Underground Mining Research Articles

Multicriteria risk assessment of water inrush in underground mines with large-scale curtain grouting: a mine disaster risk reduction strategy

This paper presents a synthetic method to assess the risk of mine water inrush before and after large scale curtain grouting based on GIS platform. Firstly, nine factors were selected from three aspects: geological conditions, hydrogeological conditions and curtain grouting parameters, to construct a multi factor assessment model. The combined weight of every factor was determined using the minimum deviation comprehensive weighting method, which can reduce the polarization effect of various assessment methods in multicriteria decision. Then, the effectiveness of the synthetic method was validated through the Maoping lead–zinc mine in Southwest China. The mining area was divided into five zones, namely safe zone, relatively safe zone, transitional zone, relatively dangerous zone, and dangerous zone. The assessment results show that the relatively dangerous and dangerous zones were significantly reduced, while the safe, relatively safe and transitional zones were significantly increased after large scale curtain grouting. Finally, we analyze the impact of curtain grouting on the risk of mine water inrush and the mechanism of zoning evolution from three aspects: water source control, pathway sealing, drainage, and pressure reduction. This work provides an effective strategy for mine disaster risk reduction.

‘New mining scheme, same old problems?’; risk factors and health challenges in underground community mining in Ghana

Abstract Ghana’s small-scale mining sector has long been a cornerstone of its economy and a vital source of livelihood for many communities. However, the sector is plagued by significant challenges, including environmental degradation, health and safety risks, and illegal practices. In response, the Ghanaian government introduced the Community Mining Scheme (CMS), a new mining model designed to promote local community participation in artisanal small-scale gold mining (ASGM). This study examines the workplace risk factors and associated health challenges faced by ASGM miners under the CMS, drawing on interviews with fifty underground CMS miners in Ghana. Our findings reveal that miners continue to face numerous health and safety challenges, including inadequate lighting, poor ventilation, exposure to noise and odors, unsupported or poorly supported loose materials, non-use of personal protective equipment, high dust levels, and unsafe blasting practices. Additionally, health concerns such as skin rashes, musculoskeletal injuries, and the risk of mercury poisoning persist. These challenges mirror those reported in the literature on unregulated and illegal ASGM in Ghana, indicating that existing issues remain unresolved under the CMS. To prevent the undermining of this initiative, it is crucial to adopt progressive practices, such as localized coping strategies and the recruitment of trained professionals to lead ASGM operations within the CMS. Enhancing miners’ risk perception through targeted outreach and awareness campaigns is also essential. Further recommendations for mitigating safety risks and health challenges are discussed in the article.

Review on Engineering Application Status of Gob-Side Entry Retaining Technology in China

Gob-side entry retaining (GSER) technology has been widely used in underground coal mines. However, the applicable conditions of GSER technology in practical engineering still need further clarification to prevent the safety hazards and significant economic losses caused by its failure. In this study, 587 application cases of GSER in China from 2000 to 2024 were collected, and the relevant data, such as geological conditions and key technical parameters of GSER projects and their impact on engineering practices, were systematically analyzed. Considering the technical characteristics and the developing status of GSER technology, the current status of the application of GSER engineering in the mining areas of China was obtained, and then the applicable geological conditions and optimal technical parameters for the effective implementation of GSER technology were identified. Additionally, the existing technical challenges and further prospects of GSER technology were illustrated. This study provides a reference for reasonable applications and further research of GSER technology.

An AI-Based Approach for Developing a Recommendation System for Underground Mining Methods Pre-Selection

Selecting the most appropriate mining method to recover mineral resources is a critical decision-making task in mining project development. This study introduces an artificial intelligence-based mining methods recommendation system (AI-MMRS) for the pre-selection of underground mining methods. The study integrates and evaluates the capability of two approaches for mining methods selection (MMS): the memory-based collaborative filtering (CF) approach aided by the UBC-MMS system to predict the top-3 relevant mining methods and supervised machine learning (ML) classification algorithms to enhance the effectiveness and novelty of the AI-MMRS, addressing the limitations of the CF approach. The results reveal that the memory-based CF approach achieves an accuracy ranging from 81.8% to 87.9%. Among the classification algorithms, artificial neural network (ANN) and k-nearest neighbors (KNN) classifiers perform the best, with accuracy levels of 66.7% and 63.6%, respectively. These findings demonstrate the effectiveness and viability of both approaches in MMS, acknowledging their limitations and the need for continuous training and optimization. The proposed AI-MMRS for the pre-selection stage supplemented by the direct involvement of mining professionals in later stages of MMS, has the potential to significantly aid in the MMS decision-making, providing data-driven and experience-based recommendations following the ongoing evolution of mining practices.

Research on visible light communication channel model in underground mines

Abstract In order to effectively model the Visible Light Communication (VLC) channel in underground mines, this paper delves into the challenges of the underground environment and develops a mathematical model by analyzing the propagation characteristics of visible light. The objective is to deepen our understanding of light signal behavior in this unique setting. Most existing research focuses on visible light channel modeling in indoor environments, with limited studies on underground mines. Our model takes into account the irregular surfaces of mine walls, as well as the effects of factors such as high dust concentration, extreme temperatures and pressures, light absorption by mine walls, and obstruction caused by large machinery on the propagation of visible light signals. This paper introduces refined optical propagation models that incorporate both scattering and light absorption considerations, resulting in a maximum received power of -46.12 dBm, which is significantly lower than that in indoor environments. These models enhance our ability to analyze and improve channel performance, thereby optimizing communication efficiency.

Towards zero harm discourse: denaturing the safety performance plateau in underground mining

Towards zero harm discourse: denaturing the safety performance plateau in underground mining

Enterobacter spp. isolates from an underground coal mine reveal ligninolytic activity

Lignin, the second most abundant renewable carbon source on earth, holds significant potential for producing biobased specialty chemicals. However, its complex, highly branched structure, consisting of phenylpropanoic units and strong carbon-carbon and ether bonds, makes it highly resistant to depolymerisation. This recalcitrancy highlights the need to search for robust lignin-degrading microorganisms with potential for use as industrial strains. Bioprospecting for microorganisms from lignin-rich niches is an attractive approach among others. Here, we explored the ligninolytic potential of bacteria isolated from a lignin-rich underground coalmine, the Morupule Coal Mine, in Botswana. Using a culture-dependent approach, we screened for the presence of bacteria that could grow on 2.5% kraft lignin-supplemented media and identified them using 16 S rRNA sequencing. The potential ligninolytic isolates were evaluated for their ability to tolerate industry-associated stressors. We report the isolation of twelve isolates with ligninolytic abilities. Of these, 25% (3) isolates exhibited varying robust ligninolytic ability and tolerance to various industrial stressors. The molecular identification revealed that the isolates belonged to the Enterobacter genus. Two of three isolates had a 16 S rRNA sequence lower than the identity threshold indicating potentially novel species pending further taxonomic review. ATR-FTIR analysis revealed the ligninolytic properties of the isolates by demonstrating structural alterations in lignin, indicating potential KL degradation, while Py-GC/MS identified the resulting biochemicals. These isolates produced chemicals of diverse functional groups and monomers as revealed by both methods. The use of coalmine-associated ligninolytic bacteria in biorefineries has potential.

The investigation of micro-crack generation in cementitious mine seals via temperature and strain analysis

Mine seals are employed in underground coal mines to effectively isolate abandoned areas from active workings. The seals are engineered to prevent air movement and endure dynamic pressure events resulting from methane explosions. Mine seals are made from cementitious materials and undergo a curing process that involves an exothermic reaction known as hydration. The presence of moisture (hydration) may result in the mixture contracting, which could subsequently lead to cracking during the early phases of the curing process. Cracks in the seal can influence the performance and structural stability. This study examines the formation of micro-cracks in cementitious mine seals throughout the curing process by evaluating temperature and strain data collected from thermocouples and strain gauges that were installed during the pouring phase. The samples for the mine seal were prepared using two distinct mixtures: traditional concrete and pumpable products sourced from conventional suppliers. Heat evolution curves were produced for each sampling location corresponding to the three samples. The samples of Mixture A and B, prepared according to specifications, exhibited the anticipated heat evolution curves, with the maximum temperature occurring at the center of the samples. In contrast to the other mixtures, the samples of mixture C, which were prepared outside of the specified parameters, exhibited the highest temperature at the bottom of the sample. The strain measurements showed a correlation with temperature readings, indicating that mixtures A and B exhibited the highest strain at the center of the sample, while mixture C demonstrated the greatest strain at the bottom of the sample. The examination of the gathered data reveals a significant likelihood of micro-cracks forming in each of the samples.

Morphology of Brine‐Seawater Interface and Spatial Distribution of Submarine Groundwater Discharge Windows in the Muddy Coast

AbstractThe brine‐seawater interface (BSI) is a unique type of groundwater‐seawater interface (GSI) characterized by the higher density of underground brine compared to seawater. This study focuses on characterizing the bay‐scale BSI morphology and identifying submarine‐groundwater discharge windows using a comprehensive in‐situ geophysical detection on the south bank of Laizhou Bay. Our findings reveal that the BSI forms an extensive mixing zone (15–20 km) without distinct contours between waters of varying salinities. The discharge windows for underground brine are located in nearshore areas with fine sand distribution and offshore pockmark areas. Hydraulic and salinity gradients drive the underground brine discharge through these windows. The aquitard window is the primary area for shallow and deep brine exchange, likely evolved from paleochannels, ancient tidal creeks, or ancient underwater barriers. These findings provide crucial modeling support for analyzing environmental evolution mechanisms and theoretical basis for planning the underground brine mining in similar coastal regions.

A comprehensive analysis of coal toughness index: Relationships among coal toughness index, uniaxial compressive strength and proximity parameters

Coal and gas outbursts are significant safety hazards in underground coal mining, particularly in deep Australian coal seams. While the traditional outburst risk management relies on threshold limit values of seam gas content, recent experiences have shown that this approach overlooks important factors such as coal toughness and strength. This study evaluates the effectiveness of the coal toughness test, also known as the Protodyakonov strength test, as a predictor of outburst risk. After upgrading the test rig and updating testing procedures, the toughness index f was compared with conventional strength parameters, revealing a strong positive correlation with uniaxial compressive strength (UCS) and drop hammer impact strength. An analysis of 98 coal samples taken from seven seams at three Australian mines revealed that lower moisture content and higher apparent relative density are associated with increased coal toughness. Specifically, the Pearson and Spearman correlation coefficients of −0.79 and −0.78 were observed, respectively, indicated a strong negative relationship between coal moisture content and toughness. Additionally, coal seams with lower volatile matter content exhibited higher toughness values. The study proposes adopting the coal toughness index as a robust alternative to the conventional indicators such as UCS, especially when obtaining intact coal samples is difficult. Incorporating the toughness index into the outburst risk assessment can improve safety by adopting a more comprehensive and reliable approach.

UAV-MSSH: A novel UAV photogrammetry-based framework for mining surface three-dimensional movement basin monitoring

Monitoring the surface three-dimensional movement caused by underground coal mining is a critical and challenging task. Despite many methods have been proposed in previous works, they focus more on the subsidence, with insufficient discussions on the horizontal displacement and the underlying coupled mechanisms between them. To address these issues, we introduce a novel UAV photogrammetry-based framework for mining surface three-dimensional movement basin monitoring, named UAV-MSSH. This framework consists of two branches: vertical subsidence and horizontal displacements. For the subsidence branch, we propose an improved cloth simulation filtering algorithm based on slope zone indexing (CSFS) to model high-precision subsidence basins. In the horizontal displacement branch, we develop a probability integral prediction prior-guided COSI-Corr (PIM-CC) method for displacement detection by bridging the gaps between the horizontal displacement and subsidence. Employing this framework, we monitored the surface three-dimensional movement using the UAV oblique photogrammetry method at a working face in western China. The accuracy evaluation results with net station GNSS data show that the RMSE of the subsidence basin is 161 mm, the relative error is 3.1 %, and the RMSEs of the east–west and north–south components are 99 mm and 85 mm, respectively, which demonstrates the effectiveness and practicality of our proposed UAV-MSSH framework in mining surface monitoring tasks. This study establishes an innovative and proven methodology for UAV monitoring in the mining field, which is valuable for safe production, disaster warning, and ecological restoration.

Multisource remote sensing monitoring and analyzing for land subsidence and crop growth in a coal mining area under different rainfall conditions

Coal has been crucial in driving economic development and production construction. However, the mining-induced subsidence may cause irreversible damage to the surrounding environment of vegetation growth. Meanwhile, with the worsening of global warming, the frequency and intensity of extreme water-related weather events, such as droughts and excessive rainfall, are on the rise, which leads to heightened impacts on ecosystems and agricultural production. Consequently, extreme water-related weather, the distribution of land subsidence, and its effect on vegetation have attracted significant attention. Based on the Sentinel-1 radar data and Sentinel-2 multispectral data from 2017 to 2022, the SBAS-InSAR technology, the object-oriented classification, and the Normalized Difference Vegetation Index (NDVI) were employed respectively in the study to obtain the spatial-temporal evolution of land subsidence, subsidence-induced water, and crop growth in Tiefa mining area, a representative coal mining area in Northeast China. Moreover, the relationship between land subsidence, subsidence-induced water, and vegetation change was analyzed combined with summer precipitation data. The results showed that: (1) The average cumulative subsidence of the mining area was 256.8 mm, and the subsidence area was 42.525 km2 for the six years. Among them, the heaviest subsidence reached a maximum of 380.5 mm in 2022, and the largest subsidence area was 20.109 km2 in 2017. (2) When the rainfall was excessive, the area of subsidence-induced water would increase sharply, with a proportion jumping to 9.71% from 5.37%, which indicated the subsidence would further amplify the destructive effect of excessive rainfall and waterlogging on land resources. (3) In addition to the existing water pits, ground cracks and shallow subsidence pits appeared under the influence of underground coal mining. The direct impact of ground cracks on crops was not apparent, while the effect of subsidence pits on crops under different rainfall conditions was dual character. In dry years, crops in the subsidence pits could grow better due to higher soil moisture. In wet years, crops in the subsidence pits would suffer the more severe waterlogging. The research results are of great significance for further understanding the influence of coal mining on surface vegetation in mining areas in Northeast China.

Discovery and Underground Mining of Large Deposits: Essential Training to Ensure Copper Supply

Editor’s note: The aim of the Geology and Mining series is to introduce early career professionals and students to various aspects of mineral exploration, development, and mining in order to share the experiences and insight of each author on the myriad of topics involved with the mineral industry and the ways in which geoscientists contribute to each. Abstract A supply shortfall of at least 6 million tonnes (Mt) Cu is expected by 2031—with total demand now forecast to increase from 25 Mt in 2023 to >36 Mt, and possibly to a suggested 50 Mt by 2050—given the present trend in demand. The deficit can be partially filled by increased mine production, expanding currently installed mine production capacity, and increasing Cu recycling. However, satisfying demand in 2050 as the demand-to-mining supply gap increases will require the accelerated discovery of at least five large Cu deposits—individually producing >0.5 to >1.0 Mt/yr Cu—and their related mine development, by 2030. These five deposit discoveries are required to replace mines scheduled to close in the 2050s, given the >20 years needed to take a deposit from discovery to mine production. The two largest sources of Cu supply, porphyry and sediment-hosted Cu deposits, can potentially fill the gap if enough discoveries are made; however, there is no evidence that this is about to occur. Future porphyry Cu discoveries are expected to be mined underground, mostly by a caving method. The demand increase is occurring at a time when the capital intensity of porphyry Cu mine development has almost doubled since 2006. We predict that the only solution to the future Cu demand-supply challenge for society and the mining industry in the short to medium term rests with simple demand-supply economics and a substantially increased Cu price. Copper substitution by other materials and recycling could potentially benefit from a significantly increased price; however, the major advantage will be conferred on deposits amenable to open-pit mining that are undeveloped because of price-dependent, failed feasibility studies. The challenge of possibly doubling Cu supply by ca. 2050 through developing mines on large Cu deposits—both discovered and undiscovered, in an unprecedented number and in a shorter period—will require a major increase in the number of competent mining industry personnel. This comes at a time when the industry faces an aging workforce, leading to a critical skills gap compounded by a chronic shortage of students graduating in the sciences and engineering with mining-related university degrees. There is an acute shortage of experienced professionals in cave mining, and the substantial number of open-pit mining professionals who are predicted to retire by 2030 will need to be replaced. On-the-job training of geoscientists and engineers after graduation, delivered by experienced practitioners through university-accredited professional development programs, is suggested as the solution.

A method for optimizing the capacity allocation of a photovoltaic-pumped hydro storage system in an abandoned coal mine

The enormous potential of the photovoltaic (PV) sector has aided in the faster attainment of China's “dual-carbon” aim. However, due to a scarcity of land resources and intermittent fluctuations in solar energy, it has been difficult to build large-scale PV bases, and existing PV systems also suffer from unstable power generation and seasonal fluctuations and are unable to be directly connected to the grid for use. However, abandoned mines with huge surface collapse zones and a large underground mining area offer a potential possibility for constructing photovoltaic-pumped hydro storage (PV-PHS) systems and limiting PV variations. Based on the abandoned mine pumbed hydro storage (AMPHS) potential assessment model and the optimized discrete wavelet decomposition algorithm, this study proposes a dynamic cycle optimization method for the PHS regulation capacity in an abandoned mine PV-PHS hybrid system. This approach is able to determine the optimal regulation capacity of AMPHS on a daily scale while limiting the volatility of the PV-PHS hybrid system. The method was applied to an abandoned mine PV-PHS hybrid system in Zaozhuang City, Shandong Province, and the optimal regulation capacity of the AMPHS was determined to be 88 MWh and 100 % elimination of PV generation volatility was achieved. This also reduces the economic cost by roughly 1.94 × 108 CNY. In addition, it is possible to store an average of 2.32 % of the PV power generated and to extend the power generation time by approximately 2.5 h per day. This research is critical for boosting the resource use of abandoned mines, and establishing the comprehensive usage model of new energy and abandoned mine resources.

Разработка трудноизвлекаемых запасов угля мобильными горнодобывающими комплексами без постоянного присутствия людей в зоне ведения горных работ

Today, millions of tons of coil remain in the subsoil and are written off as losses. These include hard-to-recover reserves unfit for mining with traditional high-performance means of integrated mechanization. One of the all-purpose technical solutions to the problem of developing such reserves can be technologies using robotic mobile mining equipment based on a heading-and-winning machine and a self-propelled car. Flowcharts for coal deposit development have been designed for seams unfit for mining with integrated mechanization means (medium thick seams, thick seams, flat and steeply inclined seams). These include open-pit and underground mining of marginal reserves from the side of the pit wall and limited reserves from the daytime surface performed by mobile mechanization means. During the operation of these means, the following process operations are repeated: coal breaking, loading into a self-propelled car, transportation along a preset trajectory, unloading into a reloader or other transport vehicle, or a warehouse on the bench. These operations can be robotized, which will increase both the safety and efficiency of coal mining. In order to perform coal-mining operations without constant attendance of maintenance staff, the existing mechanization means must be retrofitted with machine vision and a remote control system. Moreover, a robotized control system for the set of equipment must be developed to resolve the following problems. For the heading-and-winning machine: transportation (feed) along a straight line; transportation along the preset curve (formation of a diagonal entry); coal breaking at the preset thickness; coal breaking within coal-rock boundaries or along a preset cross-sectional contour; loading of broken coal into a self-propelled car; and control of the car loading level. For a self-propelled car: transportation along a preset trajectory from the loading point to the unloading point; control and management of the completeness of loading (unloading).

Causal Analysis of Roof Caving on Underground Mine: A New Theory and Optimized DEMATEL Approach

In the context of mines, roof-caving incidents constitute the most common and expensive accidents. To enhance the management and prevention of roof-caving accidents, it is imperative to investigate the factors that contribute to such incidents and comprehend the intricate causal relationships among them. This study aims to classify the causes of these accidents into three categories: basic factors, controllable factors, and sudden factors, based on the mechanism of roof caving. The categorization is primarily determined by two indicators: intervisibility and variability. Furthermore, the study delves into analyzing the mutual influence relationships among these factors and proposes the BCX theory (Basic-Controllable-Sudden causing theory) for roof caving. Subsequently, based on this theory, an index system called BCX is established for roof caving, and the DEMATEL method is employed to analyze the factors within this index system. To attain more accurate results, this study utilizes interval trapezoidal type-2 fuzzy number scale optimization and Tsallis relative entropy to address the limitations of the DEMATEL method. By comparing the outcomes of the traditional and optimal DEMATEL methods, it is observed that the optimal method exhibits superior applicability in the BCX index system of roof caving, with results that align closely with the actual scenario. Therefore, the optimal DEMATEL method’s analysis of centrality, importance, and chain relationships between the factors within the BCX index system will offer valuable guidance for preventing roof-caving accidents in mining operations.

Analysis of Factors Affecting Premature Tire Damage on Loader Units and Its Impact on Underground Mine Productivity at Pt. Freeport Indonesia

PT. Freeport Indonesia, the largest underground mining company in Indonesia, faces a significant challenge with premature tire damage on its production units. This damage results in costly downtime and negatively impacts mine productivity. This research aims to identify the factors contributing to premature tire damage and analyze their impact on company expenditures. Using a quantitative research method and multiple linear regression analysis techniques, this study found that factors such as "Puncture steel" and "Running flat" have a negative impact on company expenditures. On the other hand, the factor "Rock cut" shows a positive impact on company expenditures. This research provides valuable insights for PT. Freeport Indonesia to develop more effective tire maintenance strategies, reduce downtime, and optimize operational costs.

Mechanical mechanism of dip effect on bearing capacity of the pillar strength

Abstract The dip effect on pillar strength in underground ore-body mining is well established, but the variation in stress path (magnitude and direction of stress) due to changing inclination angles requires further study. Using elasticity theory, the Euclidean mean stress tensor characterizes the stress state in pillar zones. Numerical simulations provided the second-order tensor of peak stress for each pillar unit. Through tensor statistical analysis, the Euclidean mean stress tensor matrix was calculated, and its eigenvalues and eigenvectors, representing the magnitude and direction of the principal stress, were derived. This analysis explained the intrinsic dip effect on pillar strength through principal stress characteristics. Finally, the pillar strength envelope function for varying width-height ratios at any dip angle was obtained using the random gradient descent algorithm. Results indicate that in the peak stress state, the average principal stress directions of the pillar change with orebody dip angle, affecting the stress path. The average principal stress increases with pillar size due to increased constraints. These findings offer theoretical insights for pillar design and stability analysis.

Optimizing Underground Coal Mine Safety: Leveraging Advanced Computational Algorithms for Roof Fall Rate Prediction and Risk Mitigation

AbstractThe utilization and consumption of coal in various nations have emphasized the pivotal role played by coal mines. However, aside from the substantial contribution of coal mines, miners, engineers, and craftsmen in this industry have long been exposed to numerous risks and financial losses resulting from roof collapses in underground coal mines. Hence, due to the heightened sensitivity surrounding this issue, the accurate and low-error forecasting and assessment of the roof fall rate (RFR) are deemed crucial and of utmost importance. Nonetheless, due to the intricate and uncertain inherent characteristics of the rock formations, assessing the RFR has encountered multiple challenges that cannot be precisely approximated through traditional methods. In this paper, algorithms such as the harmony search algorithm (HS) and the invasive weed Optimization algorithm (IWO) are harnessed to address the aforementioned challenges. To model the RFR, a total of 109 data points were used, incorporating input parameters such as primary roof support (PRSUP), depth of cover (D), coal mine roof rating (CMRR), mine height (MH), and intersection diagonal span (IS). For effective data analysis and model development, the dataset was split into two separate groups: one for training and the other for testing. Specifically, 80% of the data was used to build the model, while the remaining 20% was allocated for model evaluation and validation. Based on the outcomes of three statistical metrics R2, MSE, and RMSE, it is evident that the deployment of HS and IWO algorithms demonstrates high performance, with predicted values closely aligning with actual ones. Consequently, the utilization of intelligent algorithms in the field of rock engineering is positioned as a potent tool for researchers and engineers. In conclusion, a sensitivity analysis is carried out with the help of the @RISK software as a means of ranking the influence that the input parameters have on the output of the model. Its results indicate that among different parameters, the CMRR parameter with a sensitivity degree of 0.11 has the most impact on the model, even with the smallest change in this parameter, a significant change is made in the model output.

Study of Sleep Quality in Geopathic Stresses Areas and Efficacy of Enviromat in Improving the same- A Quantitative Study

A good night's sleep is essential for maintaining a healthy body and mind, as our body cells repair themselves during sleep. However, various factors can disturb our sleep, and Geopathic Stress is considered one of the contributing reasons. Geopathic Stress refers to the disturbance of natural energy flows, primarily caused by geological features such as underground water veins, mineral deposits, and fault lines, which can lead to disruptions in health. So, we aim to investigate the impact of Geopathic Stress on sleep quality and the efficacy of Enviromat as a potential solution. In this study, a total of 22 subjects were screened and recruited as per the inclusion and exclusion criteria. The research began with a literature review of relevant studies to identify the effects of Geopathic Stress on sleep quality. After reviewing the relevant research studies, a protocol was formed and presented to the Institutional Ethics Committee for approval, at All India Institute of Medical Sciences, New Delhi. Once the protocol was approved, Geopathic Stress zones were identified in the Sleep lab, where subjects slept on the beds in these zones. Subsequently, the Enviromat was evaluated for its efficacy to mitigate the harmful effects of Geopathic Stress on sleep quality. Complete data of 20 subjects was recorded and analysed with and without Enviromat with a gap of 10 days between two readings. The results indicated that sleep quality improved significantly (from 80.78 ± 7.83 to 87.08 ± 5.70; p-value = 0.0021) in most subjects when the Enviromat was used, suggesting its potential effectiveness in counteracting the negative effects of Geopathic Stress on sleep. These findings provide valuable insights into the relationship between Geopathic Stress and sleep and highlight the Enviromat as a promising intervention.