Underground Mining Method Research Articles

Rock Slope Instability Mechanism Induced by Repeated Mining in Mountain Mining Areas

When mineral resources are extracted using underground mining methods in hilly regions, landslides or slope failures can be induced frequently. In this study, slope collapse disasters in mountain mining areas were analyzed. The model test and numerical simulation of the slope impacted by repeated mining were carried out. The crack evolution and failure process were analyzed to reveal the instability mechanism. The results show that the rock mass would topple to the inside of the slope first, when the subsidence of overlying rock was induced by the mining of the upper coal seam. When repeated mining was performed in the lower coal seam, the mining induced macro-cracks that could connect with natural fissures, inducing the outward displacement of the slope. Then, the rock mass at the foot of the slope has to bear the upper load, which is also squeezed out by the collapsed rock mass, forming the potential slip zone. Finally, the instability is caused by the shear slip of the slope toe rock mass. Therefore, the instability evolution of the slope under underground repeated mining disturbance can be divided into four stages as follows: roof caving and overlaying rock subsidence, joint rock toppling, fracture penetration, and slope toe shearing and slope slipping.

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.

Reducing mining tailings and operational dilution: a new application of the room-and-pillar mining method

The selection of an underground mining method stems from a multivariate analysis that considers geomechanical, geological, economic, and operational parameters. Even after identifying the most compatible method, there is no assurance that the mining company will achieve the best performance. The geological complexity of some deposits requires adaptations of methods described in the literature to obtain more selectivity and reduce mining waste. There are some studies on geometry of underground structures, but a methodology that describes an adaptation of a room-and-pillar mining method for ore bodies with down-dip varying from 20° to 25° is novel. The present work aimed to reduce dilution by adapting the traditional room-and-pillar mining method (TRP) to inclined ore bodies. This new method is entitled short-hole room-and-pillar (SHRP). The equations that measure the dilution are defined according to the geometry of stopes and openings. The results comprise comparative analyses of the operational and planned dilutions to measure the performance of the SHRP method. The average operating dilution of the SHRP method was more than five times lower than the planned dilution according to the TRP method. Low operational dilution indicates high selectivity of the method and its potential to reduce underground mining tailings.

Dynamic correlation between surface carbon response and underlying emissions from spontaneous combustion goaf: field study of an abandoned coal mine

Abandoned coal mine goaf is affected by air leakages and prone to spontaneous combustion, resulting in environmental pollution and geological disasters. Haizhou Open-pit Mine adopts both underground and open-pit mining methods. During the long-term mining process, the original stable stratum structure is constantly destroyed, and the slope slides, increasing cracks and severe air leakage around the goaf and roadway. The spontaneous combustion of coal is particularly prominent after the mine shut down. At present, there is no suitable indirect monitoring method to effectively explore the spontaneous combustion area in goaf. The study developed an all-weather monitoring plan and conducted multi-point continuous long-term measurements of the spontaneous combustion state in one abandoned coal mine goaf located in the eastern part of the Haizhou Open-pit Mine. We evaluated the dynamic correlation between surface CO2 flux (SCF) and changes in the underground fire areas, determined the scope and evolution trend of the fire areas, and identified the distribution and change laws of SCF. The results show a significant positive correlation between SCF and soil temperature; moreover, the SCF value was found to reflect the CO2 emission intensity of the goaf. The high SCF in the test area showed month-wise expansion and increase, while the CO2 emission gradually increased monthly, and the calculated annual total emission was approximately 7017 t. Hence, the study can further provide guidance for the monitoring of spontaneous combustion in shallow coal seams, goaf and the assessment of CO2 emissions from underground coal fires through the on-site monitoring and analysis results.

Proposed formulas for pillar stress estimation in a regular room-and-pillar pattern

Room-and-pillar mining is one of the oldest and most widely employed underground mining methods worldwide, while in recent years it has also been used for civil engineering projects and applications. The pillar design process is quite straightforward, requiring the assessment of two key elements, namely the pillar's strength and the anticipated loading imposed on it. Lots of research work has been elaborated for the estimation of pillars' strength and the main parameters associated with it, while, on the other hand, in terms of the loading the Tributary Area Theory (TAT) has been traditionally and successfully used as the dominant methodology to assess the post-mining pillar induced stresses. This paper focuses primarily on decoding the pillar loading regime by analyzing the identifying the stresses imposed to them through the use of modern computational tools offered by 2D and 3D numerical analyses, over a series of pillars' type (square, ribs), configurations and initial virgin stress fields. This allows for the development of a benchmarking framework that showcase the differences in the stress conditions and reveal the over-conservative behavior of TAT. More importantly though, it allowed for the expression of two (2) general analytical formulae for the direct estimation of the average vertical elastic stresses on pillars, both for the case of rib & square pillars layout; the most typical patterns applied in this method. They aim at providing an easy to use and more accurate estimation of the pillar stress - as compared to TAT - in alignment with the results obtained from numerical analyses. Thus, with the proposed formulas, the time-consuming numerical process needed for preliminary pillars' dimensioning is tackled in a swift and effective manner.

A Causal Analysis of the Influential Criteria in Underground Mining Method Selection

A Causal Analysis of the Influential Criteria in Underground Mining Method Selection

Heuristic control of power consumption by up to 1000 V electrical loads at mining enterprises

Purpose. To develop a method for synthesizing the structure and algorithm of the system for automated control of power consumption by up to 1000 V electrical receivers at mining enterprises with iron ore underground mining methods. This enables direct control of the load connection to the industrial power grid to ensure minimum power costs depending on its cost per day ahead. Methodology. The problem of controlling power consumption of electrical receivers at iron ore underground mines is formalized as a binary form of mixed integer programming. To solve it, a binary implementation of the heuristic genetic algorithm is used. The mathematical modeling method analyzes the impact of genetic algorithm settings, such as the number of phenotypes in the population, the number of elite phenotypes that pass unchanged to the next generation, and the method of phenotype crossover on its quality. Findings. As a result of the research, it is found that the most effective way to control the process of power consumption based on an evolutionary genetic algorithm is to use the Laplace crossover function and keep the percentage of elite phenotypes in the population at 10 %. Moreover, at the smallest population size, the best accuracy is observed when using the Laplace function, while at one- and two-point crossover functions, it worsens, but not significantly (no more than 0.2 %). However, as the number of elite phenotypes increases, the duration of the evolutionary search in the control process is reduced by almost a factor of two in the case of one- and two-point crossovers. Originality. For the first time, the structure of a heuristic system for automated control of power consumption by underground electrical receivers with a supply voltage of up to 1000 V at iron ore underground mines has been developed on the basis of an evolutionary genetic algorithm. Depending on the designed volumes of ore production and the daily power cost per day, this allows determining the optimal power load schedule of underground distribution substations in advance, which, subject to the accepted limits on hourly and daily power, minimizes the cost of purchasing power, and thus reduces the cost of the final product. Practical value. The architecture of a heuristic system for controlling power consumption by electrical receivers with a voltage of up to 1000 V based on an evolutionary genetic algorithm is developed and recommended when optimizing the power load schedule of transformer substations of mining and metallurgical enterprises, in particular, of iron ore underground mines operating in this voltage class.

Application of Z-numbers theory to study the influencing criteria in underground mining method selection

The purpose of this study was to prioritize and determine the importance of effective factors in selecting the appropriate underground mining method (UMM). This study also evaluates the uncertainty and various life-threatening/mortal and financial risks associated with these criteria. In the present study, 43 influencing criteria for underground mining method selection (UMMS) were identified and classified into two main groups. Then, a model was proposed by employing the Z-numbers theory (Z-NT). A total of 25 specialists from around the world were approved for the study, and 10 of them returned questionnaires. By applying Z-numbers and using the proposed model, the uncertainty of the experts' opinions was highly reduced. Finally, the model was applied to the Angouran Lead and Zinc (L&Z) Mine in the northwest of Iran for verification. The findings indicate that within every group of criteria, the weighting of factors determined in this study is in good harmony with the key factors considered in the selection of mining method at Angouran Mine. Also, based on the technical reports of Angouran Mine, the mine is facing various risks. Therefore, this research has also been examined from a risk assessment perspective, and the findings of the proposed model have been put against the factors influencing the various risks in the Angouran Mine. The results show that the factors that have the highest weight in risk proneness are stope collapse, underground water inflow into the stope, and machines’ downtime.

Optimization of mining methods for deep orebody of large phosphate mines

Introduction: Taking Yunnan Phosphate Group Co., Ltd. Kunyang Phosphate Mine No. 2 as the engineering background, this study aims to explore mining methods for deep ore bodies in phosphorus mines. Three mining schemes, namely open-pit mining, open-pit deep concave mining, and underground mining, were carefully selected for optimization. This article thoroughly analyzes the three schemes from various perspectives, including technical, economic, safety, and other aspects.Methods: The assessment of these aspects was conducted using the entropy weighted TOPSIS method. The technical aspects focused on evaluating the mining methods employed in each scheme. The economic aspects considered factors such as initial investment, resource recovery rate, phosphate content, production scale, infrastructure, and mining costs. Safety aspects took into account transportation safety and production safety. Additionally, the analysis considered environmental impact as one of the key factors. In total, 10 indicators were quantified to provide a comprehensive evaluation. To assess the schemes, the positive and negative ideal distances (Di+, Di−) and the relative proximity (Ci) for open-pit mining, open-pit deep concave mining, and open-pit to underground mining were calculated. These calculations helped to determine the relative performance of each scheme.Results: The relative closeness values (Ci) for Scheme 1, Scheme 2, and Scheme 3 are determined as 1.00, 0.09, and 0.68, respectively.The evaluation results indicate that the relative closeness (Ci) for open-pit mining in Scheme 1 is 1.00, for open-pit deep concave mining in Scheme 2 is 0.09, and for underground mining in Scheme 3 is 0.68. Through comparison and analysis of these results, it can be concluded that open-pit mining is the most optimal method. However, considering the fact that the open-pit portion of Kunyang Phosphate Mine No. 2 has already been extensively mined, the study recommends underground mining as the best mining plan for the phosphate mine.Discussion: By applying the entropy weight TOPSIS method to underground mining, this study overcomes the challenge of transitioning from qualitative to quantitative analysis for selecting mining methods. The mathematical approach enables the presentation of optimal mining techniques in a more precise manner. Through comparison of relative closeness, an optimal solution can be selected. This method holds significant value not only for selecting suitable mining methods for phosphorus mines but also for choosing optimal solutions for underground mining methods, drainage, ventilation, and other relevant considerations.

Applying Nonnegative Matrix Factorization for Underground Mining Method Selection Based on Mining Projects' Historical Data

Applying Nonnegative Matrix Factorization for Underground Mining Method Selection Based on Mining Projects' Historical Data

Application of the FUZZY TOPSIS method for selecting an underground mining method

Selecting the underground mining method is one of the most difficult decisions any mining engineer makes when designing a new mine or opening new parts in an existing mine. The underground mining method selection depends on many mining-geological, technical and economic factors. The process of selecting a mine excavation method is a multi-criteria decision-making process since many factors are considered when selecting a mining method. The selection of the most suitable mining method is of great importance for each mine, and this is especially evident in the phase of preparation and excavation of the ore deposit and optimization of the total cost of excavation. This paper uses the Fuzzy TOPSIS method to select the underground mining method for metallic mineral resources as one of the most important multi-criteria decision-making methods. The methodology presented will enable the application of other fuzzy methods to solve problems related to the mining method selection.

Induced hydraulic fractures in underground block caving mines using an extended finite element method

Block caving has become an attractive underground rock mining method that requires effective preconditioning of the orebody to initiate the progressive rock collapse by its weight. Hydraulic fracturing is commonly used in cave mining as a preconditioning method to induce artificial fractures in the orebody rock mass. This paper presents the numerical model of hydraulic fracture propagation in underground caving mines. An extended finite element method based on phantom nodes is adopted to simulate the propagation of multiple fractures along arbitrary paths. A poroelastic constitutive model governs the behavior of orebody rock mass, while a cohesive zone model controls the hydraulic fracture propagation. The adopted method is validated against analytical solutions for penny-shaped hydraulic fracture. The stress shadowing effect on hydraulic fracturing is investigated using representative rock properties from the “El Teniente mine”, obtained by calibrating a hydraulic fracturing field test. Several analyses of multiple hydraulic fractures considering a sequential fracturing scheme are simulated to investigate the influence of in-situ stresses, fracture spacing, injection flow rate, and Young's modulus and permeability of the matrix. The numerical results show that small fracture spacing, in-situ stress, and rock permeability locally change the principal stress magnitude, resulting in a more extensive fracture propagation. Also, the injection of new fractures induces stress shadows that reinitiate the propagation of the previous ones. This behavior is reduced by increasing the fracture spacing and rock permeability. Finally, this paper provides insights into the main parameters that affect fracture extension, which can be used to optimize the preconditioning process of underground block caving mines.

Sublevel Shrinkage (SLSh) Mining—A State-of-the-art Review

Sublevel shrinkage (SLSh) is an underground mining method similar to sublevel caving (SLC) but with continuous backfilling from the top. It features a top-down mining sequence with production drifts orientated in a longitudinal or transverse way in the orebody. Fan drilling and blasting is done from the production drifts, from where the ore is then drawn. While drawing, backfill is introduced at the top and flows down by gravity, which supports the walls and prevents caving. In this contribution, a state-of-the-art literature review is performed using various sources. Four case studies show that SLSh could be a viable alternative for stoping (e.g. sublevel open stoping “SLOS” or longhole open stoping “LHOS”) and SLC in steeply dipping, moderately thick, tabular deposits. SLSh can be applied where caving must be prevented or caveability of the hangingwall rock mass is not provided due to rock mass properties or the geometry of the deposit. SLSh also proved to be an alternative to SLOS or LHOS when only small stope sizes would be possible due to geotechnical constraints. Critical points are dilution with backfill and the backfill handling infrastructure that must have a high capacity. Stability of this infrastructure is very important and must be monitored closely. Open points are the application in massive deposits and backfill supply and handling for mines with very high production.

Prediction of dilution in sublevel stoping through machine learning algorithms

One of the most used underground mining methods is open stope mining which involves extracting a large body of ore through drilling and blasting. The method offers plenty of advantages but it has some very important drawbacks, such as overbreak, wall instability and unplanned ore dilution. The research looks to test the efficiency of using machine learning algorithms to estimate the dilution in open stopes, some of the expected benefits are reduced time cost (compared to numerical analysis) and more accurate results (compared to empirical methods). The algorithms utilized are: random forest (RF), support vector machine (SVM) and k-nearest neighbors (KNN). The algorithms were trained and tested with 752 cases from several mines across the world. Three algorithms accomplished AUC scores over 0.850, which can be considered excellent results, but random forest achieved the most impressive results (precision score = 0.835, accuracy score = 0.804 AUC score = 0.942). From the obtained results it is possible to conclude that the machine learning algorithms can be used as trustworthy tools for the estimation of dilution, but some adjustments may be needed to increase the accuracy to specific mine sites.

Influence of underground mining activities on the topographic surface, case study of Nui Beo Coal Mine (Vietnam)

Purpose. Coal mining activities by underground mining method will disrupt the equilibrium of the surrounding rock mass. In underground mining, determining the influence zone of exploiting the longwall on the topographic surface is extremely important.Through analyzing the displacement and deformation of the rock mass when exploiting the longwall 21103 in Seam 11 at Nui Beo Coal Mine, the influence is to be determined of exploiting this longwall on the topographic surface in order to forecast the boundary of the influence zone that may affect the surface works, ensuring the safety of such works. Methodology. To achieve the research results, actual field survey methods, data analysis and numerical modeling methods are used in this article. Findings. Analysis of the results from the numerical model determined that the total height of the collapsed and cracked area when exploiting the longwall 21103 in Seam 11 is about 85 m. The subsidence to the ground is about 10 cm from the center of the subsidence area. The analysis results from the numerical model also show that the roof collapse angle is 69°, thereby determining the area of influence on the topographic surface in the range of 55 m. Results on the cross-sections show that the boundary of the influence of mining on the topographic surface is the closest section 6–6, which is about 12 m. The stability time of the collapsed rock mass is determined to be about 5 months. Originality. On the basis of UDEC (Universal Distinct Element Code) software, the authors have developed a simulation model for the mining process of the longwall 21103 in Seam 11. Analysis of the results from the model has shown the state of displacement and deformation of the surrounding rock mass. In this study, the numerical modeling method is applied to simulate the displacement of the longwall, which is consistent with the actual production of the underground mine. This enabled the authors to assess and identify the affected area with the required degree of reliability. Practical value. The research results of the paper are used as a basis for implementation in actual production at Nui Beo Coal Mine. On the basis of the analysis of the surrounding rock mass displacements and deformations, when exploiting the longwall 21103 in Seam 11 at Nui Beo Coal Mine, the affected boundary of the topographic surface has been determined. At the same time, the stability time of the collapsed rock mass is also calculated. So, this is also the basis for Nui Beo Coal Mine to plan construction works on the site outside the determined affected areas to ensure the safety of such works.

A Field Study Implementing New Monitoring Technology for Roof Caving and Systematic Monitoring for Gob-Side Entry Retaining via Roof Cutting in Underground Coal Mining

The longwall mining method with gob-side entry retaining via roof cutting is a new underground coal mining method which has the characteristics of a high resource recovery ratio and environmental friendliness. Due to the complexity of this method, the research method of case-based dynamic on-site monitoring, analysis, adjustment, and optimization is usually adopted. Based on a roadway retaining via roof cutting project, in addition to the traditional indirect monitoring method of hydraulic support pressure, this study innovatively establishes a direct monitoring method for roof caving by monitoring the gangue pressure in the goaf, which provides data for the roof cutting effect and offers a new method for studying the overlying strata movement. In the project, a comprehensive monitoring and analysis system was established, including gangue pressure, cable bolt stress, bracket pressure, roadway deformation, and roof separation, which was used to dynamically analyze the effect of roof cutting and optimize the support design. The results show that the pressure of the hydraulic support close to the roof cutting is low, indicating that roof cutting is favorable in the roadway retaining mining method. The roadway deformation in the advanced abutment pressure area of the working face is small. The mining-induced stress caused by the collapse and compaction of the overlying strata in the goaf is the dominant factor affecting the effect of roadway retaining, especially in the 50-100 m range behind the working face, where the dynamic load causes high bearing capacity of the support elements, large roadway convergence, and roof separation. Temporary support and supplementary reinforcement should be added when necessary. The monitoring system presented in this study is highly comprehensive, simple, reliable, and low in cost, providing a reference for roof cutting roadway retaining projects and roof caving-related studies.

The advisability of an underground processing facility at the Voronets iron ore deposit

Relevance. When mining large iron ore deposits of the Kursk Magnetic Anomaly, one of the main problems is environmental safety, in particular, the maximum preservation of fertile soil. The underground mining method reduces the technogenic load on the natural environment and allows most of the mining waste to be placed in the mined-out space. However, main source of negative environmental impact is the processing production, which occupies large areas and is characterized by intense harmful emissions. Processing facilities placed underground significantly reduce this impact. Research objective is to assess the advisability of building an underground processing facility at the Voronets iron ore deposit. Methods of research. The work uses a comprehensive research method, including rational ore processing scheme justification, underground processing facility design, and a technical and economic comparison. Results. A scheme of ore processing with the production of a high-quality concentrate is presented, and a chain of mechanisms and apparatus for all stages of ore processing is selected, including its crushing, grinding, magnetic separation and dehydration of the resulting products. Based on the parameters of the selected equipment, its underground layout is shown, the volume the processing facility chambers is calculated. It is shown that the entire volume of tailings is located in the chamber goafs of the underground mine and are not lifted to the surface. Conclusions. An approximate assessment of the effectiveness of the processing facility underground location has been made. It has been shown that the cost of building that facility is comparable to the cost of building a similar processing facility on surface. Placing the processing in underground makes it possible to significantly reduce the area of land allotment of the enterprise, to lift only concentrate on the surface, and to eliminate the negative environmental impact of processing production.

Geological and geotechnical conditions of Shiraldzhin gold ore mining

Shiraldzhin lode deposit of gold–copper–silver ore in Kyrgyzstan has been studied since the 1980s. Shiraldzhin deposit lies within the boundaries of the Upper-Riphean Kumyshtag intrusion, with the Pre-Cambrian granitoid field broken by pillars of fine-grained Uzuntash granite of the Silurian Period. The proven five lodes have the negative economic appraisal for their mining. The primary appraisal covers only the main Sterzhnevoe lode body and includes some geomechanical problems. For this reason, the estimates of the reserves are re-interpreted toward the optimized gold extraction parameters. Modeling of the ore bodies within Shiraldzhin deposit is accomplished with justification of methods and systems to implement geotechnical solutions. Preparation of commercial ore by the sensor-based grading method allows bringing diluted ore to the level of 90% of underground gold content. Naturally, the proposed technology is a master technology for Shiraldzhin deposit. The open pit mining of Sterzhnevoe ore body in combination with the underground mining method at an ore extraction ratio of 60 : 40% defines the economic efficiency of the mining project. The geomechanical research of the ultimate limit open pit and the geotechnology efficiency evaluation in the underground mine, including the geotechnical behavior analysis in rock mass and the backfilling pilot testing, is a critical requirement to reach the design performance.

АНАЛИЗ ПРОГРАММНЫХ ПРОДУКТОВ ДЛЯ ПРОЕКТИРОВАНИЯ БУРОВЗРЫВНЫХ РАБОТ ПРИ ОТРАБОТКЕ МЕСТОРОЖДЕНИЙ ПОДЗЕМНЫМ СПОСОБОМ

This paper provides a brief overview of advanced software products for designing drilling and blasting operations in the development of deposits by underground mining method: we have demonstrated the key features of each of the software packages under consideration; presented existing companies that use them. Based on the results of this review, we have put forward our recommendations on selecting specialized software depending on the consumer's needs.

SELECTION OF THE MOST PROPER UNDERGROUND MINING METHOD FOR KODAKAN GOLD MINE IN IRAN

The selection of mining methods is a challenging and complicated concept in mining engineering. It depends on various and different factors such as geotechnical, geological and economic properties and characteristics. Kodakan Gold Mine in Iran is currently mined using the open pit method. However, due to the special conditions of this mine and the increase in waste removal costs, it is inevitable to decide to select an underground mining method in the future. The purpose of this research is to select the most proper underground mining method for this mine. The shape, dip, and depth of the deposit, the thickness of the ore, grade distribution, recovery, skilled manpower, output per worker, and strength specifications of the ore, hanging-wall, and footwall are considered as the main decision attributes. Since there are different parameters in selecting the appropriate mining method using the multi-attribute decision making approach, therefore hybrid multi-attribute decision-making method was employed in this paper to enhance the strength of the decision model and eliminate the weaknesses of the classical methods. Regarding the results of this study, rock quality designation of the hanging-wall and deposit shape have the highest weight value in selecting the underground mining method. Moreover, the shrinkage mining method is proposed as the most appropriate method.