نشریه مهندسی منابع معدنی
سال هشتم شماره 2 (تابستان 1402)

This study considers the ability of log deviation data in reservoir zonation. In this regard, 110 m of carbonate rocks from one well of the Dariyan Formation in the central part of the Persian Gulf were investigated by using 390 thin sections, well log data, and core porosity and permeability. Facies analysis led to the identification of nine microfacies in five sub-environments. To evaluate the reservoir quality in each zone, petrophysical rock types were determined by flow zone indicator and electrofacies methods. Based on the flow zone indicator, six hydraulic flow units were obtained for the reservoir interval. Using the multi-resolution graph-based clustering method and petrophysical logs of gamma, neutron, and density, 5 electrofacies were identified. Then, the two methods were compared, which show a strong correlation at many depth intervals. Zone 1 with the high frequency of electrofacies and flow units with higher reservoir quality, has the best reservoir quality. Zone 2 has low reservoir quality, flow units, and electrofacies with high gamma radiation. The frequency of high-quality reservoir electrofacies in zone 3 is lower than in zone 1. To determine reservoir zonation by the standard deviation method, each log data was subtracted from the average in the whole well and then the obtained values were added together to calculate cumulative deviation. This method is consistent with the three zones of the Dariyan Formation, but as the method of determining rock types, it is not suitable for the separation of reservoir units.

Investments and progress of mining projects depend on the quantity and quality of mineral resources and reserves; therefore, it is significant to know the reliability of the ore deposit estimation based on various methods. This research has investigated the role of geostatistics and artificial neural networks in modeling, estimating the concentration of exploration blocks, and estimating mining reserves. Spatial distribution modeling of iron values has been performed using three methods of ordinary kriging, Gaussian simulation, and artificial neural networks. To construct the block model of ore deposit, 29 exploratory boreholes with an average depth of 142.75 meters and a total length of 4139.9 meters were used. After drawing the variograms, the search ellipse was calculated, and a 3D model was obtained to estimate the concentration by ordinary kriging and Gaussian sequential simulation methods. Also, modeling and estimating the concentration was done by the artificial neural network method. Results showed that the artificial neural network technique has high validity. Also, due to its ease of use and no need for extra variographic calculations can be an appropriate alternative to geostatistical and simulation approaches. Finally, based on different cut-offs, the concentration-volume curve was drawn. The results show that this ore body has 439 million tons of ore with an average concentration of 42 % per 20% cut-off concentration.

Chromite is one of the most used strategic metals. Among different types of Chromite deposits, Padiform Chromite is more considerable economically. On other hand, decision-making for mineral exploration investigation requires accurate estimation of the quality and quantity of new deposits. For estimation of the quality and quantity of deposits, quantitative mineral resource assessments are required. Quantitative mineral resource assessment is based on descriptive, density, and average grade-tonnage models. In this research, a three-part assessment method has been used to estimate podiform chromite deposits in Naeen’s Ophiolites. The three-Part assessment method is based on an inverse relationship between the permissive area for a specific deposit type and the number of deposits. Evaluation by the three-part assessment method shows that the understudy region is high potential. Results show a 50% chance of at least 19 deposits with at least 69400 metric tons of chromite & 10% chance of at least 40 deposits with at least 46700 tons of chromite existing in the understudy region. Geochemical anomalies have been used for validation. These anolmalies have been separated based on the concentration-area (C-A) and singularity index methods. At least three geochemical anomalies in the east margin of Naeen ophiolite were identified.

The first step for carrying out mining operations in surface mines is to build a network of communication routes to access different parts of the mine, and also transport ore and waste. For the successful design of ramps in open pit mines, it is necessary to evaluate and analyze the related safety risk based on the geological conditions, geomechanical characteristics, type of machinery, and the mine design. In this research, the ramp safety risk was investigated to determine the accident-prone zones.  In this regard, the information obtained from the exploration boreholes of the Chadormalu iron ore mine was used for modeling. At first, the economic block model of the mine and the ramp were modeled in different scenarios. After selecting the optimal ramp, the total length of the ramp was zoned at 100-meter distances to assess the safety risk in 42 zones, and to identify accident-prone zones by calculating the total risk index. Thus, by drawing a bow-tie diagram, the five initial events including wall instability, car crash, stone throwing, slippery, and accident were identified as the main events leading to incidents; then the probability and consequences severity of each initial event were determined. According to the results, the car crash and wall instability events have the most negative impact on the ramp safety. Also, the highest and the lowest values of the total risk index were 110 (in zones 37 and 42) and 5 (in zones 4, 5, and 9), respectively.

This study uses data modeling and text mining techniques for oil price predictions. To improve the model's explanatory capability, text features from internet news articles on crude oil are automatically extracted using convolutional neural networks. Additionally, various time series models employ a state analysis approach called convolution. The years 2021 to 2011 saw the collection of almost 13000 news items, and it was discovered that text mining and data from large Internet-based apps perform better for prediction than other approaches. This means that it is pretty fair to say that there is a parallel link between news headlines, those headlines, and searches in the Google search engine. This relationship is highly appropriate for correctly forecasting the price of crude oil.

Uniaxial Compressive Strength (UCS) of rock material is one of the most important and effective parameters in geotechnical and mining projects. Direct evaluation of UCS is expensive and time-consuming, therefore indirect tests such as point load, Schmidt hammer and sound wave velocity tests have been developed, among which the point load test is very commonly used, simple and economic. However, this method has limitations such as the effect of loading direction, the application of load to a small part of the rock and the high dependency of the results on the dimensions of the sample. In 2009, the Core Strangle Test (CST) was developed, which has the advantage of applying load through a circle perpendicular to the core axis. In this paper, the results of designing and manufacturing a CST machine, which has been performed for the first time in Iran, are described in order to estimate the UCS of rocks with high accuracy and low cost. The design and construction of the machine were done in the rock mechanics laboratory of Yazd University. In order to calibrate the machine, 70 standard rock and concrete samples with lengths of 20, 10 and 5 cm and a diameter of 54 mm were prepared. In addition to CST, point load and direct UCS tests were performed on these 70 specimens. Then, the relationship between UCS obtained by direct, CST and point load methods was investigated. Calculations showed that the relationship between UCS and machine oil pressure at the moment of failure in the CST method is a linear relationship with a correlation coefficient of 0.78 and the relationship between UCS and point load index is also linear with a correlation coefficient of 0.63.

Today, the adoption of green technologies and sustainable development has dragged more attention in the metallurgical industry. Accordingly, in this study, the leaching kinetics of chalcopyrite (CuFeS2) concentrate using 1-Butyl-3-methylimidazolium hydrogen sulfate (BmimHSO4) as an acidic ionic liquid was investigated. Effects of operational parameters including temperature, BmimHSO4 concentration, H2O2 concentration, solid-to-liquid ratio and particle size on the rate of copper dissolution from CuFeS2 were systematically examined. The results showed that the concentration of hydrogen peroxide and temperature had the greatest and the least effect on the dissolution of chalcopyrite, respectively. Also, the highest Cu extraction (ca. 97%) in this work was achieved using 40% BmimHSO4, 30% H2O2, and 10 g/L solid to liquid ratio for particle sizes less than 37 µm and 45 °C for leaching time of 180 min. Kinetics study using Shrinking Core Model (SCM) revealed that CuFeS2 leaching process using BmimHSO4 follows the chemical reaction-controlled process. In addition, the orders of reaction with respect to BmimHSO4 and H2O2 concentration, solid to liquid ratio, particle size were estimated to be 0.5386, 0.933, -0.676 and -1.1078, respectively. Under these circumstances, the activation energy and Arrhenius constant were 46.63 kJ/mol and 0.2596×106, respectively.

In this research, the separation of solid phase and water in the final tailings of the Zonouz kaolin processing circuit was investigated. The sedimentation of solid particles was investigated by changing different parameters and their effects were evaluated on the initial rate of sedimentation, clarity of clear water, viscosity, and density of the settled pulp. Increasing the pH improved the sedimentation rate, and the settled pulp became denser. Despite the increase in sedimentation rate, the clarity of clear water decreased due to the presence of fine suspended particles at high pH. The use of flocculant, even in a small amount, increased the initial sedimentation rate by six times and improved the clarity of clear water. However, the density of the sedimented part decreased due to the increase in pulp volume.