Underground Mining Operations Research Articles

Herramientas de Gestión para la Optimización del Minado Subterráneo

The objective of this research work was to optimize productivity and reduce costs in mechanized underground mining operations; for which management tools such as TPM (Total Productive Maintenance) were applied, which made it possible to ensure the expected reliability of the equipment and Management Indicators (KPIs), contributing to greater effectiveness in operations and statistical tools to improve quality, Pareto charts and Ishikawa diagrams. A descriptive methodology consisting of the daily collection of data contained in the mine operations records, to analyze it and identify opportunities for improvement in each process, thus determining unproductive delays in drilling, ore cleaning and hauling. Among the results, it was identified that the availability of the H 357 drilling equipment had an increase of 6.80% after implementing management tools. It was also evident that productivity increased considerably in the effective working time of the Scoop measured in tons/hour, thanks to the implementation of TPM, from 79.90 to 85. Ultimately, the application of management tools allowed a philosophical change within the organization, guiding a more effective management of operations of the mining company.

Comparative analysis of the influence of different shapes of shaft sections on dust transportation

Large amounts of dust are generated during digging operations in underground mines, and the transportation of dust is affected by the shape of the roadway section. In order to know the dust transportation law of different cross-section shapes when digging. Fluent software was used to simulate the distribution of wind flow field, dust transportation trajectory, and dust quality concentration in roadways with semicircular arch, three-centered arch, rectangle and trapezium, and then analyze and compare the influence of four cross-section shapes on dust transportation, and use gray correlation analysis to investigate the correlation between the time needed to reduce the dust quality concentration of the roadway to the safe value and the ventilation air volume and air supply distance. The results of the study show that the wind speed in the roadway is in the following order from high to low: rectangle > trapezium > three-centered arch > semicircular arch. Dust particles of each size rubbed each other after blasting, and there were fewer dust particles with larger sizes in the three-centered arch roadway. Both the air supply distance and ventilation air volume impact the dust removal effect; when the air supply distances are 5 m and 10 m, the three-centered arch has a better dust removal effect; when the air supply distances are 15 m and 20 m, the effect is better in the rectangular roadway and trapezoidal roadway; and when the ventilation air volume is increased, it is the three-centered arch. Through the gray correlation analysis, it can be seen that in order to improve the construction environment in the roadway after blasting, the rectangular section can be chosen when considering the air supply distance, and the three-centered arch can be chosen when considering the ventilation air volume.

Formation of Methane Hazards During Underground Coal Production in the Longwall Area Ventilated by System Y

Abstract The article addresses a critical and timely issue: improving safety in underground coal mining. The primary objective of the paper was to develop a research methodology based on modelling studies to identify and assess the state of methane hazards during mining operations. To achieve this, structural modelling of the physical and chemical phenomena occurring in mining regions was conducted using Computational Fluid Dynamics. The core research was performed using the finite volume method on a real longwall exploitation site ventilated by a Y-system. This approach enabled the determination of methane and oxygen concentration distributions in the mining region and goafs, treated as a porous and permeable medium. Based on these findings, potential fire and/or methane explosion hazard zones were identified in the goaf. The model test results underwent a validation process, comparing them with actual measurements. The determined errors were within an acceptable range, confirming the accuracy of the developed model of the mining region and the phenomena within it. Furthermore, the model was used to predict the locations of zones at risk of fire and/or methane explosion in the goafs, particularly in areas with potentially increased gas emissions. The results clearly demonstrate the significant potential of using model studies to diagnose and forecast methane hazards in underground mining operations. Identifying these potential danger zones allows for the implementation of preventive measures to reduce the likelihood of dangerous incidents.

A multiphysics simulator for stope-coupled heat exchanger operation in deep underground mines

The ever-increasing mine depth offers unprecedented opportunities to access high-grade geothermal resources. By pre-installing pipeline systems in mined-out cavities before waste tailings placement, the stope-coupled heat exchanger (SCHE) has drawn growing attention for its superior socio-economic advantages. However, despite the extensive focus on energy efficiency, the system stability during heat production has been typically overlooked. This study therefore introduces a novel high-fidelity simulator for replicating practical SCHE operation. By embedding non-isothermal pipe flow into an evolutive thermo-poromechanics framework for cemented tailings, the outlet water temperature and multiphysics backfill response in diverse production settings are meticulously studied. Our calculations reveal for the first time that circulating chill fluid within mine backfill can substantially alleviate pressure development, suggesting enhanced system stability with heat-exchanger implementation. We also demonstrate that albeit targeting higher-grade geothermal resources, prioritizing cold-season operation, and pre-charging heat exchangers with production delays could spur heat productivity, the companion thermal pressure generation might still impose significant overloading risks. Conversely, while fast circulation would diminish the end-utilization temperature, the rapid heat removal could indeed facilitate superior efficiency and stability performance for the geothermal system. We believe these new findings hold critical implications for better positioning SCHE as a safely sustainable pathway towards hybrid utilization of deep resources.

Modeling the impact of surface mining operations on the condition of the underlying rock mass when planning underground mining operations using the CAE Fidesys software suite

Modeling the impact of surface mining operations on the condition of the underlying rock mass when planning underground mining operations using the CAE Fidesys software suite

The effect of stope size and cut-off grade on the design and scheduling of an underground mining operation in the presence of a pre-concentration system

ABSTRACT Stope layout optimisation is considered one of the main steps in the design and strategic planning of underground mining operations. This paper investigates the influence of stope size and cut-off grade in an underground sublevel stoping operation in the presence of a preconcentration system using a newly developed mathematical optimisation model. The utilisation of a bulk ore sorting system, its effects on the resource utilisation, and the final discounted cash flow of a case study are presented. Results show that incorporating a bulk sorting system to a sublevel stoping operation can significantly increase the viability of a deposit.

Study on dynamic mechanical properties and microscopic damage mechanisms of granite after dynamic triaxial compression and thermal treatment

As underground mining operations gradually extend deeper, the conditions for orebody occurrence become increasingly complex, and various geological disasters occur frequently. Rock masses are prone to different degrees and types of damage, making it impractical to continue using intact rock as a reference. To study the dynamic mechanical properties of damaged rock under actual conditions, this study subjected granite samples to impact and high-temperature damage. Detailed observations were made of the samples' surface morphology and microstructure before and after damage, and the patterns of damage changes were investigated. Subsequently, uniaxial compression tests at different loading rates were conducted on the damaged samples. By calculating the loading rate effect sensitivity, it was found that as the damage increased, the rate effect gradually diminished. In addition, this study also summarized the influence of damage and loading rate on the macroscopic failure characteristics of the samples. The novelty of this study lies in focusing on damaged rock, which more closely resembles the actual rock conditions encountered in most underground mining operations today. This research can provide a reference for stability assessment and safe construction in deep mining rock engineering and offers important insights into the feasibility of non-explosive extraction of damaged rock.

Comprehensive review of unmanned aerial vehicle application to safety mining management

The increasing interest of users in unmanned aerial vehicle (UAV) technology has developed new fields of application for it. Presently, UAVs are working in so many areas and the mining industry has shown grown interest in the use of UAVs for routine operations in surface, underground mines, and mine waste dumps. In this paper, a thorough review has been performed on the application of UAVs in mine safety management. Systematic reviews were conducted to summarize the results of over 60 papers published during the 2010-2021 period. The study offers a review of the most common applications involving mine safety, the styles of flying control, and the UAV types exploited. The paper also contributes to the identification of prevalent data acquired by sensors and points out the most popular processing techniques of aerial imagery. The obtained results revealed that UAVs are used at mining sites for safety purposes including mine surface displacements, stability monitoring, working environment, coal fire identification, drill and blast, and mine waste dump operations. This research hopes to provide a technical reference, expanding the knowledge and recognition of UAV monitoring to manage mine safety, as well as an assessment of applications in mining activities.

Research on Path Planning of a Mining Inspection Robot in an Unstructured Environment Based on an Improved Rapidly Exploring Random Tree Algorithm

To ensure the safe production of mines, the intelligent trend of underground mining operations is gradually advancing. However, the operational environment of subterranean mining is intricate, making the conventional path-planning algorithm used by mining inspection robots frequently inadequate for real requirements. To safeguard the mining inspection robot, targeting the problem of low search efficiency and path redundancy in the path planning of the existing rapidly exploring random tree (RRT) algorithm in the narrow and complex unstructured environment, a path-planning algorithm combining improved RRT and a probabilistic road map (PRM) is proposed. Initially, the target area is efficiently searched according to the fan-shaped goal orientation strategy and the adaptive step size expansion strategy. Subsequently, the PRM algorithm and the improved RRT algorithm are combined to reduce the redundant points of the planning path. Ultimately, considering the kinematics of the vehicle, the path is optimized by the third-order Bessel curve. The experimental simulation results show that the proposed path-planning algorithm has a higher success rate, smoother path, and shorter path length than other algorithms in complex underground mining environments, which proves the effectiveness of the proposed algorithm.

Reference architecture design and evaluation for digitalization of underground mining

Digitalization of underground mining operations requires interaction and interoperability between multiple stakeholders and their technical systems. A reference architecture (RA) facilitating design of multi-stakeholder digital solutions for underground mining would be valuable design knowledge for mining industry digitalization activities and would facilitate the design of concrete architectures to the underground mining context. The main contribution of this work is RA design, which is missing in the current research literature. The RA has empirical foundation on the implementation architectures of two prototypes, which were demonstrated and evaluated in an underground mining environment. The prototypes were evaluated based on several design science research evaluation criteria (feasibility, efficiency, robustness, operability) for fulfilling architectural concerns of related stakeholders. Digital Twin-based modeling, MQTT-based messaging, high accuracy location monitoring of vehicles with Lidars, reliable communication with 5G SA network, and utilization of safety zones and safety messaging for enabling emergency stops were identified as important aspects for RA design. Digital Twin (DT)-based data models focusing on the modeling of mining site, moving vehicles, communication data, and related equipment for the underground mining context may be considered as an additional contribution of our study.

Integrating robotic systems in underground roof support machine

Traditionally, the roof bolting process is performed manually by skilled workers, which is time-consuming and labor-intensive. This often exposes human operators to several risks. Bolt installation in underground coal mining operations involves moving and manipulating heavy tools quickly while ensuring the safety of the area. Hence, humans must relocate from an active mining site to a more secure place where the operator can control and monitor the roof bolting process. This study explores the integration of a six-axis robotic arm and other specialized novel technologies into an existing roof bolter machine to automate the roof bolting module, therefore replacing human duties. Owing to the harsh mining conditions in underground coal mines, the integration of robotic systems requires proper planning to ensure reliable and safe operations. The methodology adopted for integrating the robotic system in this study may be regarded as a conceptual framework for the automation of underground mining roof bolting operations. This study highlights certain specifications that should be considered when automating underground mining machines. The results showed that a robotic arm that performs human tasks during roof bolting operations can be successfully integrated into a roof bolting module by establishing a robust communication network to facilitate seamless interaction between different hydraulic, mechanical, and electronic components.

Effect of 3D printed skeleton shapes on strength behavior, stress evolution and microstructural response of cement-based tailings backfills

The inherent brittle behavior of cement-based tail backfill (CTB) poses some challenges that can significantly impact the safety and effectiveness of underground mining operations. Due to its propensity for abrupt and catastrophic failure without considerable deformation, CTB can endanger both the structural solidity of mined-out cavities and workers’ security. Hence, implementing appropriate strategies is critical to mitigate the risks associated with the brittle nature of CTB. An experiment investigation was commenced to consider the influence of diverse 3D printed polymer reinforcement geometries - specifically, hexagon, staggered quadrilateral, and rhomboid shapes - on strength behavior, stress evolution, and microstructural response of CTB via peak compression strength test plus scanning electron microscope observations. Lab findings specified a decrease in fill strength upon adding these polymer reinforcements. Specifically, the N-3D-PP-reinforced CTB exhibited a strength of 0.61 MPa. In comparison, the reinforced samples showed lower strengths of 0.39 MPa for the hexagon shape, 0.44 MPa for the staggered quadrilateral shape, and 0.45 MPa for the rhomboid shape. The toughness of CTB incorporating 3D-PP was higher than that of N-3D-PP ones. The optimal shape for an ideal toughness was the rhomboid shape, with a value of 58.06 KJ.m−3. N-3D-PP-reinforced CTB specimens exhibited a semi-brittle behavior, while 3D-PP-reinforced CTBs displayed a more ductile response with high total and dissipative energies. Cracks in N-3D-PP reinforced CTB were tensile, and mainly a combination of tensile and shear in 3D-PP reinforced CTB. Despite enhanced toughness, the presence of pores, the poor interfacial bonding between the CTB matrix and the 3D-PP, the low volume of polymer reinforcement, and the potential disruption of cement particle packing compromised the CTB’s overall strength. This research highlights the potential of 3D-printed reinforcements in transforming the landscape of mining backfill technology. The findings pave the way for the widespread adoption of 3D-printed polymer-reinforced CTB in metalliferous mines, promoting safer, more productive, and, ultimately, more profitable underground mining operations.

Bridging depths and data in mines: 5G-based point cloud mapping in unstructured environments

Underground mines pose significant challenges, including hazardous working conditions, limited access, and the need to ensure the safety of human workers. Digital transformation through the integration of modern technologies is essential to mitigate these challenges and enhance the overall safety and efficiency of mining operations. This paper addresses the pressing need for 5G connectivity for the digital transformation of underground mines and demonstrates its application through a live 3D point cloud mapping by a mobile robot. The results of the experiments conducted to validate the network’s performance for such a use-case are presented. The first experiment involved testing the latency of the network over a test drift at various loads. The second experiment involved mapping the drift and streaming the 3D point cloud map of the drift over the 5G network. These initial experiments emphasize the potential of the 5G-enabled automation in underground mines and holds promise in digitalizing underground mining operations.

Expert Elicitation for the Resilient Design and Optimisation of Ultra-long Ore Passes for Deep Mass Mining

Extension of ore pass length has become increasingly critical for optimising energy-efficient underground mining operations. Long and ultra-long ore passes, spanning from 300 to 700 m, can significantly improve the functionality and viability of underground mass mining operations though suboptimal performance has an extremely adverse impact on production. The public domain lacks substantial information regarding the primary engineering, geological, and geotechnical risks and challenges associated with the design, implementation, operation, and maintenance of such long ore passes. Therefore, the aggregation of past experiences and the insights of experts assume paramount significance. An innovative methodology is introduced to address this evident data deficiency and to establish comprehensive guidelines for the resilient design of such lengthy ore passes — combining gap analysis with expert elicitation techniques. This equips design engineers with the necessary tools to formulate and adapt strategies for assessing the numerous challenges and uncertainties that invariably accompany their projects. Expert elicitation techniques are summarised, and a gap analysis is conducted with subject matter experts, from various countries, collating their extensive ore pass design experience, to create a comprehensive list of effective parameters and key risks that must be considered. Quantitative analysis of the survey results enabled the identification and ranking of the numerous factors affecting the design, operation, and maintenance of long and ultra-long ore passes and highlights the complex technical challenges (substantial damage from rock particle impact, increased dynamic mining stresses leading to failure, air-blasts and back blasts, dust, preferential flow, turbulent and dynamic material flow) that are uncommon in shorter ore passes. Additionally, increasing length heightens the probability of intersecting weak rock or discontinuities, leading to a higher risk of structural failure and instabilities. Faulting, folding, and large-scale structures are also critical geological factors to be considered in the design of such structures. The key geotechnical factor is also the rock type surrounding the pass. Experts highlighted the lack of clear guidelines for decision-making, resilient design, and construction so this work suggests future investigations to determine the complex interaction between the effective parameters, using approaches like the rock engineering system, discovery of cascading hazards, and optimal controls.

Analytical solution for estimating the minimum required strength of sill mat by considering failure due to rock wall closure

Underhand cut-and-fill mining has been widely used in underground mining operations, especially when the rock mass or orebody is of poor quality or prone to rockburst due to high stress. In such cases, mining workers should carry out all production activities under the cemented backfill roof or sill mat instead of a highly fractured and unstable rock roof or a strong rock roof with a high potential of rockburst. Therefore, the stability and required strength of the sill mat are critical issues for mining engineers. In 1991, Mitchell considered that sill mat could fail by caving, sliding, rotation, and flexure. Mitchell also proposed an analytical solution to determine the minimum required strength of the sill mat for each type of failure based on two stiff or immobile rock walls. However, recent publications using numerical modeling and field measurements indicate that the compressive stresses in the sill mat induced by rock wall closure due to a stope excavation beneath the sill mat can be significant. It is thus highly necessary to investigate the required strength of the sill mat by considering rock wall closure. In this study, the crushing failure of sill mat due to rock wall closure generated by underground excavation and a new failure mode called "crushing and caving" is revealed by numerical modeling. An analytical solution corresponding to each failure mode is then developed to estimate the minimum required cohesion () of the sill mat. A criterion is also proposed to determine if the sill mat fails by crushing or crushing-and-caving failure. The proposed analytical solution does not involve any correction coefficients. The validity of the proposed analytical solution is demonstrated by numerical modeling. The proposed analytical solution can thus be employed to predict the of sill mat subjected to wall closure generated by underlying stope excavation.

Prediction of jumbo drill penetration rate in underground mines using various machine learning approaches and traditional models.

Estimating penetration rates of Jumbo drills is crucial for optimizing underground mining drilling processes, aiming to reduce costs and time. This study investigates various regression and machine learning methods, including Multilayer Perceptron (MLP), Support Vector Regression (SVR), and Random Forests (RF), to predict the penetration rates (ROP) using multivariate inputs such as operation parameters and rock mass characteristics. The Rock Mass Drillability Index (RDi), incorporating both intact rock properties and structural parameters, was utilized to characterize the rock mass. The dataset was split into 80% for training and 20% for testing. Performance metrics including correlation coefficient (R2), variance accounted for (VAF), mean absolute error (MAE), mean absolute percentage error (MAPE), and root mean square error (RMSE) were calculated for each method to evaluate the accuracy of the predictions. SVR exhibited the best prediction performance for ROP, achieving the highest R2, lowest RMSE, MAE, and MAPE, as well as the largest VAF values of 0.94, 0.15, 0.11, 4.84, and 94.13 during training, and 0.91, 0.19, 0.13, 6.02, and 91.11 during testing, respectively. With this high accuracy, we conclude that the proposed machine learning algorithms are valuable and efficient predictors for estimating jumbo drill penetration rates in underground mining operations.

Research on Pressure Relief and Anti-impact Technology for Segmental Hydraulic Fracturing in Directional Long Borehole in Roof

After large-scale underground mining operations in coal mines, the stress of the overlying strata above the goaf is transferred to the surrounding support areas, creating support pressures. These pressures can easily trigger dynamic disasters such as gas outbursts and roof collapses, seriously threatening mine safety and production. To ensure the safety of underground mining operations, directional long borehole segment hydraulic fracturing technology was used in the roof strata of the 2305 comprehensive caving working face of Cuijiagou Coal Mine in Shaanxi Province to conduct experimental research on the technology of directional long borehole segment fracturing for pressure relief and anti-impact. The hydraulic fracturing of the roof’s directional long borehole reduced the stress peak coefficient of the coal body in front of the working face (K≈2.9), blocked the propagation of mining stress and high stress in the goaf to the mining roadway, reduced the deformation of the mining roadway, and reduced the average working resistance of the working face support by 22% compared to the working face without any measures. The effective reduction of the length of the hanging roof, the improvement of the support resistance, and timely roof collapse during the working face mining period helped ensure the initial pressure did not form a strong impact. The initial pressure interval of the thick hard roof calculated theoretically was shortened by 53%, and the periodic pressure interval during normal mining was reduced by 27% compared with the 2303 working face under the same geological conditions. The experimental results show that the coverage of the directional long hole on the roof is extensive, with the utilization rate of segmented hydraulic fracturing wells reaching up to 80%. This technology effectively diminishes the strength of the roof above the coal seam on a large scale, thereby reducing the periodic pressure interval and intensity. As a result, it prevents the impact caused by the hanging roof during the mining period of the working face, ensuring a safe working environment for underground workers and facilitating the safe and efficient progress of mining operations.

Research on the Intelligent System Architecture and Control Strategy of Mining Robot Crowds

Despite the pressure of carbon emissions and clean energy, coal remains the economic backbone of many developing countries due to its abundant resources and widespread distribution. The stable supply of coal is also vital for the global economy and remains irreplaceable in the future global energy structure. China has been a major contributor to annual coal output, accounting for nearly 50% worldwide since 2014. However, despite implementing intelligent coal mining technology, China’s coal mining industry still employs over 1.5 million underground miners, posing significant safety risks associated with underground mining operations. Therefore, the introduction of coal mining robots in underground mines is an urgently needed scientific and technological solution for upgrading China’s and even the world’s coal energy industry. The working face needs a shearer, hydraulic support, a scraper conveyor, and other equipment for coordination. The deep integration of intelligent technology with factors such as “humans, machines, the environment, and management” in the workplace is the core content of intelligent coal mines. This paper puts forward an advanced framework for robot technology systems in coal mining, including single robots, robotized equipment, robot crowds, and unmanned systems. The framework clarifies the common key technologies of coal mining robot research and development and the cross-integration with new technologies such as 5G, the industrial internet, big data, artificial intelligence, and digital twins to improve the autonomous and intelligent application of coal mining robots. By establishing a scientific and complete standard system for coal mining robots, we aim to achieve the customized research and development and standardized production of various types of robot. A specific analysis is conducted on the research progress of common key technologies such as the explosion-proof design, mechanical system innovation, power drive, intelligent sensing, positioning and navigation, and underground communication of coal mining robots. The current research and application status of various types of coal mining robots in China are summarized. A new direction for future coal mining robot research and development is proposed. Robotic mining systems should be promoted to enhance the overall intelligence level and efficiency of mining equipment. To develop human–machine environment-integrated robots to improve the autonomy and collaboration level of coal mining robots, the digital twinning of the entire mine robot system should be accelerated; the normalized operation level of coal mine robots should be improved; research on coal mining robots, shield support robots, and transportation robots should be performed; intelligence should be achieved in fully mechanized mining faces; and equipment shield support for fully mechanized mining faces should be provided. The practical process of implementing coal mining robotization is summarized in this paper, and the technical and engineering feasibility of the coal mining machine population is verified.

Influence of mining on vegetation in semi-arid areas of western China based on the coupling of above ground and below ground – A case study of Daliuta coalfield

Underground mining operations are known to result in extensive surface subsidence, introducing a multitude of disturbances to surface vegetation, with particularly severe environmental impacts in the fragile ecosystems of arid and semi-arid regions. This study focuses on the Daliuta mining area located in semi-arid zones, selecting four distinct areas for data analysis. Areas A, B, and C fall within the mining perimeter and have all been affected by mining-related disturbances. Following coal extraction, Areas A and B underwent artificial rehabilitation measures, including fracture infilling and sea buckthorn plantation; Area C was left in its natural state without any artificial interference. Area D, unaffected by mining activities, was designated as the control group. The research utilized 60 Landsat satellite images spanning from 1988 to 2022. Employing the Normalized Difference Vegetation Index (NDVI) and the Fractional Vegetation Cover (FVC), the study classified the experimental zone’s vegetation cover and degradation into six levels, ranging from low to high. By comparing the average vegetation cover over an extended period, changes across different vegetation cover levels, and the degree of vegetation degradation before and after mining, the study assessed the impact of underground mining on surface vegetation. The conclusions drawn are as follows: Mining operations caused significant damage to the vegetation in Areas A and B, yet artificial restoration measures notably improved the vegetation quality, with an overcompensation effect observed in Area A, suggesting the potential for ecological restoration efforts to create a vegetative environment that exceeds its original condition in the long term. Mining activities also induced continuous ecological adverse effects in Area C, but the natural regeneration process progressively restored the vegetation to pre-mining levels over time. Based on these findings, the study reveals the spatiotemporal patterns of vegetation damage and recovery across different mining periods and land reclamation stages. It proposes a restoration strategy for mine areas in semi-arid regions that prioritizes natural regeneration supported by artificial guidance. This work provides valuable insights and guidance for assessing the impact of underground coal mining on surface vegetation in semi-arid areas, as well as for the rehabilitation and ecological reconstruction of mine areas, emphasizing the necessity and urgency of conducting environmental assessments and implementing restoration measures.

Комплексная оценка геоэкологических рисков при ведении открытых и подземных горных работ

Introduction. Geo-ecological risk is the probability of adverse events leading to a violation of the stability of the existing ecological system or the natural and technical geo-system “rock mass – technology – mining”, formed as a result of mining activities. The main elements of geo-ecological risk in mining are dangerous geological (landslides, rock collapses, suffusion-erosion processes, karst, etc.) and hydrogeological processes. The purpose of the research. Development of a method for integrated assessment and management of geo-ecological risks in open-pit and underground mining operations. Methodology. The paper calculates the geo-ecological risk in relation to each technological process. At the same time, the ranking of the possibility of a negative process in mining activities is determined on the basis of an expert approach, taking into account the specifics of mining and technological operations. Statistical data and expert assessments formed the basis for determining the quantitative values of geo-ecological risks in mining operations. Results and discussion. The obtained quantitative values of geo-ecological risks indicate that a management system is needed. The developed geo-ecological risk management system makes it possible to conduct a comprehensive assessment of them in the conditions of mining and mining and construction production and, based on forecast calculations, determine the distribution zones of the most dangerous processes in the “rock mass – technology – mining” system. Conclusion. Research has been conducted on the formation of a comprehensive assessment of geo-ecological risks, as well as their forecasting during open-pit and underground mining operations. It is determined that the geo-ecological risk in open-pit mining consists of the risk of alienation and degradation of soil, the risk of pollutants into the atmospheric air, the risk of pollution and depletion of the water basin, and in underground mining – from the risk of atmospheric pollution of the working area, the risk of changes in the groundwater regime and the risk of geo-mechanical transformations of the rock mass.