International Journal of Mining & Geo-Engineering
Volume:58 Issue: 1, Winter 2024

The ventilation design of mines is based on fluid dynamics. Air is the main fluid in mining ventilation. This fluid is analyzed by two models: incompressibility and compressibility. The air-fluid in the compressibility model is examined in two models of dry and wet air along with thermal analysis. This paper argues that a number of presented parameters in the common thermodynamic analysis of mine ventilation should be modified. Accordingly, issues of the Earth's true gravity acceleration, potential energy difference, the specific heat capacity of air at constant pressure and volume, enthalpy difference of air, the average volumetric mass of dry air, and the amount of output moisture are rechecked. Therefore, a new method is presented in this paper for correcting thermodynamic equations in mine ventilation design. The name of this method is the Complete Model of Wet Air Analysis (CMWAA method). The results of this paper show that the CMWAA method can accurately perform thermodynamic analysis of air-fluid in mine ventilation without requiring a specified evaporation rate in mine networks, with minimal iteration of calculations.

The productivity of the quarry during the wet season heavily depends on how well the personnel adjusts to the mine's environmental conditions and management plans. The improvement of granite production through workers' impact identification and mining advancement decision-making in Ondo State, Nigeria, has been considered in this study. The rate of granite production and the factors influencing workers’ efficiency were assessed using a well-structured survey and descriptive-analytic technique. To improve the production rate, the Multiple Criteria Decision-Making (MCDM) technique was used to select the most productive pit depending on a number of key labor impact factors. Health and safety in employment, the energy crisis, market conditions and level of competition, on-site accidents, natural disasters, and language barriers were some of the factors identified as external influencer factors affecting mine labor efficiency in granite quarrying. Finally, using the criteria's significance through the inter-criterion (CRITIC) approach, the mine workers’ influence on production was estimated and utilized for the best pit selection. The result of the MCDM revealed that the five pits (Pit 1, Pit 2, Pit 3, Pit 4, and Pit 5) had the following decision performance scores: 0.659, 0.617, 0.5, 0.5, and 0.5, respectively. This made Pit 1 the best production pit to be considered during the rainy season. The optimal solution was validated with the 2021 production report. The report shows that production from Pit 1 had the highest revenue of $16,000 Per annum, the lowest dewatering cost, and the highest production rate compared to the other four pits.

Loss of copper minerals to tailings of the rougher and scavenger circuits is one of the challenges in copper concentration plants, which reduces the efficiency of the circuit. The goal of this research is to utilize mineralogy-based techniques to identify the cause of the loss of copper minerals to tailings of the scavenger circuit. Process mineralogy studies have been performed on the scavenger of the flotation circuit - the Sungun copper concentration plant (located in northwestern of Iran). First, the feed, final concentrate, and tailing, as well as the concentrate and tailing flows of each of the scavenger circuit cells were sampled at different time intervals. Then, chemical composition analysis, laser particle size distribution analysis, and optical microscopy studies were performed on them. According to the results, the presence and changes in the abundance of copper oxide minerals, which make up about 45% of copper minerals, is one of the main reasons for the copper loss to tailings. Also, fine-grained particles of copper sulfide minerals (d80~45 µm), and the interlocking of copper sulfide minerals, especially chalcopyrite, with pyrite and gangue minerals (silicate), are among the most important causes of increased copper grade in the scavenger circuit tailings. In addition, the malfunction of the scavenger circuit cells due to the simultaneous presence of sulfide and oxide minerals and their fineness is another cause of the lost to tailings.

Loss of copper minerals in the tailings of the rougher and scavenger circuits poses a significant challenge in copper processing plants, diminishing the circuit's efficiency. Part I of this paper identified the causes of copper mineral loss in the scavenger circuit tailings of the Sungun copper concentration plant, situated in northwestern Iran. Changes in feed composition, particularly the ratio of copper oxide to sulfide minerals, along with alterations in the mineralogical properties of the input feed to the scavenger circuit, emerged as pivotal factors contributing to the loss of copper minerals into the tailings. In line with these findings, the objective of the present paper (part II) is to optimize the scavenger circuit by proposing a solution to mitigate the loss of copper minerals to the tailings. Samples were collected from the feed, concentrate, and final tailings, as well as from each cell of the scavenger circuit, followed by comminution and flotation tests on each sample. The results indicate that redirecting the scavenger circuit tailings to the input of the rougher cells, owing to their higher copper grade compared to the tailings of the rougher circuit, can enhance the circuit's recovery by more than 4%. Additionally, employing a combination of sulfide and oxide collectors, along with sulfidation to float the copper oxide minerals in the scavenger circuit, resulted in an overall recovery increase exceeding 11%. Furthermore, adjusting the size of the air bubbles to capture fine copper mineral particles from the scavenger circuit cells proved to be an effective strategy for boosting recovery. Moreover, modifying the grinding circuit to liberate the minerals present in the scavenger circuit feed, predominantly the concentrate of the scavenger circuit itself, led to a recovery increase of approximately 5%. Considering the mineralogical characteristics of the scavenger circuit feed, derived from the tailings of the cleaner cells, implementing changes in the operating conditions of the cleaner circuit—such as employing hybrid bubbles (Nano and coarse bubbles) and utilizing sulfide and oxide collectors—significantly impacted the recovery of fine copper mineral particles and copper oxide minerals to the cleaner concentrate, thereby enhancing the scavenger circuit's performance.

The properties of metallic minerals and metallic minerals-electrolyte interface have always been a concern in the induced polarization (IP) geophysical method due to their effects on the IP response. Electrochemical reactions, if carried out, affect the interface characteristics. Hence, the occurrence of the reactions and their effects on the IP signal have been modeled through recent research, but they are not well-known yet. Identifying these matters can help to create more realistic physical and petrophysical models, for a better explanation of IP effects. So, in the present study, 11 metallic mineral samples and the laboratory method named bipolar electrochemistry, introduced for the first time to the IP research field, have been used to show the performance of electrochemical reactions at the interface and the effect of various metallic minerals on them. The results showed that if the applied external electric potential is high enough, electrochemical reactions are carried out at the metallic minerals-electrolyte interface. In this study, these reactions were electrolysis of water and were carried out in all minerals (except sphalerite). However, the potential required to initiate the reactions was different for different minerals. The lack of water electrolysis reaction on the surface of sphalerite can probably be attributed to its non-conductivity. On the other hand, the external potential responsible for the interface reactions was linearly linked to the potential difference between the two sample’s extremities. Considering the different potentials required to start the reactions in various samples-electrolyte interfaces, and the absence of these reactions in the case of sphalerite samples, it can be concluded that the samples’ compounds affect the reactions and their commencing potentials. So, we believe that by studying these reactions, some properties of the metallic minerals can be achieved. Identifying the minerals’ properties and the reactions that can occur at their surfaces is essential for a detailed understanding of the factors affecting the IP phenomenon. To do this, we found bipolar electrochemistry as an appropriate way.

In this study, the geological and petrophysical methods were combined to investigate the reservoir characteristics of the Asmari Formation in one of the gas fields in the Persian Gulf. The key focus of this study is to categorize rock types and define reservoir zonation. Initially, sedimentary facies were identified through the analysis of the core samples and the petrographic studies. Subsequently, the depositional environments of each facies were interpreted. After assessing the reservoir quality of sedimentary facies, various rock typing methods, including FZI, R35, and Lucia methods, were used to categorize the reservoir rocks. Finally, reservoir zonation was carried out based on the integration of information and the NCRQI method. According to this study, the Asmari Formation in the studied field consists of 10 sedimentary facies deposited in a carbonate ramp environment during the Rupelian and Chattian stages. From the perspective of frequency, coralgal reef facies play a significant role in this platform, while from a reservoir standpoint, the thin-bedded ooid grainstones are the most important reservoir facies. The high variability in porosity and permeability data for each facies indicates the importance of diagenetic changes in reservoir quality and porosity distribution. A comparative analysis of rock typing methods revealed that the reservoir rock is composed of five reservoir rock types, associated with different sedimentary facies, pore sizes, and reservoir properties. Finally, based on the integration of geological and petrophysical information, the reservoir rock was divided into five reservoir zones, with reservoir zones As-2 and As-4 being the most important due to their relatively high porosity and permeability.

Long-term production planning for open-pit mines is recognised as one of the vital decision-making issues in open-pit mining operations. In addition, the ore grade is one of the most significant sources of uncertainty in a mining operation, as it classified run-of-mine material into ore and waste. In the classical approach, the destination of mining blocks is determined by comparing the estimated grade with a pre-determined cut-off grade. However, the uncertainty of material grade dramatically affects production planning. In this paper, a novel model was developed based on the idea of simulating the grade to incorporate the risk of grade uncertainty. In the proposed model, the economic consequences of the assigned destination are calculated using the profit and loss functions and they are integrated with the production scheduling. The proposed production planning was implemented in an iron ore mine, and the results were discussed for classical, loss, and profit models. Results show that the net present value increases by 3.64% by implementing the profit function. In contrast, the loss function method reduces the net present value by 2.23% compared to the classic model. This happens because the amount of ore class is increased by 7.46% using the profit function method and decreased by 2.49% using the loss function method. Additionally, the coefficient of variation, as an index of uncertainty, was investigated. The results show that the loss function approach attempts to extract more reliable blocks in the early years and postpone the high-uncertain blocks to the later years of the production.

As the depth of mineral exploration has increased in recent years, multiple exploration methods have become necessary to obtain more accurate depth and surface data. Each type of exploratory data has different uncertainty, resolution, and efficiency levels. Using these data individually or preparing traditional models based on a single data type often fails to meet the desired accuracy level. Therefore, mineral prospectivity mapping (MPM) has become more common in integrating these data. MPM methods require determining the importance of the data used. This importance is expressed as the weight of the layers (evidence). Typically, data-driven methods cannot be used to determine the weight of evidence layers in green areas due to the need for sufficient deposits. In these areas, knowledge-based methods, using the opinions of expert geologists, are often used to determine the weight of the layers. However, the weights determined by different experts may vary depending on their perspectives. Therefore, one of the challenges of using MPM methods in green areas is determining a reliable weight for the layers. This paper uses different exploration data, such as airborne geophysical data, geochemistry, geology, and remote sensing data, to prepare suitable reference layers. Due to the limited mineral prospects available in this area, we used the prediction-area (P-A) method to calculate the layers' weights without experts' opinions. We then used these weights to produce the gold prospectivity map in this area using the multi-index overlay (MIO) and the (Adjusted, Conventional, and Modified) TOPSIS methods. Finally, the obtained results were used to evaluate the efficiency of these methods and the calculated weights for this area.

The concentration of sulfide minerals can be achieved through various methods, and one such method is flotation. In the case of cobaltite, a mineral composed of cobalt sulfoarsenide, its ability to float is attributed to the presence of sulfur within its lattice structure. Cobalt, a versatile element with historical applications in dyeing, has gained strategic importance in recent times due to its utilization in alloys and lithium batteries. However, the scarcity of cobaltite in the Earth's crust has limited the extent of research conducted on its flotation. Nonetheless, previous studies have indicated that under specific conditions, cobaltite can indeed be floated. The objective of this particular study was to separate cobaltite minerals from magnetite and other associated minerals through the process of flotation. Initially, preliminary tests were conducted using Minitab software and Taguchi analysis. These tests revealed that the highest recovery rate, approximately 71%, was achieved at acidic pH levels (pH=4) using PAX as the collector. Subsequent additional tests were carried out, resulting in a recovery rate of 75% and a grade of 22.3%. One of the significant findings of this study was the influence of pH on the recovery of cobaltite when sulfhydryl collectors were employed. It was observed that cobaltite exhibited a considerably low recovery rate when the pH approached neutral or alkaline values.

In this study, a novel numerical approach is proposed to characterize the dissolution of rock minerals and wormhole propagation in carbonate rocks using the Darcy scale model. Accordingly, only the spatial variables of the governing partial differential equations are discretized, while the time variable remains continuous. Consequently, the partial differential equations are turned into ordinary ones, which are then numerically solved by high-order Runge-Kutta methods. The proposed approach is verified against the analytical solution in a 1D core model. Afterwards, it will be utilized to investigate the effect of multiple transport and reaction phenomena on the matrix acidizing in 2D carbonate formations. Also, the staggered grid technique is employed to accurately predict the wormhole patterns during several injection regimes. Compared to the previous studies, the proposed numerical approach is less complicated and straightforward. Furthermore, the computational cost is more affordable.

The primary aim of this study was to define the final pit boundaries utilizing the maximum flow Pseudoflow method in an open-pit mining context. Our methodology encompassed exploratory data analysis (EDA), establishing geomechanical and economic factors, and assessing the final pit. The study was conducted using Python 3.11 and SGeMS 3.0. We discovered that our block model comprised 480,000 blocks of 10x10x10 m dimensions. We generated 20 pits with revenue factors between 0.1 to 2, increasing by increments of 0.1. The Study indicated that pit 20 was optimal, with an estimated NPV of 17855 MUSD, extracting 212 million tons of ore and 58 million tons of waste rock, achieving a stripping ratio based on block model and market conditions, and is subject to change with further block sequencing analysis. Nevertheless, pit 20 emerged as the most advantageous when considering economic feasibility, given its high estimated NPV and favorable stripping ratio.

Utilizing the aggregate piers is one of the methods to improve and increase the bearing capacity of soft soils. The ultimate bearing capacity of these piers is affected by parameters such as the physical properties of the piers, structural conditions, the embedment depth and replacement ratio of piers, which complicates the estimation of bearing capacity. In this study, the Gene Expression Programming method was used for the prediction of the ultimate bearing capacity of clay soils reinforced with aggregate piers. For this purpose, two different models were developed, of which the first model (GEP2) utilized two input variables, the undrained shear strength of clay (Su) and replacement ratio (ar), while the second model (GEP4) used four input variables including the undrained shear strength of clay (Su), replacement ratio (ar), slenderness ratio (Sr), and embedment depth of piers (df). The coefficient of determination of the GEP2 model, and the GEP4 model is 0.921 and 0.942, respectively. Besides, comparing the GEP4 model of this research with the developed models of previous studies confirms the superior performance of the GEP4 model, considering both the accuracy and number of input parameters. The results of sensitivity analysis showed that the undrained shear strength of clay (Su), replacement ratio (ar), slenderness ratio (Sr), and embedment depth of piers (df) have the highest impact on the prediction of bearing capacity, respectively. Furthermore, the parametric analysis demonstrated that increasing the Su, ar, Sr, and df would improve the bearing capacity of the aggregate piers reinforced clay.