Exploitation
Samia Chaoui; Adel Djellali; Benghazi Zied; Sarker Debojit
Abstract
This study aims to investigate the stability of rooms and pillars along the inclined zinc orebody at the Chaabet El Hamra underground mine (Setif, Algeria). Stability was initially assessed using an analytical shear strength model, with the results subsequently validated through numerical modeling. Geomechanical ...
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This study aims to investigate the stability of rooms and pillars along the inclined zinc orebody at the Chaabet El Hamra underground mine (Setif, Algeria). Stability was initially assessed using an analytical shear strength model, with the results subsequently validated through numerical modeling. Geomechanical characterization revealed low interstitial porosity, strong to very strong uniaxial compressive strengths ranging from 50.4 MPa to 129 MPa, and significant fracture-related secondary porosity. Rock Mass Rating (RMR89) and Geological Strength Index (GSI) values suggest fair to good rock quality. The mine design features square pillars inclined at 10°, with walls originally oriented perpendicular to the orebody dip, measuring 5 m in width and 3 m in height. The rooms, situated under a cover depth of 145.3 m, are 9 m wide. This configuration yielded an effective extraction rate of 87.24% and a safety factor of 1.63, indicating stable mining conditions. Phase 2D finite-element simulation confirmed these findings, showing a maximum displacement of 3.96 mm, surface subsidence of 0.57 mm, and a safety factor of 1.66, suggesting minimal environmental impact and long-term stability. Shear/compressive stress results from tributary area theory, aligning with numerical results and validating both approaches for inclined orebodies. Finally, the pillar walls, originally perpendicular to the orebody dip, were modified to be vertical relative to the horizontal plane, while maintaining the same pillar and room dimensions and cover depth. This adjustment improved stability by enhancing stress distribution and pillar core confinement, increasing the safety factor to 1.85.
Mineral Processing
Sahil Thakur; Ravi Kumar Sharma
Abstract
Slope stability is critical for infrastructure safety, particularly in seismically active regions. This work evaluates the stability of a slope along the Baroti-Reyur road in Himachal Pradesh, located in Zone 5, using a novel combination of Limit Equilibrium Methods (LEMs) and Finite Element Methods ...
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Slope stability is critical for infrastructure safety, particularly in seismically active regions. This work evaluates the stability of a slope along the Baroti-Reyur road in Himachal Pradesh, located in Zone 5, using a novel combination of Limit Equilibrium Methods (LEMs) and Finite Element Methods (FEMs). The analysis examines natural slope conditions and the impact of sustainable mitigation measures, including retaining structures and bioengineering techniques, under the static and dynamic conditions. The soil model incorporated a modulus of elasticity (E) of 90,000 kN/m², and a poisson's ratio (v) of 0.3 to reflect realistic slope-soil-structure interactions. Retaining structures such as gravity, cantilever, and gabion walls (4 m, 6 m, and 5 m high) were constructed using M30 RCC and Fe500 steel. Bioengineering measures featured deep-rooted grasses like Vetiver and Broom grass to improve soil cohesion (c), shrubs like Lantana camara for surface stability, and trees like Albizia lebbeck to reinforce deeper soil layers. These vegetation-based interventions enhanced slope resilience, while promoting ecological restoration. Theoretical LEM analysis revealed marginal stability, with static FOS values of 1.1 and pseudo-static FOS of 1.05. GEO5 pseudo-static analysis indicated critically low FOS value of 0.88 for dynamic saturated conditions, improving to 2.01 with retaining structures. FEM analysis using PLAXIS 2D provided more detailed insights, capturing complex soil-structure interactions with a static FOS of 1.028 and dynamic FOS of 0.994. By combining FEM with sustainable mitigation strategies, this work offers a framework for resilient slope stabilization, ensuring safety, while promoting environmental sustainability in seismically active regions.
Exploitation
F. Soltani; P. Moarefvand; F. Alinia; P. Afzal
Abstract
The traditional approaches of modeling and estimation of highly skewed deposits have led to incorrect evaluations, creating challenges and risks in resource management. The low concentration of the rare earth element (REE) deposits, on one hand, and their strategic importance, on the other, enhances ...
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The traditional approaches of modeling and estimation of highly skewed deposits have led to incorrect evaluations, creating challenges and risks in resource management. The low concentration of the rare earth element (REE) deposits, on one hand, and their strategic importance, on the other, enhances the necessity of multivariate modeling of these deposits. The wide variations of the grades and their relation with different rock units increase the complexities of the modeling of REEs. In this work, the Gazestan Magnetite-Apatite deposit was investigated and modeled using the statistical and geostatistical methods. Light and heavy REEs in apatite minerals are concentrated in the form of fine monazite inclusions. Using 908 assayed samples, 64 elements including light and heavy REEs from drill cores were analyzed. By performing the necessary pre-processing and stepwise factor analysis, and taking into account the threshold of 0.6 in six stages, a mineralization factor including phosphorus with the highest correlation was obtained. Then using a concentration-number fractal analysis on the mineralization factor, REEs were investigated in various rock units such as magnetite-apatite units. Next, using the sequential Gaussian simulation, the distribution of light, heavy, and total REEs and the mineralization factor in various realizations were obtained. Finally, based on the realizations, the analysis of uncertainty in the deposit was performed. All multivariate studies confirm the spatial structure analysis, simulation and analysis of rock units, and relationship of phosphorus with mineralization.
Rock Mechanics
Sahrul Poalahi Salu; Bima Bima
Abstract
Expansion of mining pit is associated with an increased risk of slope instability and high costs. This is because changes in geometry of the mine slope significantly affect slope stability, alter the stripping ratio, and potentially threaten the continuity of mining operations. Therefore, this research ...
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Expansion of mining pit is associated with an increased risk of slope instability and high costs. This is because changes in geometry of the mine slope significantly affect slope stability, alter the stripping ratio, and potentially threaten the continuity of mining operations. Therefore, this research work aimed to investigate the impact of changes in geometry of mining pit on slope stability to provide insight into safety, economic assurances, and ensure the sustainability of mining operations. This research work was applied by the 2D numerical modeling method using the Slide Software V. 6.0 Rocscience to analyze geometry of mining pit and impact on slope safety factors. The investigation was conducted at Pit Block A of Pt. Hikari Jeindo, managing nickel mining activities in the Langgikima District, North Konawe, Regency, Southeast Sulawesi Province, Indonesia. The results showed that the modeling method successfully showed changes in slope geometry, ensuring safe and economically viable slope safety factors. However, to obtain a more comprehensive understanding of slope stability conditions, a 3D numerical modeling method is required to capture the area affected by expansion of mining pit.
V. Sarfarazi; K. Asgari
Abstract
In this investigation, the impact of confining pressure on the tensile strength obtained by point load test (PLT) is examined by particle flow code in two dimensions. In this regard, at first, a numerical model is calibrated using the Brazilian experimental test results. The tensile strength of the model ...
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In this investigation, the impact of confining pressure on the tensile strength obtained by point load test (PLT) is examined by particle flow code in two dimensions. In this regard, at first, a numerical model is calibrated using the Brazilian experimental test results. The tensile strength of the model material is equal to 2.5 MPa. Secondly, PLT is performed on the numerical models with dimension of 15 cm × 50 cm. The rectangular models are tested by PLT under the presence of the confining pressure. The loading rate is 0.001 mm/min, confining that the pressure is changed with the 13 different values of 0 MPa, 0.002 MPa, 1MPa, 1.5 MPa, 2 MPa, 2.5 MPa, 3MPa, 3.5 MPa, 4 MPa, 5MPa, 6 MPa, 9 MPa, and 11 MPa. The results obtained show that the vertical tensile crack develops through the model under a low confining pressure, while several shear bands are developed in the models under a high confining pressure. The number of shear cracks is augmented by augmenting the confining pressure. Is(50) is the augment by augmenting the confining pressure. Also a new criterion is rendered in order to determine Is(50) based on the confining pressure.
Exploration
Vivek Sharma; Ravi Kumar Sharma; Pardeep Kumar
Abstract
In the present work, the empirical correlations between standard penetration test (SPT) N-values versus shear modulus (Gmax), and Peak Ground Acceleration (PGA) amplifications for sub-Himalayan district-Hamirpur, Himachal Pradesh (India) consisting of highly variable soil/rock strata at different ...
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In the present work, the empirical correlations between standard penetration test (SPT) N-values versus shear modulus (Gmax), and Peak Ground Acceleration (PGA) amplifications for sub-Himalayan district-Hamirpur, Himachal Pradesh (India) consisting of highly variable soil/rock strata at different depths and across the terrain are evaluated. In the first stage, the N values obtained from SPTs are conducted in the field at 184 locations covering the studied area. The shear wave velocity for each soil profile of each borehole is calculated using the best available correlation in the literature. Further, the seismic response parameters are evaluated for these values using the ProShake software. Finally, the empirical relationships between maximum shear modulus and SPT value for different soil types are determined along with the ground motion amplifications. The amplification factor for Bhoranj sub-division varies from 1.40 to 2.60 and from 1.28 to 2.30, 1.20 to 2.10, 1.22 to 1.85, and 1.22 to 1.70 for Barsar, Nadaun, Hamirpur, and Sujanpur, respectively. The studied area consists of variable soil strata including clay, silt, sand, conglomerate, sandstone, and mixture thereof. The correlation between shear modulus and N value is coherent with already reported correlations for regular soils. The amplification factor reported for the sites plays an important role in planning infrastructure in the region. The correlations between maximum shear modulus (Gmax) and SPT value for hilly terrain comprising of highly complex geological formations such as mixed soil and fractured rocks presented in the study are not available in the research work carried out earlier.
A. Zolfaghari; N. Barzegar; M. Amini
Abstract
The gypsum mineralization occurred in the form of Satin Spar and Selenite in the south and southwest of the Fars province in the folded Zagros zone. In this region, Satin Spar mineralization has been formed as stratiform between the red marl and siltstone units of Late Miocene–Pliocene in Agha ...
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The gypsum mineralization occurred in the form of Satin Spar and Selenite in the south and southwest of the Fars province in the folded Zagros zone. In this region, Satin Spar mineralization has been formed as stratiform between the red marl and siltstone units of Late Miocene–Pliocene in Agha Jari, Bakhtiari, and the Gachsaran formations. The reserves of Satin Spar in this area are at least 200,000 tons. Satin Spar due to its chatoyancy, has been able to distinguish itself from gypsum. This beautiful light phenomenon (chatoyancy) results from the regular and parallel arrangement of the Satin Spar fibers. The mineral was first identified by its physical properties, and then by the X-ray diffraction analysis. They were also examined by scanning electron microscopy for its structure and also the structure of fiber crystals and their optical properties. In order to examine the polishing condition of Satin Spar, several samples of this gemstone were also selected for fantasy and Cabochon cut. For the first time in Iran, the exploration of Satin Spar gemstone in the Fars region can be a model for its discovery in the other evaporative formations in the country.
Environment
Sphiwe Emmanuel EMMANUEL Mhlongo; Francis Amphose Dacosta; Armstrong Kadyamatimba; George O Akintola
Abstract
South Africa has 6100 documented abandoned mines. The government is responsible for the management and rehabilitation of these mines to address their environmental problems, physical hazards, and socio-economic issues. In general, rehabilitating abandoned mines involves making a series of critical decisions ...
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South Africa has 6100 documented abandoned mines. The government is responsible for the management and rehabilitation of these mines to address their environmental problems, physical hazards, and socio-economic issues. In general, rehabilitating abandoned mines involves making a series of critical decisions about the strategies to be implemented in rehabilitating the major features of these mines. This paper presents an expert system developed to aid in selecting appropriate strategies for rehabilitating abandoned mines in South Africa. This system is known as the Expert System for Selection of Strategies for Rehabilitation of Abandoned Mines (ES-SRSA). The ES-Builder (Version 3.0, McGoo software) was used to design the knowledge and rule-based components of the expert system. The rules of the expert systems were developed based on the documented knowledge of the problems of abandoned mines in South Africa and the information gathered by the researcher through visits to selected abandoned mine sites in the country. The ES-SRSA provides 45 recommendations of suitable strategies for dealing with the different problems of features such as underground entries, mine waste, surface mine excavations, silos and orebins, and other features like dilapidated buildings/infrastructure. Most of the rules of this expert system encourage the repurposing and reuse of these mine features to improve the social and economic status of the host communities. The use of this expert system has the potential of contributing to the reduction of the risks of implementation of ineffective strategies for the rehabilitation of abandoned mines in a country like South Africa.
Rock Mechanics
Mahdi Bajolvand; Ahmad Ramezanzadeh; Amin Hekmatnejad; Mohammad Mehrad; Shadfar Davoodi; Mohammad Teimuri; Mohammad Reza Hajsaeedi; Mahya Safari
Abstract
Bit wear is one of the fundamental challenges affecting the performance and cost of drilling operations in oil, gas, and geothermal wells. Since identifying the factors influencing bit wear rate (BWR) is essential, and the ability to predict its variations during drilling operations is influenced by ...
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Bit wear is one of the fundamental challenges affecting the performance and cost of drilling operations in oil, gas, and geothermal wells. Since identifying the factors influencing bit wear rate (BWR) is essential, and the ability to predict its variations during drilling operations is influenced by environmental and operational factors, this study aims to develop an Adaptive Bit Wear Rate Predictor (ABWRP) algorithm for estimating the BWR during drilling operations for new wells. The structure of this algorithm consists of a data transmitter, data processor, deep learning-based bit wear rate estimator, and a bit wear updating module. To develop a model for the BWR estimation module, data from two wells in an oil field in southwest Iran were collected and analyzed, including petrophysical data, drilling data, and bit wear and run records. Both studied wells were drilled using PDC bits with a diameter of 8.5 inches. After preprocessing the data, the key factors affecting the bit wear rate were identified using the Wrapper method, including depth, confined compressive strength, maximum horizontal stress, bit wear percentage, weight on bit, bit rotational speed, and pump flow rate. Subsequently, seven machine learning (ML) and deep learning (DL) algorithms were used to develop the bit wear rate estimation module within the ABWRP algorithm. Among them, the convolutional neural network (CNN) model demonstrated the best performance, with Root Mean Square Error (RMSE) values of 0.0011 and 0.0017 and R-square (R²) values of 0.96 and 0.92 for the training and testing datasets, respectively. Therefore, the CNN model was selected as the most efficient model among the evaluated models. Finally, a simulation-based experiment was designed to evaluate the performance of the ABWRP algorithm. In this experiment, unseen data from one of the studied wells were used as data from a newly drilled well. The results demonstrated that the ABWRP algorithm could estimate final bit wear with a 14% error. Thus, the algorithm developed in this study can play a significant role in the design and planning of new wells, particularly in optimizing drilling parameters while considering bit wear effects.
Environment
Kushai Caleb Aluwong; Mohd Hazizan bin Mohd Hashim; Suhaina Ishmail
Abstract
In the past, assessing water quality has typically involved labor-intensive and costly processes such as laboratory analysis and manual sampling, which do not provide real-time data. In addition to tasting bad, drinking acidic water on a regular basis can result in acid reflux and recurrent heartburn ...
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In the past, assessing water quality has typically involved labor-intensive and costly processes such as laboratory analysis and manual sampling, which do not provide real-time data. In addition to tasting bad, drinking acidic water on a regular basis can result in acid reflux and recurrent heartburn while high total dissolved solids water can cause kidney stones, especially when the hard water content is more than 500ppm. With growing concerns about water quality, there is a need for continuous monitoring of pH and TDS levels in surface and groundwater sources. To address this, a cutting-edge wireless sensor system leveraging on Internet of Things (IoT) technology has been developed. This system incorporates top-notch pH and TDS sensors known for their accuracy, durability, and environmental compatibility. Integrated with microcontrollers featuring wireless communication capabilities, these sensors enable seamless data transmission to a central server through IoT protocols like cellular networks. The collected data is processed and calibrated to ensure reliability and precision. The IoT platform connected to the central server manages device connectivity, data storage, and analysis, making real-time data accessible via user-friendly web or mobile applications with interactive graphs and dashboards. Power-saving features are implemented to optimize battery life in remote and off-grid locations, and weather-resistant enclosures protect the sensor nodes from harsh environmental conditions. By deploying this wireless-based sensor system, users can gain valuable real-time insights into water quality in surface and groundwater monitoring locations.
Exploration
Hassanreza Ghasemi Tabar; Sajjad Talesh Hosseini; Andisheh Alimoradi; Mahdi Fathi; Maryam Sahafzadeh
Abstract
Estimating ore grades during the exploration phase is often time-consuming and costly due to the need for extensive drilling. Geophysical surveys, as the last indirect exploration method before drilling, offer valuable insights into subsurface mineralization. This study introduces a novel approach for ...
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Estimating ore grades during the exploration phase is often time-consuming and costly due to the need for extensive drilling. Geophysical surveys, as the last indirect exploration method before drilling, offer valuable insights into subsurface mineralization. This study introduces a novel approach for simulating “identical twins” of borehole copper grade values using geophysical attributes derived from the geoelectrical method in the Kahang porphyry copper deposit, central Iran. By treating the simulated values as digital twins of actual borehole grades, we employed four machine learning algorithms—Linear Regression (LR), Gradient Boosting (GB), Random Forest (RF), and Support Vector Machine (SVM)—to model the complex relationships between geophysical inputs and copper grades. After data preprocessing with Principal Component Analysis (PCA), a refined dataset was used to train, test, and validate each model. The results demonstrate that GB yielded the highest predictive accuracy, generating grade estimates closely aligned with actual values. This identical twin modeling approach highlights the potential of machine learning to enhance early-stage mineral exploration by reducing dependence on costly drilling.
Mineral Processing
Fatemeh Kazemi; Ali akbar Abdollahzadeh
Abstract
This research work aims to explore the intricate mineralogy and texture of the tailing piles of iron ore processing plants to present a particle-based prediction for magnetite recovery. Three samples were taken from different points of tailings piles of an iron ore processing plant. Davis tube tests ...
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This research work aims to explore the intricate mineralogy and texture of the tailing piles of iron ore processing plants to present a particle-based prediction for magnetite recovery. Three samples were taken from different points of tailings piles of an iron ore processing plant. Davis tube tests were performed on each sample under various operating conditions. Process mineralogy studies were conducted to determine the mineralogy modal of the feed and product of each test. An Artificial Neural Network (ANN) model was used to make a model that related the grade and recovery of magnetite in the product to the mineralogy modal of the tailing piles. The magnetite grade and association index of feed, the magnetic intensity, and the water flow rate were the inputs to this network. The grade and magnetite recovery correlation coefficients were 0.954 and 0.86, respectively. The grade of magnetite in the feed emerged as a limiting factor on the grade and recovery of magnetite in concentrate. An increase of one unit in magnetite grade in the feed resulted in a 1.68 decrease in the recovery. The association index changes with the coefficients of -0.173 cause the changes in predicted magnetite recovery in the concentrate.
R. N. Singh; A.S. Atkins; A.G. Pathan
Abstract
Ground water and surface water create a range of problems in lignite mining utilizing surface mining methods. In order to create a safe and economic mining environment, it is essential to carry out mining after dewatering the rock mass surrounding the lignite mines by advance dewatering techniques. This ...
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Ground water and surface water create a range of problems in lignite mining utilizing surface mining methods. In order to create a safe and economic mining environment, it is essential to carry out mining after dewatering the rock mass surrounding the lignite mines by advance dewatering techniques. This paper briefly describes the ground water regimes including pressure gradients associated with various lignite deposits together with the practical examples of some important lignite deposits in the world. An effective method of controlling ground water in multi-aquifer environment in lignite deposits is to carry out rock mass dewatering using borehole pumps. This approach will help reducing the inflow rates of ground water to the mining excavation and also increase the effective strength of the overburden strata, thus, increasing the slope stability of the mining excavations. The main theme of this paper is to present a case history analysis of Thar lignite deposit in Sindh, Pakistan which has lignite reserves of some 193 billion tonnes. The paper presents a proposed method of dewatering the Thar prospect together with an assessment of the quality of aquifer water which can be used to improve the quality of life of people inhabiting in the Thar Desert area of Sindh, Pakistan. Water samples from three aquifers were collected from nine different locations and were analyzed in the laboratory for evaluating their physical and chemical characteristics. The test results indicated that the aquifer water can be classified as (sodium+ potassium) – chloride type water with a TDS range of 1000 to 20,000 mg/L. Consequently, this ground water is classified as brackish (saline water) requiring treatment before it can be utilised for domestic or industrial consumptions. It should be noted that this ground water does not contain heavy metals and toxic metals including arsenic, mercury and lead or cyanide. However, results indicate that groundwater from a few locations contained traces of silver (<4oppb)Owithozinc0<0.1ppm.
Exploitation
Shambhavi sinha; Anup Tripathi; Akhil Avchar; Mritunjay kumar
Abstract
Accurate assessment of rock mass quality in marble quarries remains challenging because conventional empirical classification systems are largely strength-dominated and insufficiently sensitive to discontinuity-controlled block instability. This study proposes a quarry-specific empirical framework, termed ...
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Accurate assessment of rock mass quality in marble quarries remains challenging because conventional empirical classification systems are largely strength-dominated and insufficiently sensitive to discontinuity-controlled block instability. This study proposes a quarry-specific empirical framework, termed the Marble Rock System (MRS), designed to explicitly capture structural, hydro-mechanical, and alteration-driven controls governing bench-scale stability in dimension stone marble quarries. The primary objective was to develop and validate an empirically grounded classification system using machine learning as an independent diagnostic tool rather than as a black-box predictor.A comprehensive geomechanical database comprising 85 quarry-scale records was developed from three active marble quarries in southern Rajasthan, India. Six physically interpretable parameters intact strength, weathering or serpentinization, joint frequency, joint surface condition, groundwater influence, and block stability were incorporated into the MRS framework. Supervised machine learning models, including artificial neural networks, support vector machines, and linear regression, were trained to predict independently derived factors of safety for validation. Model performance was evaluated using coefficient of determination, root mean square error, cross-validation, and classification metrics.Results show that MRS-based models achieved consistently higher predictive accuracy, improved class separability, and more stable generalization than models trained using conventional Rock Mass Rating inputs. Sensitivity analysis revealed that block stability and joint characteristics dominate stability prediction, while intact strength plays a secondary role. These findings confirm that marble quarry slope behaviour is primarily discontinuity-controlled. The proposed MRS provides a physically interpretable, empirically validated framework for quarry-scale stability assessment and offers a robust alternative to conventional classification systems for operational decision-making.
M. Eftekhari; A. Baghbanan; H. Hashemolhosseini
Abstract
The cracked Brazilian disc (CBD) specimen is widely used in order to determine mode-I/II and mixed-mode fracture toughness of a rock medium. In this study, the stress intensity factor (SIF) on the crack-tip in this specimen is calculated for various geometrical crack conditions using the extended-finite ...
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The cracked Brazilian disc (CBD) specimen is widely used in order to determine mode-I/II and mixed-mode fracture toughness of a rock medium. In this study, the stress intensity factor (SIF) on the crack-tip in this specimen is calculated for various geometrical crack conditions using the extended-finite element method (X-FEM). This method is based upon the finite element method (FEM). In this method, the crack is modeled independently from the mesh. The results obtained show that the dimensionless SIFs for the pure modes I and II increase with increase in the crack length but the angle in which pure mode-II occurs decreases. For the mixed-mode loading, with increase in the crack angle, NI value decreases, while NII value increases to a maximum value and then decreases. The results obtained from the crack propagation examinations show that the crack angle has an important effect on the crack initiation angle. The crack initiation angle increases with increase in the crack angle. When the crack angle is zero, then the crack is propagated along its initial direction, whereas in the mixed-mode cases, the crack deviates from the initial direction, and propagates in a direction (approximately) parallel to the direction of maximum compressive load.
F. Razavi Rad; F. Mohammad Torab; A. Abdollahzadeh
Abstract
Considering the importance of Cd and U as pollutants of the environment, this study aims to predict the concentrations of these elements in a stream sediment from the Eshtehard region in Iran by means of a developed artificial neural network (ANN) model. The forward selection (FS) method is used to select ...
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Considering the importance of Cd and U as pollutants of the environment, this study aims to predict the concentrations of these elements in a stream sediment from the Eshtehard region in Iran by means of a developed artificial neural network (ANN) model. The forward selection (FS) method is used to select the input variables and develop hybrid models by ANN. From 45 input candidates, 13 and 14 variables are selected using the FS method for Cadmium and Uranium, respectively. Considering the correlation coefficient (R2) values, both the ANN and FS-ANN models are acceptable for estimation of the Cd and U concentrations. However, the FS-ANN model is superior because the R2 values for estimation of Cd and U by the FS-AAN model is higher than those for estimation of these elements by the ANN model. It is also shown that the FS-ANN model is preferred in estimating the Cd and U population due to reduction in the calculation time as a consequence of having less input variables.
Rock Mechanics
A. Akrami; M. Hosseini; H. Sodeifi
Abstract
Hydraulic fracturing is used in the oil industry in order to increase the index of production and processing in the wells whose efficiencies have been dropped due to a long-term harvest or the rocks around the wells are of low permeability. Since the hydraulic fracturing operation is costly, it is of ...
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Hydraulic fracturing is used in the oil industry in order to increase the index of production and processing in the wells whose efficiencies have been dropped due to a long-term harvest or the rocks around the wells are of low permeability. Since the hydraulic fracturing operation is costly, it is of special importance to the project managers to determine the pressure required for hydraulic fracturing and the suitable pump for this operation. The numerical modelings used in this work are aimed to investigate the fracture pressure in the carbonate rocks of Bangestan reservoir in Ahvaz, Iran, and to determine a relationship between the pressure required for fracturing and the confining pressure. In this work, unlike the other ones in this field, the developed numerical models had no initial crack or fracture, and the path of the crack and how the crack grows were studied without any pre-determination and presumption. The results obtained show that, in most cases, the crack starts from the central part of the sample, and is extended to its two ends. The crack extension direction was along the borehole axis inside the sample and perpendicular to the lateral stress. The numerical modeling results were well-consistent with the experimental ones, indicating that the pump capacity constraints in the laboratory could be overcome through numerical modelings.
Rock Mechanics
M. Lak; M. Fatehi Marji; A.R. Yarahamdi Bafghi; A. Abdollahipour
Abstract
The explosion process of explosives in a borehole applies a very high pressure on its surrounding rock media. This process can initiate and propagate rock fractures, and finally, may result in the rock fragmentation. Rock fragmentation is mainly caused by the propagation of inherent pre-existing fractures ...
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The explosion process of explosives in a borehole applies a very high pressure on its surrounding rock media. This process can initiate and propagate rock fractures, and finally, may result in the rock fragmentation. Rock fragmentation is mainly caused by the propagation of inherent pre-existing fractures of the rock mass and also from the extension of the newly formed cracks within the intact rock due to the explosion. In this work, the process of extension of blast-induced fractures in rock masses is simulated using the discrete element method. It should be noted that, in this work, fracture propagation from both the rock mass inherent fractures and newly induced cracks are considered. The rock mass inherent fractures are generated using the discrete fracture network technique. In order to provide the possibility of fracture extension in the intact rock blocks, they are divided into secondary blocks using the Voronoi tessellation technique. When the modeling is completed, the fracture extension processes in the radial and longitudinal sections of a borehole are specified. Then a blast hole in an assumed rock slope is modeled and the effect of pre-splitting at the back of the blast hole (controlled blasting) on the fracture extension process in the blast area is investigated as an application of the proposed approach. The modeling results obtained show that the deployed procedure is capable of modeling the explosion process and different fracture propagations and fragmentation processes in the rock masses such as controlled blasting.
F. Hadadi; B. Jodeiri Shokri; M. Zare Naghadehi; F. Doulati Ardejani
Abstract
In this paper, we investigate a probabilistic approach in order to predict how acid mine drainage is generated within coal waste particles in NE Iran. For this, a database is built based on the previous studies that have investigated the pyrite oxidation process within the oldest abandoned pile during ...
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In this paper, we investigate a probabilistic approach in order to predict how acid mine drainage is generated within coal waste particles in NE Iran. For this, a database is built based on the previous studies that have investigated the pyrite oxidation process within the oldest abandoned pile during the last decade. According to the available data, the remaining pyrite fraction is considered as the output data, while the depth of the waste, concentration of bicarbonate, and oxygen fraction are the input parameters. Then the best probability distribution functions are determined on each one of the input parameters based on a Monte Carlo simulation. Also the best relationships between the input data and the output data are presented regarding the statistical regression analyses. Afterward, the best probability distribution functions of the input parameters are inserted into the linear statistical relationships to find the probability distribution function of the output data. The results obtained reveal that the values of the remaining pyrite fraction are between 0.764% and 1.811% at a probability level of 90%. Moreover, the sensitivity analysis carried out by applying the tornado diagram shows that the pile depth has, by far, the most critical factors affecting the pyrite remaining
M. Esmailzadeh; A. Imamalipour; F. Aliyari
Abstract
The main aim of mineral exploration is to discover the ore deposits. The mineral prospectivity mapping (MPM) methods by employing multi-criteria decision-making (MCDM) integrate the exploration layers. This research work combines the geological, alteration, and geochemical data in order to generate ...
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The main aim of mineral exploration is to discover the ore deposits. The mineral prospectivity mapping (MPM) methods by employing multi-criteria decision-making (MCDM) integrate the exploration layers. This research work combines the geological, alteration, and geochemical data in order to generate MPM in the Kighal-Bourmolk Cu-Mo porphyry deposit. The overlaying of rock units and fault layers was used to prepare the geological layer. The remote sensing and geological studies were employed in order to create an alteration layer. For generating the geo-chemistry layer, the stream sediment and lithogeochemical data were utilized. The lithogeochemistry layer was categorized into 9 ones including Cu, Mo, Bi, Te, the alteration indices (e.g. potassic, phyllic, and propylitic), and the geochemical zonality indices (e.g. Vz1 and Vz2). In addition, the stream sediment layer was categorized into 6 layers including Cu, Mo, Bi, Te, and the geochemical zonality indices (e.g. Vz1 and Vz2). By examination of the created layers, the consistency of the potential areas was verified by field surveys. Afterward, the weights were assigned to each layer considering the conceptual model of porphyry copper systems. Consequently, the layers were integrated by the fuzzy gamma operator technique, and the final MPM was generated. Regarding the generated MPM, 0.86% of the studied area shows a high potential porphyry mineralization, and these areas are proposed for the subsequent exploration drilling locations.
Vanshika Bhardwaj; Kanwarpreet Singh
Abstract
Natural hazards are naturally occurring phenomena that might lead to a negative impact on the environment and also on the life of living beings. These hazards are caused due to adverse conditions of weather and climate events, and also due to certain human activities that are harmful to the environment. ...
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Natural hazards are naturally occurring phenomena that might lead to a negative impact on the environment and also on the life of living beings. These hazards are caused due to adverse conditions of weather and climate events, and also due to certain human activities that are harmful to the environment. Natural hazards include tsunamis, earthquakes, volcanic activity, landslides, etc. Among these natural hazards, landslides are among the most common natural hazards resulting in loss of life and property each year, leading to socio-economic impact; thus to avoid such losses, a comprehensive study of landslides is required. Landslides generally occur in hill region with steep slopes, heavy precipitation, loose shear strength of soil or due to many human activities like afforestation or construction activities. To resolve the problem of landslides in a hilly region, much research is conducted annually, providing a predicted landslide susceptibility zonation (LSZ) mapping of the area of research. The predicted landslide susceptibility maps are verified based on the past landslide data, an area under the curve (AUC), and other methods to provide an accurate map for landslide susceptibility in any area. In this study,93 research articles are reviewed for analysis of LSZ, and various observations are made based on the recent trends followed by various researchers over the world over the past ten years. The study can be useful for many researchers to practice their research on landslide susceptibility zonation.
M. Babaei; M. Abedi; Gh. H. Norouzi; S. Kazem Alilou
Abstract
This work presents the application of a geostatistical-based modeling approach for building up electrical properties acquired from a geophysical electrical tomography survey deployed for the purpose of porphyry Cu exploration at the Takht-e-Gonbad deposit, in the central domain of Iran. Electrical data ...
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This work presents the application of a geostatistical-based modeling approach for building up electrical properties acquired from a geophysical electrical tomography survey deployed for the purpose of porphyry Cu exploration at the Takht-e-Gonbad deposit, in the central domain of Iran. Electrical data were inverted in 2D along several profiles across the main favorable zones of Cu-bearing mineralization to image electrical resistivity and chargeability properties. Upon tight spatial correlation of these geophysical properties and Cu mineralization (i.e. Cu grade), electrical models were constructed in 3D through geostatistical interpolation of 2D inverted data to provide insights into the geometry of probable ore mineralization. Anomalous geophysical zone that was coincident simultaneously with higher values of electrical chargeability and resistivity, was in accordance with the main body of high Cu grades generated from exploratory drillings. It reveals that the porphyry-type Cu mineralization system in this area has strong geophysical footprints controlled mainly by rock types and alterations. Note that these physical models supply valuable pieces of information for designing the layout of further exploratory drillings, constructing geological characteristics, separating non-mineralized form mineralized zones, and resource modeling.
Exploration
Eid R. Abo-Ezz; El Sayed I Selim; Hatem Aboelkhair; Haytham Sehsah
Abstract
The bimodal hypsometry of the Arabian-Nubian Shield in the Neoproterozoic triggered the formation of post-amalgamation marine bains in the low-stand terranes of the Arabian shield (AS). The carbonate successions in the extraordinary marine basins in the AS are intruded by granite plutons of different ...
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The bimodal hypsometry of the Arabian-Nubian Shield in the Neoproterozoic triggered the formation of post-amalgamation marine bains in the low-stand terranes of the Arabian shield (AS). The carbonate successions in the extraordinary marine basins in the AS are intruded by granite plutons of different causative types, with major shear zones pathways. Therefore, the conditions for the formation of skarn deposits are mature at the contact of the carbonate succession with the causative granite plutons. Multidisciplinary approaches including ASTER data, Magnetic data, and geochemical data have been applied to the Murdama basin to locate the promising areas for skarn deposits. The Murdama basin has contrasting magnetic anomalies of different intensity at the contact between the Murdama limestone and the post-Murdama causative batholiths; significant magnetic anomalies exist at the contact with the Idah causative magmas. Lineaments related to the Najd fault system (NFS) exist eastward, where calc-silicate alteration-related minerals were evolved, with no clues for penetrative effect for such alteration activity along pathways related to the fracture system or at contact with the Abanat suite. Different spectral mapping techniques, including Spectral Information Divergence (SID), Spectral Angle Mapper (SAM), and Constrained Energy Minimization (CEM) confirm that the Idah suite is the predominant causative magma in the study area with highly evolved calc-silicate alteration-related minerals, such as wollastonite, garnet, and pyroxene. Meanwhile, The Idah suite has been identified as the main causative magma for other reduced skarn localities that have been recorded from the Murdama basin, i.e. the Qitan and An Nimriyah South. Alteration related mineral zones of kaolinite, chlorite, muscovite, and hematite are evolved alongside with calc-silicate minerals at the contact bewteen Idah suite, and the Murdama carbonate member. The geochemical data suggests reducing effect for the Idah suite at the contact between the Murdama carbonate succession and Idah plutons. These preliminary results of this study need detailed field investigations and geochemical explorations for the proposed skarn deposits in the Neoproterozoic molasse basins of the AS.
Exploitation
Taiwo Blessing Oamide; Adebayo Babatunde; Toluwase Daniel Olaiya
Abstract
This study developed and assessed several artificial intelligence (AI) models for predicting blast-induced toe volume in small-scale dolomite mines located in the Akoko Edo Local Government Area, Edo State, Nigeria. Seven predictive models were constructed: Adaptive Boosting (AdaBoost), Random Forest ...
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This study developed and assessed several artificial intelligence (AI) models for predicting blast-induced toe volume in small-scale dolomite mines located in the Akoko Edo Local Government Area, Edo State, Nigeria. Seven predictive models were constructed: Adaptive Boosting (AdaBoost), Random Forest (RF), Gaussian Process Regression (GPR), Support Vector Regression (SVR), a conventional Artificial Neural Network (ANN), and two Imperialist Competitive Algorithm-optimized ANNs (ICA-ANNs). The models were trained using eight input parameters including uniaxial compressive strength (UCS), spacing (S), burden (B), sub-drill (SB), drill hole length (DHL), stiffness ratio (SR), maximum instantaneous charge (MIC), and powder factor (K) with blast toe volume (TV) as the target output. Input data were collected through a combination of field measurements and laboratory analyses. Among all the models evaluated, the ICA-ANN with an 8-7-1 architecture achieved the highest predictive accuracy. It outperformed AdaBoost by 9.17%, SVR by 7.20%, GPR by 5.56%, RF by 4.75%, a standard ANN (8-5-1) by 0.78%, and a standard ANN (8-7-1) by 0.28%, based on mean squared error (MSE) and coefficient of determination (R²) metrics. Furthermore, the ICA-ANN model was applied to optimize blast design parameters. The optimal values obtained were: spacing = 1.0 m, burden = 0.8 m, sub-drill = 0.6 m, MIC = 0.72 kg, and powder factor = 0.65 kg/m³. These optimized parameters reduced the blast toe volume by 20.05%, from 209.50 m³ to 154.87 m³. The results highlight the robustness and efficiency of the ICA-ANN model for blast design optimization. By improving fragmentation quality and minimizing residual toe volume, the approach offers a practical pathway for enhancing both productivity and cost-effectiveness in small-scale mining operations.
Exploration
Abdelrahem Khalefa Embaby; Sayed Gomaa; Yehia Darwish; Samir Selim
Abstract
This study aims to develop an empirical correlation model for estimating the uranium content of the G-V in the Gabal Gattar area, northeastern desert of Egypt, as a function of the thorium content and the total gamma rays. Using the recent MATLAB software, the effect of selecting tan-sigmoid as a transfer ...
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This study aims to develop an empirical correlation model for estimating the uranium content of the G-V in the Gabal Gattar area, northeastern desert of Egypt, as a function of the thorium content and the total gamma rays. Using the recent MATLAB software, the effect of selecting tan-sigmoid as a transfer function at various numbers of hidden neurons was investigated to arrive at the optimum Artificial Neural Network (ANN) model. The pure-linear function was investigated as the output function, and the Levenberg-Marquardt approach was chosen as the optimization technique. Based on 1221 datasets, a novel ANN-based empirical correlation was developed to calculate the amounts of uranium (U). The results show a wide range of uranium content, with a determination coefficient (R2) of about 0.999, a Root Mean Square Error (RMSE) equal to 0.115%, a Mean Relative Error (MRE) of -0.05%, and a Mean Absolute Relative Error (MARE) of 0.76%. Comparing the obtained results with the field investigation shows that the suggested ANN model performed well.
