Exploration
Shaghayegh Esmaeilzadeh; Ali Moradzadeh; omid Asghari; Reza Mohebian
Abstract
Seismic inversion is a critical technique for estimating the spatial distribution of petro-elastic properties in the subsurface, based on the seismic reflection data. This work introduces an iterative geostatistical seismic inversion method, designed to address challenges in complex geological settings ...
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Seismic inversion is a critical technique for estimating the spatial distribution of petro-elastic properties in the subsurface, based on the seismic reflection data. This work introduces an iterative geostatistical seismic inversion method, designed to address challenges in complex geological settings by incorporating self-updating local variogram models. Unlike the conventional approaches that rely on a single global variogram or fixed local variograms, the proposed method dynamically updates the spatial continuity models at each iteration using automatic variogram modeling and clustering of variogram parameters. The optimal number of clusters is determined using three cluster validity indices: Silhouette Index (SI), Davies-Bouldin Index (DB), and Calinski-Harabasz Index (CH). The method’s effectiveness was evaluated using a three-dimensional non-stationary synthetic dataset, demonstrating robust convergence when employing the SI and CH indices, with both achieving a high global correlation coefficient of 0.9 between the predicted and true seismic data. Among these, the CH index provided the best balance between the computational efficiency and inversion accuracy. The results highlight the method’s ability to effectively capture local spatial variability, while maintaining a reasonable computational cost, making it a promising approach for seismic inversion in complex sub-surface environments.
F. Khorram; O. Asghari; H. Memarian; A. Hoseein Morshedy; X. M. Emery
Abstract
The key input parameters for mine planning and all subsequent mining activities is based on the block models. The block size should take into account for the geological heterogeneity and the grade variability across the deposit. Providing grade models of smaller blocks is more complex and costly than ...
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The key input parameters for mine planning and all subsequent mining activities is based on the block models. The block size should take into account for the geological heterogeneity and the grade variability across the deposit. Providing grade models of smaller blocks is more complex and costly than larger blocks, but larger sizes cannot represent areas with high spatial variability accurately. Hence, a unique block size is not an optimal solution for modeling a mine site. This paper presented a novel algorithm to create an adaptive block model with locally varying block sizes aiming to control dilution and ore loss in Sungun porphyry copper deposit of Iran with a complex geometry characterized by multiple dikes. Three grade block models with different block sizes and simulated by direct block simulation are the inputs of algorithm. The output is a merged block model, assigning the smaller blocks to the complex zones, such as ore-waste boundaries, and larger blocks to the continuous and homogeneous zones of the ore body. The presented algorithm is capable to provide an accurate spatial distribution model with a fewer number of blocks in comparison to the traditional block modeling concepts.
S. Talesh Hosseini; O. Asghari; Seyed A. Torabi; M. Abedi
Abstract
An accurate modeling of sophisticated geological units has a substantial impact on designing a mine extraction plan. Geostatistical simulation approaches, via defining a variogram model or incorporating a training image (TI), can tackle the construction of various geological units when a sparse pattern ...
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An accurate modeling of sophisticated geological units has a substantial impact on designing a mine extraction plan. Geostatistical simulation approaches, via defining a variogram model or incorporating a training image (TI), can tackle the construction of various geological units when a sparse pattern of drilling is available. The variogram-based techniques (derived from two-point geostatistics) usually suffer from reproducing complex and non-linear geological units as dyke. However, multipoint geostatistics (MPS) resolves this issue by incorporating a training image from a prior geological information. This work deals with the multi-step Single Normal Equation Simulation (SNESIM) algorithm of dyke structures in the Sungun Porphyry-Cu system, NW Iran. In order to perform a multi-step SNESIM algorithm, the multi-criteria decision-making and MPS approaches are used in a combined form. To this end, two TIs are considered, one for simulating dyke structures in the shallow depth, and two for simulating dyke structures in a deeper depth. In the first step, a TI is produced using geological map, which has been mined out during the previous exploration operations. After producing TI, the 35 realizations are simulated for the shallow depth of deposit in the area under study. To select the best realization (as a TI for the next step) of the simulation results, several statistical criteria are used and the results obtained are compared. To this end, a hybrid multi-criteria decision-making is designed on the basis of a group of statistical criteria. In the next step, the dyke structures in the deeper depth are also simulated by the new TI.
Exploitation
S. Salarian; O. Asghari; M. Abedi; S. K. Alilou
Abstract
This work aims at figuring out the spatial relationships between the geophysical and geological models in a case study pertaining to copper-sulfide mineralization through an integrated 3D analysis of favorable target. The Ghalandar Skarn-Porphyry Cu Deposit, which is located in NW Iran, is selected for ...
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This work aims at figuring out the spatial relationships between the geophysical and geological models in a case study pertaining to copper-sulfide mineralization through an integrated 3D analysis of favorable target. The Ghalandar Skarn-Porphyry Cu Deposit, which is located in NW Iran, is selected for this research work. Three geophysical surveys of direct current electrical resistivity and induced polarization tomography along with magnetometry are performed to construct the physical properties of electrical resistivity, chargeability, and magnetic susceptibility, respectively. Inverse modeling and geostatistical interpolation are utilized to generate the physical 3D models. A 3D model of Cu grade is generated using ordinary kriging; however, the indicator kriging method is run to design a 3D model of rock types through incorporating the drilling results. Block models of geophysical and geological characteristics are cast in a similar 3D mesh to investigate their relationships in copper mineralization. A concentration-volume multi-fractal method is utilized to divide each model into its sub-sets, where the most productive portions in association with Cu-bearing mineralization are distinguished. Note that sub-sets of geophysical models are spatially matched with geological models of Cu grade and rock types. The zones with low electrical resistivity, high chargeability, and low magnetic susceptibility correspond to the main source of Cu mineralization in a dominated skarn rock type setting.
Exploitation
I. Masoumi; Gh.R. Kamali; O. Asghari
Abstract
Dilution can best be defined as the proportion of waste tonnage to the total weight of ore and waste in each block. Predicting the internal dilution based on geological boundaries of waste and ore in each block can help engineers to develop more reliable long-term planning designs in mining activities. ...
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Dilution can best be defined as the proportion of waste tonnage to the total weight of ore and waste in each block. Predicting the internal dilution based on geological boundaries of waste and ore in each block can help engineers to develop more reliable long-term planning designs in mining activities. This paper presents a method to calculate the geological internal dilution in each block and to correct the ultimate grade of each geological block according to the internal dilution values that have already been calculated for each one of them. In this regard, the input data is first indexed based on the lithological logs of drill holes. The occurrence probabilities of ore and waste in each block are calculated via 100 realizations using the sequential indicator simulation. Dilution is computed as the ratio of waste rock tonnage to the total tonnage of ore and waste. Furthermore, joint simulation of the continuous variables is performed for each mining block using the minimum/maximum auto-correlation factors. In the next step, for each block, the final grade variables including iron and iron oxide are computed by considering the calculated internal dilution. These analyses are applied to the Gohar Zamin iron ore deposit, and the actual internal dilution calculated based on the lithological logs of blast holes is compared with the same values obtained based on the proposed method in each block. The results obtained were found to be satisfactory.
Exploitation
H. Rahimi; O. Asghari; F. Hajizadeh; F. Meysami
Abstract
The purpose of this work is to compare the linear and non-linear kriging methods in the mineral resource estimation of the Qolqoleh gold deposit in Saqqez, NW Iran. Considering the fact that the gold distribution is positively skewed and has a significant difference with a normal curve, a geostatistical ...
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The purpose of this work is to compare the linear and non-linear kriging methods in the mineral resource estimation of the Qolqoleh gold deposit in Saqqez, NW Iran. Considering the fact that the gold distribution is positively skewed and has a significant difference with a normal curve, a geostatistical estimation is complicated in these cases. Linear kriging, as a resource estimation method, can be problematic and gives an unrealistic gold grade. In order to check and correct the errors in the linear methods, the non-linear kriging method has been deployed. One of the applicant's non-linear estimation methods is Indicator Kriging (IK). The IK method converts grade values into binary units of 0 and 1 using multiple thresholds that can be selected by the number-size (N-S) fractal model. The N-S model identifies important and critical thresholds based on the grade distribution. In IK, the Multiple Indicator Kriging (Multiple IK) and Median Indicator Kriging (Median IK) methods could be involved due to the number of indicator thresholds. IK is not sensitive to high values. Here, we make a comparison between Median IK and Multiple IK as well as those with ordinary kriging (OK), which is a linear kriging method. Overall, we conclude that all of these methods are suitable for resource estimation among these methods, although the IK method is better for estimation in different categories of gold grades.
Exploitation
S. Talesh Hosseini; O. Asghari; Seyed R. Ghavami Riabi
Abstract
Due to the existence of a constant sum of constraints, the geochemical data is presented as the compositional data that has a closed number system. A closed number system is a dataset that includes several variables. The summation value of variables is constant, being equal to one. By calculating the ...
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Due to the existence of a constant sum of constraints, the geochemical data is presented as the compositional data that has a closed number system. A closed number system is a dataset that includes several variables. The summation value of variables is constant, being equal to one. By calculating the correlation coefficient of a closed number system and comparing it with an open number system, one can see an increase in the values of the closed number system, which is false. Such features of this data prevent the application of standard statistical techniques to process the data. Therefore, several methods have been proposed for transforming the data from closed to open number systems. There are various geostatistical methods consisting of estimation and simulation methods in order to model a deposit. Geostatistical simulations can produce various models for a deposit with different probability percentages. The most applicable geostatistical simulation method is the sequential Gaussian simulation technique, which is highly flexible. In this work, 392 Litho-geochemical data of the Baghqloom region of Kerman in Iran consisting of 20 elements were at first converted using an open number system. Afterwards, the elements that were helpful for exploring the area and were normally standard were simulated for 100 times. After the simulations, the valid output was chosen using geostatistical validation. The maps derived from the simulations revealed the enriched concentrations of mineralization elements in the central regions.
M. Doustmohammadi; A. Jafari; O. Asghari
Abstract
Water inflow is one of the most important challenges in the underground excavations. In addition to inducing working conditions and environmental problems, it decreases the stability and quality of the surrounding rocks. The direct method of measuring rock mass hydraulic conductivity consists of drilling ...
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Water inflow is one of the most important challenges in the underground excavations. In addition to inducing working conditions and environmental problems, it decreases the stability and quality of the surrounding rocks. The direct method of measuring rock mass hydraulic conductivity consists of drilling the boreholes and observing the rate of fluid lost in the boreholes. Applying this method is still problematic due to the depth of underground spaces, and also the groundwater level covering them. Therefore, many researchers have tried to predict the water inflow indirectly. This paper attempts to predict the groundwater conditions in the Beheshtabad tunnel (in Iran) using the fuzzy inference system based on the datasets acquired from the preliminary exploration studies. 250 datasets for the Beheshtabad tunnel were used out of which, 200 datasets were used to develop the model and 50 were used to validate the results obtained. 90% accuracy was obtained through comparing the fuzzy estimation and actual groundwater conditions. The proposed model can be used with much less degree of complexity for prediction of the groundwater conditions as well as decreasing the overall costs of the exploration measurements, and due to these characteristics, it is applicable for most users.
Omid Asghari
Abstract
Post-mineralization activities may cause difficulties in the process of ore modeling in porphyry deposits. Sungun, NW Iran, is one of the porphyry copper deposits, in which dyke intrusions have made ore modeling more complicated than expected. Among different kinds of dykes, two types were chosen and ...
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Post-mineralization activities may cause difficulties in the process of ore modeling in porphyry deposits. Sungun, NW Iran, is one of the porphyry copper deposits, in which dyke intrusions have made ore modeling more complicated than expected. Among different kinds of dykes, two types were chosen and the consequent geostatistical analyses were applied on. In this study, simple directional variograms were used for extracting relevant information from dyke systems on which the Sequential Indicator Simulations were applied consequently. One hundred realizations were produced on the simulation grid considering the anisotropy characteristics and E-type map has been provided averaging all realizations. Moreover, a binary state between dyke and non-dyke environments was produced putting threshold on the E-type grid node values to discriminate the ore from barren dykes. Hole-effect models were fitted to the empirical variograms perpendicular to the dyke strike. Dimensional information was elicited from these models and the results were compared with the previously carried out geological investigations, and finally a good numerical match was found between these two sources of information.
H. Rezaee; O. Asghari; J.K. Yamamoto
Abstract
A simple but novel and applicable approach is proposed to solve the problem of smoothing effect of ordinary kriging estimate which is widely used in mining and earth sciences. It is based on transformation equation in which Z scores are derived from ordinary kriging estimates and then rescaled by the ...
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A simple but novel and applicable approach is proposed to solve the problem of smoothing effect of ordinary kriging estimate which is widely used in mining and earth sciences. It is based on transformation equation in which Z scores are derived from ordinary kriging estimates and then rescaled by the standard deviation of sample data and the sample mean is added to the result. It bears the great potential to reproduce the histogram and semivariogram of the primary data. Actually, raw data are transformed into normal scores in order to avoid asymmetry of ordinary kriging estimates. Thus ordinary kriging estimates are rescaled using the transformation equation and after that back-transformed into the original scale of measurement. For testing the proposed procedure stratified random samples have been drawn from an exhaustive data set. Corrected ordinary kriging estimates follow the semivariogram model and back-transformed values reproduce the sample histogram, while keeping local accuracy.
