Stope Design Research Articles

Industry Survey on the Current State of Stope Design Methods in the Underground Mining Sector

Stope design is a core discipline within mining engineering. This study analyzes the current state-of-the-art of stope design through a survey addressed to mining industry professionals. In stope design research the dominance of empirical methods has slowly shifted towards numerical methods. Recent advancements have mostly focused on the development of stope optimization algorithms. The survey consisted of 19 questions and was distributed to stope design experts via email, LinkedIn messages, and the Mining Industry Professionals network forum. In total, 36 responses of satisfying quality from 20 countries were received and analyzed. No dominance of a single stope design method was recognized. Empirical methods and personal expertise are still used widely. However, a readiness for change in stope design practice was indicated in 87% of responses. The current needs of the stoping-based underground mining sector are to increase the amount of geotechnical data, automate stope design and implement related software, and integrate these into general mine planning. According to 70% of the participants, acquired geotechnical data should be available within three days to be employed in design practice. The industry is ready to implement more efficient stope design methods if they offer results proven in case studies.

Development of a knowledge-based system for assessing unplanned dilution in open stopes

A reliable estimation of unplanned dilution is one of the most vital parameters in open stopping mining methods as unplanned dilution and sloughing can lead to an increase of the cost production and most importantly to safety concerns. Owing to this importance, several predictive models to estimate unplanned dilution and stope overbreak have been proposed. However, some of these existing models do not provide any physical meaning of the underlying dilution problem. To overcome this limitation, a fuzzy inference system (FIS) is proposed. In this paper, a new design tool capable of assessing unplanned dilution in a reliable manner is developed. The methodology relies on a fuzzy inference system (FIS) as many epistemic uncertainties that are associated with unplanned dilution are not systematically accounted for in existing methods. To this end, a dilution database from Ridder-Sokolny mine in Kazakhstan has been compiled. It consists of unplanned dilution cases and includes stope geometry, rock mass characteristics and stope reconciliation data. Subsequently, knowledge-based FIS was implemented. Overall, the results of the FIS show good classification performance (84% of accuracy). In comparison to the dilution graph developed based on traditional method, the FIS results show better performance. Hence, it was concluded that the proposed FIS could be an alternative tool for empirical open stope design.

Stochastic stope design optimisation under grade uncertainty and dynamic development costs

ABSTRACT Stope design optimisation defines three-dimensional extraction volumes aiming to maximise cashflows, subject to geotechnical and operational constraints. Available stope layout methods are deterministic, failing to account for grade uncertainty and variability that affect stope locations and sizes, as well as value. A two-stage stochastic integer programming model for stope design optimisation is proposed, integrating grade uncertainty quantified through geostatistical simulations, level allocation, variable stope and pillar sizes for different geotechnical zones, and development costs. An application at an underground gold mine employing sublevel open stoping highlights the integration and management of grade uncertainty to define risk-resilient stope design.

A Feasibility Study on The Implementation of Neural Network Classifiers for Open Stope Design

Assessing the stability of stopes is essential in open stope mine design as unstable hangingwalls and footwalls lead to sloughing, unplanned stope dilution, and safety concerns compromising the profitability of the mine. Over the past few decades, numerous empirical tools have been developed to dimension open stope in connection with its stability, using the stability graph method. However, one of the principal limitations of the stability graph method is to objectively determine the boundary of the stability zones, and gain a clear probabilistic interpretation of the graph. To overcome this issue, this paper aims to explore the feasibility of artificial neural network (ANN) based classifiers for the design of open stopes. A stope stability database was compiled and included the stope dimensions, rock mass properties, and the stope stability conditions. The main parameters included the modified stability number (N’), and the stope stability conditions (stable, unstable, and failed), and hydraulic radius (HR). A feed-forward neural network (FFNN) classifier containing two hidden layers (110 neurons each) was employed to identify the stope stability conditions. Overall, the outcome of the analysis showed good agreement with the field data; most stope surfaces were correctly predicted with an average accuracy of 91%. This shows an improvement over using the existing stability graph method. In addition, for a better interpretation of the results, the associated probability of occurrence of stable, unstable, or caved stope was determined and shown in iso-probability contour charts which were compared with the stability graph. The proposed FFNN-based classifier outperformed the conventional stability graph method in terms of accuracy and better prabablistic interpretation. It is suggested that the classifier could be a reliable tool that can complement the conventional stability graph for the design of open stopes.

Stope stability assessment by the Mathews–Potvin method: a case-study of open stoping in salt rock mass under conditions of secondary stress field

Predicting the stability of open stopes is a challenging task for underground mine engineers. The introductory part of this paper presents main issues related to stability and safety of soil and rock mass in course of large earthworks and underground works. On the basis of former studies, this paper reviews the research findings on stope stability by the methods of Mathews and Potvin in the stoping design for rock salt mines operating at depths greater than 1 km under conditions of secondary stress fields, as well as the rock mass quality assessment by Barton’s method. The conservative stope design has been performed for a few scenarios of design parameters. In conclusions, it is underlined by the stability graph at the given parameters, that in the first case-study scenario, HR is 4.5 m and the Mathews–Potvin stability number is 68 m. It is concluded that the stopes will be stable and preserve their shapes. On the basis of presented case study (stope stability assessment in the test halite–polyhalite–polymineral salt deposit was carried out for a few scenarios at maximal effective stresses and under conditions of jointing), the authors provide the general provisions on salt rock mass assessment at great depths.

Development of a Stope Stability Prediction Model Using Ensemble Learning Techniques - A Case Study

The consequences of collapsed stopes can be dire in the mining industry. This can lead to the revocation of a mining license in most jurisdictions, especially when the harm costs lives. Therefore, as a mine planning and technical services engineer, it is imperative to estimate the stability status of stopes. This study has attempted to produce a stope stability prediction model adopted from stability graph using ensemble learning techniques. This study was conducted using 472 case histories from 120 stopes of AngloGold Ashanti Ghana, Obuasi Mine. Random Forest, Gradient Boosting, Bootstrap Aggregating and Adaptive Boosting classification algorithms were used to produce the models. A comparative analysis was done using six classification performance metrics namely Accuracy, Precision, Sensitivity, F1-score, Specificity and Mathews Correlation Coefficient (MCC) to determine which ensemble learning technique performed best in predicting the stability of a stope. The Bootstrap Aggregating model obtained the highest MCC score of 96.84% while the Adaptive Boosting model obtained the lowest score. The Specificity scores in decreasing order of performance were 98.95%, 97.89%, 96.32% and 95.26% for Bootstrap Aggregating, Gradient Boosting, Random Forest and Adaptive Boosting respectively. The results showed equal Accuracy, Precision, F1-score and Sensitivity score of 97.89% for the Bootstrap Aggregating model while the same observation was made for Adaptive Boosting, Gradient Boosting and Random Forest with 90.53%, 92.63% and 95.79% scores respectively. At a 95% confidence interval using Wilson Score Interval, the results showed that the Bootstrap Aggregating model produced the minimal error and hence was selected as the alternative stope design tool for predicting the stability status of stopes.
 
 Keywords: Stope Stability, Ensemble Learning Techniques, Stability Graph, Machine Learning

A New Criterion for Numerical Modelling of Hangingwall Overbreak in Open Stopes

Determining stability, quantifying planned dilution, and estimating the potential dilution associated with hangingwall overbreak are critical in the process of stope design in sublevel open stoping mines. To satisfy these objectives, empirical stability graphs and numerical modelling are currently used in the mining industry. Empirical methods are limited to the database used to calibrate them. In the case of numerical modelling, some of the available criteria used to evaluate hangingwall overbreak do not include the intermediate principal stress around the stope and/or the rock mass geotechnical characteristics. In this study, a new criterion for numerical modelling is proposed to estimate the hangingwall overbreak in open stopes. This new criterion includes the intermediate principal stress around the stope and the rock mass geotechnical characteristics. To develop the criterion, several open stope numerical models are simulated considering different geometrical and geotechnical conditions. The criterion is calibrated to reproduce empirical case histories of hangingwall overbreak. Next, the criterion is verified with case histories of hangingwall overbreak that presented different conditions used to calibrate the criterion. The proposed criterion establish a significant influence and relationship between rock quality and the minimum and intermediate principal stresses on hangingwall overbreak. The criterion offers sufficient flexibility for application to a wide range of geometries, in situ stress conditions, and depth and rock mass properties.

Factors Influencing Ore Recovery and Unplanned Dilution in Sublevel Open Stopes. Case study of Shaft No.4 at Konkola Mine, Zambia

Konkola Copper Mine’s Number 4 Shaft is a trackless underground mine applying sublevel open stoping (SLOS) mining method. Number 4 shaft wants to increase ore production from 1 million metric tonnes per annum to 3 million metric tonnes per annum in the next 5 years but ore recovery is 70% or less and dilution is 20% or more. In order to achieve the desired annual target of 3 million metric tonnes ore recovery should be increased from70% to (≥85%) and dilution should be reduced from 20% to (≤10%). Despite being one of the most used underground mining methods, the current SLOS has a challenge of high unplanned dilution. This paper reviews and evaluates parameters that influence recovery and unplanned dilution in sublevel open stopes and applies numerical modelling using PHASE2 software to establish the influence of stress environment on unplanned dilution at the mine. The input parameters for numerical modelling were: Uniaxial Compressive strength (UCS=170MPa), Geological Strength Index (GSI) =55, Young’s Modulus (E) =26000MPa, Hoek-Brown constant (s) =0.0067, Hoek-Brown constant (mi) =20 and Poisson ratio (v) =0.2 major principal stress (σ1) 39MPa, intermediate stress (σ2= 18MPa) and the minor principal stress (σ3= 15MPa). Results obtained from review of mine production records indicate that the main factors that influence unplanned dilution at Number 4 shaft are: poor ground conditions, lack of compliance to recommended stope designs, poor drilling and blasting practices, presence of geological discontinuities, adopted mining sequence of extracting high ore grade first that leads to creation of high stress blocks within the orebody and delayed mucking practice. Results obtained from PHASE 2D model indicate that total displacement of 90mm is recorded in the hangingwall hence influencing stope wall instability that leads to increased unplanned dilution. After stope extraction, it was observed that 60MPa of induced stress developed at the top right corner and 45-50 MPa at the crown pillar and right bottom corner of the stope.

Modification of rock stress factor in the stability graph method: a case study at the Alhada Lead-Zinc Mine in Inner Mongolia, China

The stability graph is an empirical approach to predicting stope performance based on the geometric dimensions of stopes and the geotechnical conditions of the surrounding rock mass. Stability graph is commonly used to design and estimate the stability of open-stope mines and underground openings. Most engineers calculate the rock stress factor by the stability graph method considering the maximum principal stress at the center of the critical face and the uniaxial compressive strength of the intact rock, whereas the spatial multidimensional stress state, compressive strength of the rock mass, and tensile strength of the rock mass are not taken into account. In this study, the maximum and the minimum principal stresses dominating the rock stress factor are introduced into the stability graph. The rock stress factor (A) is modified by the Mohr-Coulomb criterion with tensile cutoff. The modified stability graph method was validated by adopting Cavity Monitoring System (CMS) laser technology, and it was then successfully applied in a case study at the Alhada Lead-Zinc Mine in Inner Mongolia. Compared with Mitri’s method, the proposed stability graph expands the scope of the narrow vein stope design dimensions. The modified rock stress factor in the stability graph provides a technical basis for the subsequent recovery of residual orebodies.

Stope Design for Conservation of Mineral and Safety in Underground Manganese Mine – A Case Study of Munsar Mine of MOIL Limited

MOIL Limited is the major manganese producer of the country. Manganese is mined chiefly by undergroundmining. Cut and Fill method of stopping is adopted in underground mines along with sill and barrier pillars toprotect the levels. Valuable manganese ore is locked in sill pillars and to stope design analysis was conducted toimprove reserves. Models were prepared with modified stopping methods for stability analysis. This paperpresents the outcome of the study.

Empirical and Numerical Finite-Element-Based Model to Improve Narrow Vein Mine Design in Peruvian Mining

This paper proposes a numerical finite-element-based model aimed at optimizing narrow-vein stope stability. This model combines empirical and numerical methods to develop a sequence, which may determine an acceptable stope safety factor. A stope stability analysis was conducted through the Mathews stability graph method, which requires two factors: the hydraulic radius (HR) and stability number (N’). The Mathews stability graph method is used to assess the stability of an underground design. Variations in stope dimensions are estimated by changing the HR and Factor A within the N’, which is determined through numerical methods. The results of the numerical simulation indicate that the HR increases with an increase in stope dimensions, while Factor A maintains an inverse relationship with the maximum stress induced on the excavation walls. This document demonstrates the potential of combining empirical and numerical methods in stope design optimization, especially when developed in small narrow vein mines.

Stability assessment of underground mine stopes subjected to stress relaxation

ABSTRACTStress relaxation plays an important role in the design of underground stopes. The aim of this paper is to assess the stope stability in connection with the stress relaxation using a classification approach. Three types of stress relaxation were clearly defined, namely partial relaxation, tangential relaxation and full relaxation. A neural network classifier was implemented to assess the stability of the stopes on the basis of case histories of stope performances. The results of the classification were compared to existing empirical methods of quantifying the stress relaxation. Overall, the present study shows higher classification accuracies, especially when the stress relaxation was considered. The results suggested that the relaxation type can be a good predictor of stability. Relaxed stope (full and tangential stress relaxation) cases are the most critical in the sense that lower accuracies were obtained and the probability of correct classification is rather erratic.

On the question of original versus modified stability graph factors – a critical evaluation

ABSTRACTThe Stability Graph has become an industry standard for open stope design. To date, there are two schools of thought on the use of the Original and Modified Stability Graph number factors. This paper is aimed at answering the question: Is there a difference between the Original and the modified stability number factors? To answer this question, a critical examination of the Extended Mathews and Modified Stability Graph databases was conducted to create a combined database of 316 datapoints. One version of the database was based on the original number factors, while a second was based on the modified factors. Logistic regression methods were applied to redefine the stope stability state boundaries. We concluded that differences between the stope stability states transition zones in the Stability Graphs are due to the differences in size of the databases rather than differences in the Original and Modified Stability Graph number factors.

Using Empirical Approaches in Stope Design

Maden planlama ve tasarlama süreci, doğal kaynakların etkin bir şekilde kullanılmasını sağlamak ve madencilik sırasında ortaya çıkan maliyetlerin tümünü azaltmak açısından oldukça önemlidir. Yeraltı madenciliğinde seçilecek üretim yöntemine bağlı olarak, kazı arınlarının seyrelme ve cevher kaybını en aza indirecek şekilde tasarlanması gerekmektedir. Bu noktada kaya kütlesi karakterizasyonu ve kazı arını geometrisi gibi parametreleri göz önünde bulunduran ampirik kazı arını tasarımları dikkat çekmektedir. Duraylı kazı arınlarını tasarlamak üzere, ampirik duraylılık grafiği yönteminin de bu kapsamda yaygın olarak kullanıldığı bilinmektedir. Duraylılık grafiği yöntemi ilk olarak kazı arını tasarımlarını yapmak üzere ortaya konulmuş, ardından kazı arını tasarımı konusunda özellikle metal madenlerinde dünya çapında geniş kabul görmüştür. Yöntem, Tünel Kalitesi Q indeksine dayanmakta ve kazı arını tasarımını etkileyen en önemli faktörleri dikkate almaktadır. Duraylılık grafiği yönteminde geçmişten bugüne, kazı arınlarının duraylılık durumunu tahmin etmedeki güvenilirliğini artırmayı amaçlayan çeşitli gelişmeler yaşanmıştır. Bu çalışma öncelikle duraylılık grafiği yöntemini detaylı bir şekilde tanıtmakta ardından bu konuda yapılan gelişmeleri ele almaktadır.

Modified ground support with alternative fill material for ground control at munsar underground manganese mine of moil limited, India

Abstract MOIL Limited is operating 7 underground and 3 opencast mines in central India and producing annually more than 1.3 million tonnes of various grades of manganese ore. The underground mines are operating at shallow – 90 m at Munsar mine to moderate – 353 m at Balaghat mine below the surface with horizontal cut and fill (HCF) or its variant method of stoping with post filling by hydraulic sand stowing. The Munsar mine is being worked underground since 1903. The opencast mining is presently stopped. The ore body below the opencast quarry is geological continuity of the area excavated in past by opencast method of mining. The underground mining is done through the adit in three levels i.e. 270’L, 220’L, 170’L and by incline in western part of the property at 70’L. The horizontal drift development has been developed in the manganese ore body with sill drive of 5 m above the sill pillar in lower level at 70’L and barrier pillar of 5 m thickness is left for protection of upper level at 170’L. Valuable mineral has been locked in sill pillar and therefore rock mechanics investigations have been carried out. On the basis of study now the drift development has been carried out in footwall rock at 70’L, (-) 30’L and below levels and it has improved the minable manganese ore by about 20%. In this modified HCF stope design, an alternative fill material in place of sand, which has been developed in house by use of overburden (OB) material after treatment, has been used for hydraulic stowing. The experimental trials find out that the alternative fill material of OB is more compact and forms a non-expansion floor for the men and machines in the stope. This will certainly help in the introduction of mobile underground mining equipment for drilling in the stopes and mechanical mucking, transportation and loading of the ROM. The paper presents rock mechanics investigations and future use of alternative fill material of overburden material after heat treatment for better safety and productivity at Munsar Mine of MOIL.

Probabilistic-Based Stope Design Methodology for Complex Ore Body with Rock Mass Property Variability

This paper presents a probabilistic approach for optimizing stope design methodology while taking into consideration the variability in the rock mass properties. For this study, a complex orebody in a Canadian mine was used. Because of the variability in the rock mass properties of the orebody, it was not possible to determine precisely, the values of geotechnical design input parameters and hence the need to utilize a probabilistic approach. Point Estimate Method (PEM), a probabilistic tool, was incorporated into numerical analysis using FLAC3D to study the deformation magnitudes of various stope geometries to determine the optimal stope geometry with a minimum ground control problem. Results obtained for the distribution of the wall deformations and the floor heaves for each option of the stope geometry were compared to select the best geometry to achieve the optimum stability condition. The methodology presented in this study can be helpful in the process of underground mine planning and optimization in complex orebody.

Risk Evaluation, Design, Implementation, Instrumentation, and Verification for Crown Pillar Extraction at Pinos Altos Mine

The Santo Nino ore body at Pinos Altos Mine has been in production since 2009 using both open pit and underground mining methods. Between 2015 and 2017, an extensive study evaluated extraction strategy of the Santo Nino crown pillar. The Agnico Eagle project team evaluated geomechanical, operational, safety and economical risks before developing a comprehensive plan to extract the Santo Nino crown pillar by underground stoping. The geomechanical aspects of that study focused on interpreting in situ rock mass conditions and understanding the mechanical and hydrological/hydrogeological mechanisms influencing ground reaction during open pit and underground mine operations to make meaningful forward predictions for crown pillar extraction. Numerical modeling played a significant role in making forward predictions. To minimize uncertainty in those predictions, the model parameters were calibrated using measured pit slope deformations, back analysis of historical slope instabilities and underground observations of rock mass conditions. Ultimately, it was decided that long-hole stoping would be utilized for crown pillar extraction. The pit floor would be used as a drilling horizon, and the upper most level of the underground operations served as the mucking horizon. Various safety and operational risk mitigation strategies were developed and implemented; this included geomechanical monitoring using the in-pit radar system and numerous borehole extensometers installed underground to monitor ground deformations. The calibrated numerical model results provided valuable input for the design of the instrumentation program, and once the crown pillar came into production in late 2017, the instrumentation provided valuable data for model verification and stope design adjustments.

A Case Study of Fracture Law and Stress Distribution Characteristics of Surrounding Rock of Working Face in Deep Mines

In order to provide the basis for deep mine stope design and disaster prevention, microseismic and coal stress monitoring techniques were used to measure the surrounding rock fracture law and stress distribution in deep mine stope. According to the microseismic monitoring, after the mine enters the deep mining stage, the range of overlying strata movement expanded, the overlying strata are divided into several characteristic layers, which are periodically fractured along with the working face advance. And the influence distance of the movement of the overlying strata on the front of the working face is far beyond the influence distance of the shallow mining stage. According to the joint analysis of vibration and stress monitoring data, it can be known that the real-time warning of rockburst risk can be acknowledged through the joint monitoring of microseismic and stress.

Prediction of open stope hangingwall stability using random forests

The prediction of open stope hangingwall (HW) stability is a crucial task for underground mines. In this paper, a relatively novel technique, the random forest (RF) algorithm, is introduced for the prediction of HW stability. The objective of this study is to verify the feasibility of the RF algorithm on HW stability prediction and investigate the relative importance of influencing variables. The training and verification of RF models were conducted on a dataset from the literature and a total of 115 HW cases were analysed. Thirteen influencing variables were selected as the inputs with the HW stability being selected as the output. The dataset was randomly divided into the training set and the testing set. Fivefold cross-validation was used as the validation method, and the grid search method was used for the hyper-parameters tuning. Performance measures were chosen to be the confusion matrix, the receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC). The results show that the RF algorithm had great potential for the prediction of HW stability. AUC values achieved by the optimum RF model on the training set and the testing set were 0.884 and 0.873, respectively, indicating that the optimum RF model was excellent at predicting HW stability. The stope design method was found to be the most sensitive variable among all variables evaluated, with an importance score of 0.168 out of 1. The RQD and HW height also had a strong influence on the stability of an open stope HW.

Evolutionary Random Forest Algorithms for Predicting the Maximum Failure Depth of Open Stope Hangingwalls

The prediction of the failure depth of open stope hangingwalls (HWs) has become a crucial task for underground mines worldwide. In this paper, an evolutionary random forest (RF) technique that combines the RF algorithm and particle swarm optimization (PSO) was proposed to model the non-linear relationship between maximum failure depth (MFD) of stope HWs and its influencing variables. The training and verification of RF models were conducted on a dataset collected from the literature, and a total number of 125 valid HW cases were analyzed. The 13 influencing variables were used as inputs. Hyper-parameters of RF models were tuned by PSO with fivefold cross-validation, and the performance of RF models was measured by root-mean-square error and correlation coefficient (R). Experimental results show that the RF algorithm had great potential for predicting the MFD of HWs. The R values between the predicted and actual MFD values were 0.93 and 0.84, respectively. The stope design method was found to be the most significant influencing variable with an importance score of 0.516 out of 1, followed by the RQD of rock mass (0.127), stope strike (0.078), and HW height (0.075).