R. Gholami; A. Moradzadeh
Abstract
Reservoir permeability is a critical parameter for characterization of the hydrocarbon reservoirs. In fact, determination of permeability is a crucial task in reserve estimation, production and development. Traditional methods for permeability prediction are well log and core data analysis which are ...
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Reservoir permeability is a critical parameter for characterization of the hydrocarbon reservoirs. In fact, determination of permeability is a crucial task in reserve estimation, production and development. Traditional methods for permeability prediction are well log and core data analysis which are very expensive and time-consuming. Well log data is an alternative approach for prediction of permeability because they are usually available for all of the wells. Hence, attempts have been made to utilize well log data to predict permeability. However, because of complicate and non-linear relationship of well log and core permeability data, usual statistical and artificial methods are not completely able to provide meaningful results. In this regard, recent works on artificial intelligence have led to the introduction of a robust method generally called support vector machine (SVM). The term “SVM” is divided into two subcategories: support vector classifier (SVC) and support vector regression (SVR). The aim of this paper is to use SVR for predicting the permeability of three gas wells in South Pars filed, Iran. The results show that the overall correlation coefficient (R) between predicted and measured permeability of SVR is 0.97 compared to 0.71 of a developed general regression neural network. In addition, the strength and efficiency of SVR was proved by less time-consuming and better root mean square error in training and testing dataset.
Hasan Alizadeh; Mahnaz Nedaei; Negar Tirandaz
Abstract
One of the significant negative factors involved in exploiting granite stones as ornamental stones is the presence of heterogeneous fractures within the rock mass. Joints can either be destructive or beneficial in the production granite piles and building stone mines depending on their characteristics. ...
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One of the significant negative factors involved in exploiting granite stones as ornamental stones is the presence of heterogeneous fractures within the rock mass. Joints can either be destructive or beneficial in the production granite piles and building stone mines depending on their characteristics. This work focuses on evaluating the joints in the Divchal mine area of Kelardasht, north Iran. To get to that point, the main faults are surveyed from the aerial photograph, geological and tectonic maps, and field observations. According to this implementation, a density map of faults is provided for the entire studied area. The characteristics of the main joints including the length, slope, number, and orientation are collected in the mine area. The volumetric percentage of joints ( ) and joint set spacing ( ) parameters are computed at specific stations to identify suitable locations for granite extraction. The findings of this work suggest that the lower the value of ( < 10), the larger the blocks can be extracted. On the other hand, at the high values, the width of the extraction block increases. These conditions are typically found in locations far from the main faults where the density of joints is low, and as a result, the distance between joints is higher. The values > 60 indicate a crushed rock mass, and are typically observed in clay-free shear zones. It is recommended that the opening of the working face be avoided in situations near the main faults due to the fragmentation of rocks and denser joint spacing.
Mostafa Javid; Behzad Tokhmechi
Abstract
There are two methods for identifying formation interface in oil wells: core analysis, which is a precise approach but costly and time consuming, and well logs analysis, which petrophysists perform, which is subjective and not completely reliable. In this paper, a novel coupled method was proposed to ...
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There are two methods for identifying formation interface in oil wells: core analysis, which is a precise approach but costly and time consuming, and well logs analysis, which petrophysists perform, which is subjective and not completely reliable. In this paper, a novel coupled method was proposed to detect the formation interfaces using GR logs. Second approximation level (a2) of GR log gained from optimum mother wavelet decomposition was used for formation interface detection. Short time Fourier transform (STFT) of a2 was gained since the window band was fixed in the entire of well depths. Inverse STFT of various windows of transformed data was gained, which creates various signals in depth domain. To this end, a novel formulation was developed to obtain modified signal for formation interface detection. The mean of various resulted signals creates a smooth signal the logarithm well of which highlights formation interfaces. Synthetic data were used to test the applicability of proposed algorithm. Accordingly, GR logs corresponding to five different wells located in an oilfield in south of Iran also were used to investigate the accuracy and applicability of the proposed method. Lastly, the validation process took place by comparing the results of core data analysis and the proposed method. Good agreements were obtained between these approaches, demonstrating the applicability of the proposed methodology.
M. Hemmatian; B. Tokhmchi; V. Rasouli; R. Gholami
Abstract
A good knowledge of the parameters causing casing damage is critically important due to vital role of casing during the life of a well. Cement sheath, which fills in the gap between the casing and wellbore wall, has a profound effect on the resistance of the casing against applied loads. Most of the ...
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A good knowledge of the parameters causing casing damage is critically important due to vital role of casing during the life of a well. Cement sheath, which fills in the gap between the casing and wellbore wall, has a profound effect on the resistance of the casing against applied loads. Most of the empirical equations proposed to estimate the collapse resistance of casing ignore the effects of the cement sheath on collapse resistance and rather assume uniform loading on the casing. This paper aims to use numerical modeling to show how a bad cementing job may lead to casing damage. Two separate cases were simulated where the differences between good and bad cementation on casing resistance were studied. In both cases, the same values of stresses were applied at the outer boundary of the models. The results revealed that a good cementing job can provide a perfect sheath against the tangential stress induced by far-field stresses and reduce the chance of casing to be damaged.
Asghar Azizi; Ali Dehghani; Seyyed Zioddin Shafaei
Abstract
AbstractThe purpose of this study was to investigate the controllable operating parameters influence, including pH, solid content, collector, co-collector, and depressant dose, and conditioning time, on apatite flotation kinetics. Four first order flotation kinetic models are tested on batch flotation ...
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AbstractThe purpose of this study was to investigate the controllable operating parameters influence, including pH, solid content, collector, co-collector, and depressant dose, and conditioning time, on apatite flotation kinetics. Four first order flotation kinetic models are tested on batch flotation time-recovery profiles. The results of batch flotation tests and the fitting of first-order kinetic models to assess the influence of operating parameters on the flotation kinetics indicated that model with fast and slow - floating components and classical model gave the best and the worst fit for experimental data, respectively. Also, rectangular distribution of floatabilities and gamma distribution of floatabilities fitted the experimental data well. In this study, the model with rectangular distribution of floatabilities associated with fractional factorial experimental design was employed to evaluate the effect of six main parameters on kinetic parameters (R_∞, K). The result indicated that linear effects of depressant dose, conditioning time, and the interaction effects of solid concentration and pH statistically were important on ultimate recovery but the significant parameters for flotation rate constant were linear effects of solids content, depressant dosage and the interaction effect between pH and conditioning time. Regression equations obtained to relate between flotation operation and kinetic parameters.
Hamid Khoshdast
Abstract
A new parametric model was developed for predicting cut point of hydraulic classifiers. The model directly uses operating parameters including pulp flowrate, feed particle size characteristics, pulp solids content, solid density and particles retention time in the classification chamber and also covers ...
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A new parametric model was developed for predicting cut point of hydraulic classifiers. The model directly uses operating parameters including pulp flowrate, feed particle size characteristics, pulp solids content, solid density and particles retention time in the classification chamber and also covers uncontrollable errors using calibration constants. The model applicability was first verified using a bench scale classifier and then, validated at industrial scale for a coal classifier. Results showed that the new model can predict the cut point more precisely compared to the conventional Masliyah model, i.e. the accuracy values of 80% and 37% for the new and Masliyah models, respectively. Sensitivity study showed that the model was extremely sensitive to the particle size distribution of feed while being least sensitive to the particles retention time.
M. Hosseini Nasab
Abstract
In this research work, the parameters affecting the settling velocity within the thickeners were studied by introducing an equivalent shape factor. Several thickener feed samples of different densities including copper, lead and zinc, and coal were prepared. The settling tests were performed on the samples, ...
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In this research work, the parameters affecting the settling velocity within the thickeners were studied by introducing an equivalent shape factor. Several thickener feed samples of different densities including copper, lead and zinc, and coal were prepared. The settling tests were performed on the samples, and the corresponding settling curves were plotted. Using the linear regression analysis, the Chein's equation was fitted to the experimental data in order to obtain the equivalent shape factors for the different minerals. Moreover, the relations between the equivalent shape factors and the settling parameters were investigated. The R-squared values for the fits proved the capability of the Chein’s equation to fit well on the experimental data (0.96
M. Mohebbi; A.R. Yarahmadi Bafghi; M. Fatehi Marji; J. Gholamnejad
Abstract
Presence of joints and fractures in rocks strongly influences the behavior of the rock mass by dividing the media into smaller units. These structures intensify the potential instability besides the development of sliding and rotational movements. The assumption of discontinuum media changes the whole ...
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Presence of joints and fractures in rocks strongly influences the behavior of the rock mass by dividing the media into smaller units. These structures intensify the potential instability besides the development of sliding and rotational movements. The assumption of discontinuum media changes the whole analysis conditions in relation to the continuum analysis. Acquisition of geometrical and structural discontinuity data alongside their mechanical properties is of paramount importance in a rock mass analysis. Orientation, spacing, expansion, and other geometrical characteristics of the rock mass and their relative geometrical position to the studied projects influence the pattern and potential of failure. Therefore, inevitably, the first step involved in the analysis of rock mass is geometric data collection of the discontinuities as a crucial step before analysis. In this study, the traditional data collection methods in structural discontinuities with their disadvantages are reviewed. Then the discontinuity data collection based on digital image analysis is developed and applied in a case study to several walls of the Choghart iron ore mine. The results obtained show that this method has a very good accuracy in assessing the fine structures, and also it collects data in a much shorter time. This study, therefore, suggests that the proposed method can be used as a practical approach.
Exploitation
M. Jamshidi; M. Osanloo
Abstract
The block economic value (BEV) of a single-metal deposit is calculated based on the metal content and the related costs. The common methods available for calculating BEV are just based upon the profitable elements, and the effects of undesirable elements on BEV are not considered. However, in multi-element ...
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The block economic value (BEV) of a single-metal deposit is calculated based on the metal content and the related costs. The common methods available for calculating BEV are just based upon the profitable elements, and the effects of undesirable elements on BEV are not considered. However, in multi-element deposits, the effects of other elements existing in the blocks on BEV should be considered with the purpose of optimizing the blending. These elements and blending methods have considerable effects on the quality of the final product. In this paper, a new approach is introduced to determine BEV in multi-element deposit with two types of profitable and penalty elements by considering the effect of blending on BEV. Consequently, the ultimate pit limits (UPLs) will be determined based on these conditions. The developed model is tested in the Gol-e-Gohar No.2 iron-ore mine, and the mine UPLs is determined. The results obtained showed that the mineable reserve of the pit increased by 3% when the effects of both types of elements are considered. In order to investigate the effect of grade uncertainty on BEV, twenty realizations of the ore block are generated using the sequential Gaussian simulation approach. The UPLs of all the realizations are determined using the developed BEV-calculation method, and the pit limits with different probabilities of occurrence are determined. The total mineable reserve varied between 20,380 and 46,410 million tons. The exploitation of mine should start with the smallest pit (100% probability). The largest pit should be considered as a guide for surface-facility locating.
Exploitation
B. Tokhmechi; S. Ebrahimi; H. Azizi; Seyed R. Ghavami-Riabi; N. Farrokhi
Abstract
Recognition of ore deposit genesis is still a controversial challenge for economic geologists. Here, this task was addressed by the virtue of Bayesian data fusion (BDF) implementing available proofs: semi-schematic examples with two (Cu and Pb + Zn) and three (Cu, Pb + Zn and Ag) evidences. The data, ...
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Recognition of ore deposit genesis is still a controversial challenge for economic geologists. Here, this task was addressed by the virtue of Bayesian data fusion (BDF) implementing available proofs: semi-schematic examples with two (Cu and Pb + Zn) and three (Cu, Pb + Zn and Ag) evidences. The data, in current paper are just concentrations of indicated elements, were collected from Angouran’s deposit in Iran at prospecting and general exploration stages. BDF was used for discrimination between three geneses of Massive Sulfide, Mississippi and SEDEX types. Better genesis recognition with clear discrimination between the geneses was achieved by BDF as compared with earlier studies. The results showed that uncertainties were reduced from 50% to less than 30% and deposit recognition was improved greatly. Furthermore, we believe that using more properties can have a beneficial effect on the overall outcome. The comparison made between 2 and 3 properties showed that the amount of probable belonging values to any type of deposit was greater in 3 properties. It was also confirmed that using the completed information from the various stages of exploration progress can be amplified and be used for genesis recognition via BDF.
G. Kulekci; A. Osman Yilmaz; M. Çullu
Abstract
The aim of this work is to obtain recycled aggregate (RA) from construction debris in order to reduce the rapid consumption of aggregate resources and the environmental impact of these resources. In order to fulfill this aim, the density, porosity, Schmidt hardness test, uniaxial compression resistance, ...
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The aim of this work is to obtain recycled aggregate (RA) from construction debris in order to reduce the rapid consumption of aggregate resources and the environmental impact of these resources. In order to fulfill this aim, the density, porosity, Schmidt hardness test, uniaxial compression resistance, carbonation depth, and ultrasonic p-wave velocity experiments were conducted on different construction debris transported by trucks from 9 different points in Turkey. In addition, the debris samples taken were broken down to the size of the aggregate and subjected to the tests of density, porosity, moisture content, freeze-thaw, and impact resistance. As a result of the conducted experiments, the lowest mass loss as a result of freezing-thawing was in GRA with 9.36%, the highest mass loss was in ORA with 22.58%, the highest ORA average aggregate impact strength index was 21.27%, and the lowest TRA aggregate impact strength index was found to be 18.26%. İt was determined that most of the physical properties of RA obtained from the construction wreckage was within the limit values specified in the literature and that the recycled aggregates could be used instead of natural aggregate. With this work and these results, RA obtained could be used in many areas such as concrete aggregate in the construction sector, underground filling in mining, filling material in gunned concrete, and filling materials on highways.
Kwang Hyok Kim; Tok Hyong Han; Un Chol Han; Ryo Myong Hong
Abstract
This paper focuses on a study concerned with estimation of the platform motion at the lower loading station in the Trucklift slope hoisting system with varying profile of track. The TruckLift slope hoisting system is an innovative transport technology for open-pit mines, and considerably accelerates ...
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This paper focuses on a study concerned with estimation of the platform motion at the lower loading station in the Trucklift slope hoisting system with varying profile of track. The TruckLift slope hoisting system is an innovative transport technology for open-pit mines, and considerably accelerates and cheapens transport from mine. When a truck drives onto or drives off the platform at the lower loading station in the Trucklift slope hoisting system with varying profile of track, the platform motion influences the operation of the Trucklift slope hoisting system, and the configuration of inclined rope hitched to the platform is varied. The simulation result by using the ADAMS (Automatic Dynamic Analysis of Mechanical Systems) software shows that the horizontal distance between lower loading station and platform varies when a truck drives onto or off the platform and the initial horizontal distance that is the distance between lower loading station and platform when the winder is applied the brake, can be an important factor in operation of the Trucklift slope hoisting system with varying profile track.
S. Alamdari; M.H. Basiri; A. Mousavi; A. Soofastaei
Abstract
The haul trucks consume a significant energy source in open-pit mines, where diesel fuel is widely used as the main energy source. Improving the haul truck fuel consumption can considerably decrease the operating cost of mining, and more importantly, reduce the pollutants and greenhouse gas emissions. ...
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The haul trucks consume a significant energy source in open-pit mines, where diesel fuel is widely used as the main energy source. Improving the haul truck fuel consumption can considerably decrease the operating cost of mining, and more importantly, reduce the pollutants and greenhouse gas emissions. This work aims to model and evaluate the diesel fuel consumption of the mining haul trucks. The machine learning techniques including multiple linear regression, random forest, artificial neural network, support vector machine, and kernel nearest neighbor are implemented and investigated in order to predict the haul truck fuel consumption based on the independent variables such as the payload, total resistance, and actual speed. The prediction models are built on the actual dataset collected from an Iron ore open-pit mine located in the Yazd province, Iran. In order to evaluate the goodness of the predicted models, the coefficient of determination, mean square error, and mean absolute error are investigated. The results obtained demonstrate that the artificial neural network has the highest accuracy compared to the other models (coefficient of determination = 0.903, mean square error = 489.173, and mean absolute error = 13.440). In contrast, the multiple linear regression exhibits the worst result in all statistical metrics. Finally, a sensitivity analysis is used to evaluate the significance of the independent variables.
Environment
S. Abbaszade; F. Mohammad Torab; A. Alikhani; H. Molayemat
Abstract
In geochemical exploration, there are various techniques such as univariate and multivariate statistical methods available for recognition of anomalous areas. Univariate techniques are usually utilized to estimate the threshold value, which is the smallest quantity among the values representing the anomalous ...
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In geochemical exploration, there are various techniques such as univariate and multivariate statistical methods available for recognition of anomalous areas. Univariate techniques are usually utilized to estimate the threshold value, which is the smallest quantity among the values representing the anomalous areas. In this work, a combination of the Sequential Gaussian Simulation (SGS) and Gap Statistics (GS) methods was utilized as a new technique to estimate the threshold and to visualize the anomalous regions in the Hararan area, which is located in SE Iran, and consists of copper mineralization that seems to be connected to a porphyry Cu-Mo system. Furthermore, the most important advantage of this method is the reliable assessment of the anomalous areas. In other words, the anomalous areas were discriminated in terms of their probability values. The regions with high probability values were reliable and appropriate to locate the drilling points for a detailed exploration. It not only decreases the risk, cost, and time of exploration but also increases the drilling point reliability and precision of reserve estimation after drilling. In this research work, the results of analysis of 607 lithogeochemical samples for the element Cu were used. The SGS method was performed on the transformed data and 50 realizations were obtained. In the next step, the back-transformed realizations were utilized to obtain an E-type map, which was the average of 50 realizations. Moreover, the results of the GS method showed that the Cu threshold value was 228 ppm in the area. Therefore, using the E-type map, areas with values greater than 228 ppm were introduced as the anomalous areas. Finally, the probability map of the exceeding threshold values was acquired, and the anomalous districts located in the southern part of the studied area were considered as more reliable regions for future detailed exploration and drilling.
Mohammad Reza Garmsiri; Hassan Haji Amin Shirazi
Abstract
The results of batch settling tests (BST) are used to investigate settling behavior of solids suspension, which contribute to sizing thickeners. Conventional methods in analyzing BST on the basis of visual and graphical procedures lead to sub-optimally sized and selected thickeners. A computational approach ...
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The results of batch settling tests (BST) are used to investigate settling behavior of solids suspension, which contribute to sizing thickeners. Conventional methods in analyzing BST on the basis of visual and graphical procedures lead to sub-optimally sized and selected thickeners. A computational approach based on quantitative analysis of BST can be beneficial. About 300 settling experiments were performed by varying conditions, including solids concentration, type and dosage of chemical aids. Solid samples were collected from iron, copper, coal, lead and zinc tailings and feed streams. Settling curves based on experimental data considering extreme limits were generated and analyzed. Therefore, a mathematical model, h(t), is introduced to define batch settling curves. Furthermore, it is shown that, on settling velocity curves a maximum value is likely to occur (except in extreme conditions such as very high or very low solids concentration suspensions or extremely high dosage of flocculant). In addition, to compare batch settling curves quantitatively, an index, Ii, based on parameters which can be obtained from the model h(t), is developed. The proposed model and index can simply be utilized in a computerized approach of settling curves analysis.
Amid Morshedlou; Hesam Dehghani; Seyed Hadi Hoseinie
Abstract
Utilizing the gathered failure data and failure interval data from Tabas coal mine in two years, this paper discusses the reliability of powered supports. The data sets were investigated using statistical procedures and in two levels: the existence of trend and serial correlation. The results show that ...
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Utilizing the gathered failure data and failure interval data from Tabas coal mine in two years, this paper discusses the reliability of powered supports. The data sets were investigated using statistical procedures and in two levels: the existence of trend and serial correlation. The results show that the powered supports follow the Gamma reliability function. The reliability of the machine decreases to almost zero after 520 operation hours and after 80 hours the probability of failure of powered supports increases to 60 percent. The failure rate of powered support shows an improving behavior and therefore a decreasing failure rate. In the beginning of the process, the failure rate is 0.021 failures per hour. This reaches the rate of 0.012 after a sudden decrease, thence forward on a gently decreasing rate and after 100 hours gets to the rate of 0.01. Regarding the maintenance policy and to protect the machine’s operation continuity, preventive maintenance strategy can be chosen. The reliability of the discussed machine can be maintained on a descent level by inspecting and controlling the parts in short term intervals. With regard to reliability plots of powered supports operation, preventive reliability-based maintenance time intervals for 80% reliability levels for powered supports is 15 hours.
F. Khorram; H. Memarian; B. Tokhmechi; H. Soltanian-zadeh
Abstract
In this study based on image analysis, an ore grade estimation model was developed. The study was performed at a limestone mine in central Iran. The samples were collected from different parts of the mine and crushed in size from 2.58 cm down to 15 cm. The images of the samples were taken in appropriate ...
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In this study based on image analysis, an ore grade estimation model was developed. The study was performed at a limestone mine in central Iran. The samples were collected from different parts of the mine and crushed in size from 2.58 cm down to 15 cm. The images of the samples were taken in appropriate environment and processed. A total of 76 features were extracted from the identified rock samples in all images. Neural network used as an intelligent tool for ore grade estimation and the features of every image were combined with weighted average method. In order to feature dimensional decrease, principal component analysis method was used. Six principal components, which were extracted from the feature vectors, captured 90.661% of the total feature variance. Components were used as the input to neural network and four grade attributes of limestone (CaCO3, Al2O3, Fe2O3 and MgCO3) were used as the output. The root of mean squared error between the observed values and the model estimated values for the test data set are 6.378, 4.847, 0.1513 and 0.0284, the R2 values are 0.7852, 0.8663, 0.7591and 0.8094 for the mentioned chemical composition respectively. The magnitude of R2 indicates the correlation between actual and estimated data. Therefore, it can be inferred that the model can successfully estimate the limestone chemical compositions percentage.
M. Noroozi; R. Kakaie; Seyed M. E Jalali
Abstract
Fault zones and fault-related fracture systems control the mechanical behaviors and fluid-flow properties of the Earth’s crust. Furthermore, nowadays, modeling is being increasingly used in order to understand the behavior of rock masses, and to determine their characteristics. In this work, fault ...
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Fault zones and fault-related fracture systems control the mechanical behaviors and fluid-flow properties of the Earth’s crust. Furthermore, nowadays, modeling is being increasingly used in order to understand the behavior of rock masses, and to determine their characteristics. In this work, fault zones and fracture patterns are reviewed, and also comprehensive studies are carried out on the fracture geometry and density variations. A model to describe damage zones around the strike-slip faults is developed, in which the range of damage zone styles commonly found around strike-slip fault zones are shown. A computer code, named DFN-FRAC3D, is developed for the two- and three-dimensional stochastic modeling of rock fracture systems in fault zones. In this code, the pre-existing and fault-related fractures are modeled by their respective probability distributions, and the joint density may be varied by the distance from the fault core. This work describes the theoretical basis and the implementation of the code, and provides a case study in the rock fracture modeling to demonstrate the application of the prepared code.
H. Moeini; A. Aryafar
Abstract
Anomaly recognition has always been a prominent subject in preliminary geochemical explorations. Among the regional geochemical data processing, there are a range of statistical and data mining techniques as well as different mapping methods, which serve as presentations of the outputs. The outlier’s ...
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Anomaly recognition has always been a prominent subject in preliminary geochemical explorations. Among the regional geochemical data processing, there are a range of statistical and data mining techniques as well as different mapping methods, which serve as presentations of the outputs. The outlier’s values are of interest in the investigations where data are gathered under controlled conditions. These values in exploration geochemistry indicate the mineralization occurrences, and therefore, their identification is vital. Both the robust parametric (based on Mahalanobis distance) and non-parametric (based on depth functions) techniques have been developed for a multivariate outlier identification in geochemistry data. In this research work, we applied the local multivariate outlier identification approach to delineate the geochemical anomaly halos in the Hamich region, which is located in the SE of Birjand, South Khorasn province, East of Iran. For this purpose, 396 litho-geochemical samples that had been analyzed for 44 elements were used. The obtained results show a good agreement with the geological and mineral indices of Pb, Zn, and Cu in the southern part of the area. Such studies can be used by a project director to optimize the core drilling places in detailed exploration steps.
Mineral Processing
M. Heshami; R. Ahmadi
Abstract
The aim of this work is to investigate the effect of thermal treatment on the grinding behavior of manganese ore in the various size fractions of -1.7+1.18, -1.18+0.6, -0.6+0.3 and -0.3+ 0.15 mm. Breakage Function Determination Software (BFDS) is used to calculate the selection function of the experiment. ...
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The aim of this work is to investigate the effect of thermal treatment on the grinding behavior of manganese ore in the various size fractions of -1.7+1.18, -1.18+0.6, -0.6+0.3 and -0.3+ 0.15 mm. Breakage Function Determination Software (BFDS) is used to calculate the selection function of the experiment. The results of SEM analysis show the micro-cracks in the thermally treated manganese sample, and DTA/TG analysis show that heating at 750 °C leads to dehydroxylation of montmorillonite, and decomposition of calcite and decomposition of montmorillonite to silicate minerals occur at 850 °C. Montmorillonite mineral with a hardness of 2 is turned into silicate minerals with an average hardness of 7. Therefore, it can be seen that the thermal treatment leads to a decrease in the specific rate of breakage from 1.04 min-1 to 0.65 min-1 (approximately to 37%) for a size fraction of -0.300+ 0.15 mm. It; can be expressed that the thermally treated sample is broken more slowly than the untreated sample. Also, parameter “A” is the maximum Si value, decreasing for the heated sample from 4.36 min-1 to 4.28 min-1. The selection function results show that all size fractions of this material follow a first-order kinetics.
M. Adil; S. Raza; I. Amin
Abstract
Despite the slope stability measures, rock falls are witnessed at section KM-37 of the Swat motorway (M-16), Khyber Pakhtunkhwa, Pakistan. The geotechnical data analysis of the site reveals that although the chances of plane/slope failures are reduced from 43% to 23% with the help of the existing design, ...
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Despite the slope stability measures, rock falls are witnessed at section KM-37 of the Swat motorway (M-16), Khyber Pakhtunkhwa, Pakistan. The geotechnical data analysis of the site reveals that although the chances of plane/slope failures are reduced from 43% to 23% with the help of the existing design, still there are possibilities of rock fall at the sight, which has also been witnessed during the field visits. The rock fall hazards are assessed through field tests and simulation, and significant stabilization measures are suggested. The rock fall tests are conducted, and then using the data obtained, the rock fall simulation is carried out using GeoRock 2D®. From a combination of the kinematic analysis and rock fall simulation, the hazard level along the slope ranges from moderate to high. The reason for this is the increasing velocity of the falling boulder and the impact of energy at the bottom of the slope. This is an indication of the risk, as the most hazardous area is at the toe of the slope, where the highway road is the main element at risk. Rock boulders of different shapes and sizes are released from a couple of benches in order to check their impacts on the highway. Based on the simulation, it is concluded that the spherical shaped boulders are released from higher benches covering more horizontal distances and reaching the highway with a higher bouncing heights at the toe of the slope than the cylindrical shaped boulders. The maximum bounce height of 7 m has been recorded at the toe of the slope. In order to reduce the impacts of energy and bounce heights of the boulders striking the slope surface, certain mitigation measures are suggested like a ditch of a specific size filled with sand or fine debris at the toe of the slope. Draping wire mesh on the slope surface and a retaining wall or fence would be greatly helpful and economical to reduce the rock falling hazards along the road side at section KM-37 of the Swat motorway.
M. Moghadasi; A. Nejati Kalateh; M. Rezaie
Abstract
Gravity data inversion is one of the important steps in the interpretation of practical gravity data. The inversion result can be obtained by minimization of the Tikhonov objective function. The determination of an optimal regularization parameter is highly important in the gravity data inversion. In ...
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Gravity data inversion is one of the important steps in the interpretation of practical gravity data. The inversion result can be obtained by minimization of the Tikhonov objective function. The determination of an optimal regularization parameter is highly important in the gravity data inversion. In this work, an attempt was made to use the active constrain balancing (ACB) method to select the best regularization parameter for a 3D inversion of the gravity data using the Lanczos bidiagonalization (LSQR) algorithm. In order to achieve this goal, an algorithm was developed to estimate this parameter. The validity of the proposed algorithm was evaluated by the gravity data acquired from a synthetic model. The results of the synthetic data confirmed the correct performance of the proposed algorithm. The results of the 3D gravity data inversion from this chromite deposit from Cuba showed that the LSQR algorithm could provide an adequate estimate of the density and geometry of sub-surface structures of mineral deposits. A comparison of the inversion results with the geologic information clearly indicated that the proposed algorithm could be used for the 3D gravity data inversion to estimate precisely the density and geometry of ore bodies. All the programs used in this work were provided in the MATLAB software environment.
Mineral Processing
M. Jahani Chegeni; S. Kolahi
Abstract
The shell liner type, rotation speed, and ball filling percent are the key factors influencing the charge behavior inside the SAG mills, and consequently, their performance. In this work, the milling operation of industrial SAG mills is investigated using the Discrete Element Method (DEM). First, an ...
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The shell liner type, rotation speed, and ball filling percent are the key factors influencing the charge behavior inside the SAG mills, and consequently, their performance. In this work, the milling operation of industrial SAG mills is investigated using the Discrete Element Method (DEM). First, an industrial SAG mill with dimensions of 9.50 m × 4.42 m that has a Smooth-type liner is simulated. Then by changing the liner types, i.e. Wave, Rib, Ship-lap, Lorain, Osborn, and Step liners, six other independent simulations are performed. In order to investigate the impact mechanism and improve the mill performance, two new parameters called ‘head height’ and ‘impact zone length’ are introduced. Then the effects of the mill shell liner type on those parameters at two different mill speeds, i.e. 70% and 80% of its critical speed (CS), are evaluated. Also for validation of the simulation results, a laboratory-scale SAG mill with dimensions of 57.3 cm × 16.0 cm is simulated. The results obtained indicate that the Osborn liner, due to the angularity of its lifters and their proper number and thickness, performs best because it increases both parameters more than the other liners. Thus this liner is recommended as the best and optimal liner in this research work and is suggested for installation inside the industrial SAG mills. Also the Wave liner, due to its specific geometrical shape and its wavy lifters as well as their low number and inadequate thickness, provides the lowest charge ‘head height’. Therefore, it is not recommended to install this liner inside the industrial SAG mills. Meanwhile, comparison of the simulations related to the laboratory-scale SAG mill with the experimental results demonstrates a good agreement that validates the DEM simulations and the software used.
Exploitation
R. Shamsi; M. S. Amini; H. Dehghani; M. Bascompta; B. Jodeiri Shokri; Sh. Entezam
Abstract
This paper attempted to estimate the amount of flyrock in the Angoran mine in Zanjan province, Iran using the gene expression programming (GEP) predictive technique. The input data, including flyrock, mean depth of the hole, powder factor, stemming, explosive weight, number of holes, and booster were ...
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This paper attempted to estimate the amount of flyrock in the Angoran mine in Zanjan province, Iran using the gene expression programming (GEP) predictive technique. The input data, including flyrock, mean depth of the hole, powder factor, stemming, explosive weight, number of holes, and booster were collected from the mine. Then, using GEP, a series of intelligent equations were proposed to predict flyrock distance. The best GEP equation was selected based on some well-established statistical indices in the next stage. The coefficient of determination for training and testing datasets of the GEP equation were 0.890 and 0.798, respectively. The model obtained from the GEP method was then optimized using teaching– learning-based optimization algorithm (TLBO). Based on the results, the correlation coefficient of training and testing data increased to 91% and 89%, which increased the accuracy of the Equation. This new intelligent equation could forecast flyrock resulting from mine blasting with a high level of accuracy. The capabilities of this intelligent technique could be further extended to the other blasting environmental issues.
M. Mohammadi Behboud; A. Ramezanzadeh; B. Tokhmechi
Abstract
Multiplicity of the effective factors in drilling reflects the complexity of the interaction between rock mass and drilling bit, which is followed by the dependence of parameters and non-linear relationships between them. Rock mass or, in other words, the formation intended for drilling, as the drilling ...
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Multiplicity of the effective factors in drilling reflects the complexity of the interaction between rock mass and drilling bit, which is followed by the dependence of parameters and non-linear relationships between them. Rock mass or, in other words, the formation intended for drilling, as the drilling environment, plays a very essential role in the drilling speed, depreciation of drilling bit, machines, and overall drilling costs. Therefore, understanding the drilling environment and the characteristics of the in-situ rock mass contributes a lot to the selection of the machines. In this work, a 1D geo-mechanical model of different studied wells is built by collecting the geological data, well logs, drilling data, core data, and pressure measurements of the formation fluid pressure in various wells. Having the drilling parameters of each part of the formation, its specific energy is calculated. The specific energy index can be used for predicting the amount of energy consumed for drilling. In order to find the relationship between the drilling specific energy (DSE) and its effective parameters, the multivariate regression model is used. Modeling DSE is done using the multivariate regression, which contains the parameters rock characteristics, well logs, and a combination of these two features. 70% and 30% of the data are, respectively, selected as the training and test for validation. After analyzing the model, the correlation coefficients obtained for the training and test data were, respectively, found to be 0.79 and 0.83. The parameters uniaxial compressive strength (UCS), internal friction angle, and fluid flow are among the most important factors found to affect DSE.
