methodologies facilitate a thorough examination of subsurface conditions, encompassing factors such as geological stability, hydrological fluctuations, and environmental considerations. Utilizing physiographical analysis is of utmost importance in identifying locations with potential risks and developing appropriate site-specific reclamation procedures in the study area. The ERT analysis has successfully confirmed the findings of the physiographical study, revealing the presence of five distinct underground galleries, namely, GL1, GL2, GL3, GL4, and GL5, that are likely submerged in water. These galleries establish connections between the underground spaces and the groundwater, as indicated by their low resistivity values of ~50 Ωm or less. The resistivity measurements exhibit variations that can be attributed to fluctuations in the underground water content. The Wenner, Schlumberger, and dipole–dipole arrays have adeptly discerned the existence of water-filled underground galleries with commendable accuracy. However, the joint array configuration stands out as the pre-eminent choice among these standards due to its unparalleled technical robustness. The findings concurred with the notable correlation between water-filled galleries’ spatial arrangement and shallow groundwater level. The integration of physiographical and ERT data improves the precision of subsurface characterization, facilitating informed decision-making for efficient water management and site rehabilitation in the context of opencast mining.

Underground galleries possess random subsidence threats if they are not treated well. Threats even become multifold when these galleries are located somewhere in the vicinity of the railway tracks. So, checking the stable ground formation or the health of the subsurface formation near railway tracks and mapping the galleries are very important tasks for the sake of the environment, economy and lives. Galleries under the present study are associated with the coal seam-X and seam-XA of the Jogidih Colliery of Jharia Coalfield. Seven electrical resistivity tomography (ERT) profiles and magnetic surveys were performed at a side of the railway track to characterize the subsurface formation near railway tracks and to detect the gallery and its extension. Both ERT and magnetic data analysis suggest the presence of some galleries at a certain distance from the railway tracks. Moreover, combined analysis of ERT and magnetic data suggests that ground within ~20 m from the railway tracks is found to be stable with homogeneous compact formation.

The Jharia coalfield stands as a paramount asset within the Indian economy. However, many pressing issues, such as coal fires, land subsidence, unplanned mining, child labor, deforestation, and air pollution, demand immediate attention. Effective planning and comprehensive mitigation strategies are imperative to address these challenges. This research centers on evaluating an area near Bhuiyadih village subjected to rat hole mining using non-invasive geophysical methods. The evaluation includes a joint analysis of multiple geophysical techniques, such as gravity, magnetic, and seismic surface wave methods. The potential data has been evaluated by generating edge detection, upward continuation maps, and radial average power spectrum (RAPS) plots. Seismic surface wave velocity structure has been evaluated and used as a constraint to model the subsurface structures using potential field data. Evaluating subsurface layers from the RAPS, Seismic surface wave model, and 2D model generated from the potential data indicates a weathered layer, an overburden sandstone layer, and a coal seam of thickness ~ 4.5 m, ~ 14 m, and ~ 11 m, respectively. The wideness of the gallery boundary has been evaluated using the composite lineament map and found to be surpassing approved limits for underground mining, signifying evidence of rat hole mining practices. The thin pillars in the coal seam and fractures observed on the surface indicate the failure of overburdened rock masses, leading to land subsidence in the nearby villages. The study reinforces the urgency of shifting the local population to a safer environment to avoid unfortunate situations.

This paper deals with severe issue of groundwater crisis over a part of hard rock terrain in the premises of Central Institute of Mining and Fuel Research (CIMFR), Dhanbad, Jharkhand, India. The goal of this study is delineation and mapping of fractured rock mass for groundwater exploration. Generally, fractured rock formation is the only source of groundwater in hard rock terrain. Electrical resistivity tomography (ERT) survey was conducted along three profiles over different parts of CIMFR premises using Wenner–Schlumberger and dipole–dipole arrays. Combined inversion of both arrays has been carried out during data analysis for better delineation of fracture rock masses in the complex geological environment. Two water-saturated fracture zones have been identified for the availability of groundwater, which has been confirmed by direct borehole drilling. This proves the effectiveness of ERT survey by combined inversion of both arrays for delineation of fracture zones.

Land subsidence is a serious problem in Indian coalfields due to old underground mine workings. Unfortunately, most of these are uncharted as no mine plans are available. The hidden galleries, goafs, shafts etc. may pose great threat for future mine development as well as to the local environment. The mine workings should be charted to undertake an effective preventive action. In the present study, 2D electrical resistivity tomography (ERT) technique has been used to detect underground mine workings, mainly air or water filled galleries. Initially, the whole exercise has been executed through a synthetic model study. Gaussian random noise of 5mV/A has been added with synthetic data to demonstrate field condition which provides realistic results. ERT survey was conducted over a part of Jogidih coal mine of Jharia coal field in India for a first time. Four electrode configurations, Wenner, Schlumberger, dipole-dipole and gradient were considered for this study. The results indicate the presence of sub-surface water and air filled cavity due to high resistivity contrast with surroundings. Copyright 2017 Geological Society of India

The present study deals with the characterization of subsurface coal fires of East Basuria colliery in Jharia coal field, India using tilt derivative and downward continuation of magnetic data. Magnetic data processing methods such as diurnal correction, noise removal, reduction to pole, tilt derivative and downward continuation have been used to process the data and for the interpretation of results on the basis of magnetic properties of overlying materials which change with the temperature variation above or below the Curie temperature. Most of the magnetic anomalies are associated with coal fire and non-coal fire regions which are correlated with tilt-derivative anomaly and corresponding downward-continued anomaly at different depths. The subsequent surface and subsurface characteristics are explained with good agreement. Approximate source depth of principal anomaly inferred from tilt derivatives method are corroborated with multi-seam occurrences, mine working levels and surface manifestation which are also correlated well with 3D model of downward continued anomaly distribution.