فهرست مطالب پیمان افضل

The study area is situated 21 km SW of Ardestan city and 80 km NE of Esfahan (Central Iran). and according to the sedimentary structural divisions (Fig. 1; Aghanabati, 1998) in the central part of Urumieh-Dokhtar Magmatic Belt (UDMB) The UDMB in the Alpine-Himalayan orogenic belt, the most productive metallic belt of Iran, composed of basic to acidic volcanic and plutonic rocks, tuff and agglomerate. The UDMB represents geochemical characteristics of subduction zones with features of calc-alkaline locally toward alkaline (Berberian and Berberian, 1981; Alavi, 1994; Shahabpour, 2007; Omrani et al., 2008; Ghorbani and Bezenjani, 2011; Yeganehfar, 2013; Rajabpour et al., 2017). The UDMB hosts several porphyry Cu±Mo±Au deposits including Sungun, Sarcheshmeh, Kahang, Darehzar, Nowchun and Meiduk (Atapour and Aftabi, 2007; Zarasvandi et al., 2015; Zamanian et al., 2016; Alirezaei et al., 2017; Jamali, 2017) and associated porphyry copper-gold, gold epithermal and manganese-iron deposits (Rajabpour et al., 2017; Ostadhosseini et al., 2018; Alaminia et al., 2020; Ostadhosseini et al., 2021). Different stages of Cenozoic magmatic activity in the middle segment of the UDMB around the study area consist of different successions of volcanic and intrusive rocks (Radfar, 1998). The Eocene to Miocene diorite- monzodiorite bodies were intruded the Eocene volcanic and subvolcanic rocks. In the middle of the area, these intrusive units are juxtaposed with a fault boundary (Marbin fault) adjacent to Eocene volcanic units. 
 
The Eocene volcanic stage is dominated by basalt, andesitic basalt, andesite, tuffs and ignimbrites rocks. Quaternary sediments are widespread in the northeastern and southern parts of the area. The oldest rock unit of this area is the Shotori dolomite formation trending NW-SW and belonging to Triassic age and located in the southwest of the study area. Cu mineralization occurs within the Eocene volcano-sedimentary sequence. The purpose of this study is to determine the type of Cu mineralization based on the mineralization characteristics, geometry, texture, structure and alteration studies, as well as the geochemistry and tectonic environment of the host volcanic rock.
For the purposes of this study, 60 thin sections of volcanic rocks and 30 polished thin sections of ore samples were studied by a standard petrographic microscope under reflected and transmitted lights. 10 surface and drill–holes samples from volcanic rocks were crushed and powdered in tungsten carbide swing mill for whole-rock analysis. The chemical analyses were performed for the major elements using X-ray fluorescence (XRF) and trace elements using Inductively Coupled Plasma-Mass Spectrometry (ICP-MS). Electron microprobe analyses were performed, using a JXA-8100 electron microprobe. Operating conditions were 35 kV accelerating voltage, a beam current of 20 nA, and a beam diameter of 2-10 μm.
All the petrographic studies as well as chemical analyses including XRF, ICP-MS and EPMA were carried out at the Seoul National University Laboratories, Seoul, South Korean.
The dominant rocks of the area under study are basalt, basaltic andesite, andesite and a small volume of pyroclastic rocks which are metaluminous composition and calc-alkaline affinity. Geochemically, they are enriched in LREE relative to HREE, enrichment of LILE and negative anomalies of HFSE (i.e., Nb, Ti), pointing to characteristics of subduction-related magmatic possibly generated by partial melting of metasomatized lithospheric mantle source. As the discrimination diagrams of tectonic setting display, the volcanic rocks are also classified as a subduction-related magmatic arc. Alteration zones were developed in the rock types including silicic, propylitic, argillic, sericitic and zeolitic. The propylitic and silicic alterations were extended within the mineralized zones. The propylitic alteration is the dominant alteration consisting mainly epidote, chlorite, and calcite. The silicification zone consists of crystalline quartz-formation, which occurs as veins and veinlets including some copper minerals. The carbonate alteration is observed in basaltic andesite and andesite rocks. Copper mineralization is mainly strata-bound, and occurs partially as veins, veinlets and disseminated in the andesite, basaltic andesites, and basaltic rocks. Based on microscopic studies, three mineralization stages were recognized in the Rahimabad deposit including pre-mineralization, mineralization, and post-mineralization stages. In the pre-mineralization stage, pyrite is formed in decreasing conditions in the host rock. In the main mineralization stage, pyrite is replaced by primary Cu and Ag sulfide minerals such as chalcopyrite, bornite, chalcocite, digenite, jalpaite and acanthite. Finally, in the post mineralization stage, copper sulfide minerals are replaced by secondary copper sulfide minerals (chalcocite, covellite and digenite) and oxide minerals (malachite, azurite, goethite and hematite).
The Rahimabad Cu (Ag) deposit lies in the SW of the Ardestan city in the Urumieh-Dokhtar Magmatic Belts, Central Iran. In this area, Cu and Ag mineralization is observed in the volcano-sedimentary rocks. The copper (Ag) mineralization occurs in andesite, basaltic andesite and basaltic lavas. These rocks are meta-aluminous and have a calc-alkaline affinity and indicate a subduction-related magmatic arc. The main alterations zones are silicic, propylitic, argillic, sericitic and zeolitic. The geometry of mineralization is strata-bound and the texture and structure of mineralization is open space filling, disseminated, vein-veinlet and replacement. Based on microscopic as well as EPMA data, the most important Cu and Ag minerals include chalcopyrite, bornite, chalcocite- covellite group minerals, malachite, azurite, acanthite and jalpaite, which are accompanied by magnetite and hematite. Pyrite is mostly observed as a separate mineral in the host rock. The overall mineralization characteristics and tectonic setting, the type of host rock, geometry, texture and structure, mineralogy and the paragenetic of Cu minerals and finally the alteration zones with different types of copper deposits document that the Rahimabad copper deposit share many features with those of Manto type copper deposits.
Acknowledgment
The present study was financially supported by the Cu-Au company of Ardestan. The authors are grateful to Mr. Sharif for providing sampling facilities and let us access to drill cores and exploration data.

The aim is to use the Concentration-Volume (C-V) fractal model to identify high-quality parts of coal seams based on sulfur and ash concentrations. In the K1 and K7 coal seams in the North Kochakali coal deposit, 5 and 6 different populations of ash and sulfur content were obtained based on the results. According to this model, sulfur and ash concentrations below 1.81% and 33.1% for the K7 seam, and below 4.46% and 37.1% for the K1 seam, respective base on Russian standard for ash and high sulfur content of North Kochakali coals were considered as appropriate values. In order to identify the high-quality parts of K1 and K7 coal seams, plans at different depths were used based on the C-V fractal model. Plans at different depths suggests that the southern part of the K1 seam and the northern part of the K7 seam have the highest-quality based on sulfur and ash concentrations, which should be considered in the extraction operation. The logratio matrix was used to compare the results of the C-V fractal model with the geological data of pyrite veins and coal ash. This matrix indicates that sulfur content above 3.8% for the K7 seam and above 4.41% for the K1 seam have good and very good correlation with pyritic veins of geological data, respectively. There are good overall accuracy (OA) values in the correlation between parts of the seam with ash concentration above 37.1% and 45.7% for the K1 and K7 seams, respectively, and the coal ash obtained from the geological data.

In this research, the leaching of REEs from the tailing of the apatite-iron ore processing unit of Morvarid mine (NW Iran), has been investigated using nitric, hydrochloric and sulfuric acids. This tailing contains rare earth elements (REEs) specifically Ce, La, Nd, Y and its accompanying minerals are magnetite, apatite, monazite, hematite, quartz. The appropriate dimensions for apatite release are 80-75μm. Leaching tests were performed for all three acids, and digestion process was also used for sulfuric acid. The leaching in the presence of sulfuric acid, under a temperature of 90°C, an acid concentration of 40% and a time of 60 minutes, leads to the total recovery of REE equal to 40.23%, and in acid sulfuric acid digestion at 200°C, equal to 61.21%. became. The recovery of REE when using hydrochloric acid at 72.64°C, concentration of hydrochloric acid 36.21% and time 56.28 minutes, was equal to 60.57%. In the presence of nitric acid, under the optimal conditions of temperature 61.51°C, acid concentration 40% and time 72.92 minutes. Furthermore, the maximum recovery of total REE equal to 51.9% was obtained. Due to the higher recovery and the lower price of sulfuric acid, this method is suggested for extracting for the extraction of REEs from the tailings.

The Fatehabad Cu deposit is located in the Khorasan Razavi province, 35 km SE of the Torbat-e Heydariyeh and in the Khaf-Kashmar-Bardaskan metal belt. The vein and veinlet mineralization consist of chalcopyrite, pyrite, magnetite, chalcocite, bornite, covellite, malachite and iron oxides associated with siliceous-sericite, argillite and propylitic alteration in the volcanic rocks formed parallel to the sub-faults that branch off from the Dorouneh fault. The similar pattern of REE and trace elements in the mineralized veins and associated volcanic rocks suggests an magmatic-hydrothermal origin of the ore elements. In the vein system of Fathabad district, quartz, pyrite, chalcopyrite, and magnetite veins with propylitic alteration in the early stage of mineralization, quartz, pyrite, chalcopyrite and magnetite veins with sericite alteration in the main stage of mineralization and quartz, pyrite and chalcopyrite veins were identified along with argillic and iron oxide alterations. Calcite veins along with sericite and iron oxide alterations were also identified in the late stage of mineralization. The enrichment of trace, LREEs/HREEs ratio, positive Eu anomalyand negative Ce anomaly, indicate reducing conditions and a high pH of the mineralized fluids. Fluid inclusion studies with low salinity (13.9 to 4.74 wt% NaCl eqv.) and low temperature (111 to 192 oC) indicate dilution and mixing of the sulfur- and element-rich magmatic-hydrothermal fluid with meteoric water, leading leaching and precipitation of trace, rare and copper elements. The δ34S isotopes values (-1.58 to -2.86‰) in the chalcopyrite minerals indicate the magmatic origin of sulfur. The geology, geochemistry, and fluid inclusions evidences indicate that the Fathabad Cu deposit is belong to epithermal style mineral systems.

In seismic methods, the estimation of formation pressures is acquired by transforming the seismic velocity to the pore pressure and contrasting it with the velocity log and effective pressure obtained during the well-test program. This study is regarding the velocity studies in one of the oilfields in SW Iran, which is generally carbonated. Except for the Kazhdumi Formation, they do not have shale interbeds. This study is based on information from 23 wells and seismic interpretation. Compressional (Vp) and shear velocity (Vs) models are determined from combined geostatistical models and compared with the value-volume fractal method, especially the velocity-volume model. Based on vertical Seismic Profiling (VSP) data, the maximum Interval velocity is 2760-2900 m/s in the northeast of the field related to the Gotnia Formation. In order to determine the formation fracture pressure, the shear velocity cube is modeled using exploratory well-cores and dipole sonic imager (DSI) shear velocity logs. The final cube with a coefficient of 0.95 has been determined for the shear velocity data obtained from the porosity, lithology, and primary DSI shear velocity data. The final amounts of inverted acoustic impedance (AI) in the deeper formation of the field are mainly in the range of 8000-15000 [(m/s)*(gr/cm3)], which it could be referred to as calcareous formations. Based on the calculation of the logratio matrix obtained from the Velocity-Volume (Vp-V) fractal model, the maximum overall accuracy (OA) in the dominant limestone intervals is 0.74. It indicates a high correlation of the compressional velocity cube model obtained from a combination of sequential Gaussian simulation (SGS) and co-kriging models with acoustic impedance inversion (AI). In the final Vp cube’s vertical Variogram, the sill is 0.34, and in major and minor is 0.96. Anisotropy range for vertical variogram range is 96 meters and for major and minor directions is 11850 meters.

Hesar gold mining area is located in Iran Alborz-Azerbaijan zone. The predominant lithology in the mineral range is volcanic, subvolcanic, and sedimentary rocks of the Cenozoic period, which include volcanic and pyroclastic rocks, andesite-trachyandesite, basalt, eicombrite, and tuffs of the Eocene age and related to the Laramid orogenic phase under the influence of Laramide. Expansion phase of volcanic lava that erupts from several fissures and emerges in the form of delirious dykes and floods and stocks, mainly dacite, rhyodacity with Oligocene age, and alterations related to these masses such as silicification, pyritization and caudal formation Major mineralization in the study area includes pyrite, goethite, magnetite and gold, which is mineralized in two phases and is mainly selective and dispersed. Gold mineralization is the result of the decomposition of pyrite and arsenic pyrite, which is free in the field. The rock has been found to be related to the second phase of volcanic and semi-volcanic outcrops of the Oligomocene age. The results obtained from microscopy studies of fluid shortcuts in quartz mineral indicate that the homogenization temperature varies in the range of 140 to 260 ° C and also the melting temperature of the last ice crystal changes from -0.1 to -9. ° C and salinity is between 0.18 to 14% by weight equivalent of NaCl with a frequency range of 2 to 6% by weight equivalent of NaCl.

Jalal Abad iron deposit is located in 38 km northwest of Zarand city with about 200 million tons of iron ore reserves with an average grade of 46.2% iron, 0.98%, sulfur and 0.07% phosphorus. It is one of the seven important iron deposits of central Iran. The rock types of this area include low-sulfur oxide high-grade iron ore, sulfur-containing high-grade iron ores and low-grade silicate magnetite iron ores. Separation of mineralized zones based on the extent of ore and geological gangues is important for mine planning and drilling operation in mines. The main purpose of this study is the separation of mineralized zones based on the frequency and spatial expansion of mineral ores and gangues using fractal modeling in the deposit. The concentration-volume (C-V) fractal model was used for iron, sulfur and phosphorus in this deposit. These results showed that the main mineralized zones have a grading range as Fe ≥ 51, S ≤0.7 and P ≤0.4%. The fourth and fifth populations obtained by the iron block model are related as the main ores. Gangues and weakly mineralized zones also indicated at the first and second zones. Finally, optimal decisions can be made based on economic changes related to time and market conditions, for the third zone.

The southern section of the Caspian Sea convexity is included in the Central Alborz, which stretches from Semnan to Qazvin. The Central Alborz zone is the focus of the research because of the strong association between lead and zinc mineralization and tectonics, as well as the great potential of this zone. The major horizons of lead and zinc mineralization, as well as the location of these horizons with orogenic events, have been investigated in this study, based on fieldwork and office studies as well as previous research. According to this research, there are eight lead and zinc mineralization horizons in Central Alborz, ranging from old to recent, including the mineralization horizon of Soltanieh Formation associated with Zaygonin orogeny, the mineralization horizon of Mila Formation associated with Caledonian orogeny, the mineralization horizon of Mubarak Formation With Alborz orogeny, Mineralization horizon of Ruteh Formation related to Hercynian orogeny, Mineralization horizon of Elika Formation related to Early Cimmerian orogeny, Mineralization horizon of Lar Formation related to Middle Cimmerian orogeny, Cretaceous mineralization horizon related to Laramid orogeny and Mineralization within the Karaj Formation is related to the Eocene age in the Pyrenean orogen. According to mathematical modeling in the Central Alborz area, the lead and zinc mineralization controls by thrust faults and reverses-strike slip faults. According to the findings of this study, more than 60% of mineralizations connected to structures occur in the Mesozoic. Triassic mineralizations occurred along with extention tectonics, while Cretaceous mineralizations formed under a compressive regime.

In the seismic methods, estimation of the formation pressures is obtained by converting the seismic velocity to the pore pressure, and comparing it with the effective pressure during the well-test program. This work is a new challenge regarding the velocity study domain in an oil field in SW Iran. The reservoir generally consists of carbonate rocks, and contains no shale interbeds. Here, 23 well information, seismic data interpretation, compressional (Vp), and shear velocity (Vs) models are implemented. The models are determined from the combined geo-statistical methods, and the results obtained are compared with the fractal models. The final Vs cube is modeled in order to determine the formation fracture pressure using the exploratory well cores and dipole sonic imager (DSI) Vs logs with a correlation coefficient of 0.95 for the Vs data obtained from the porosity, lithology, and primary DSI data. The vertical seismic profiling (VSP) data introduce a maximum interval velocity of 2760-2900 m/s in the field related to the Gotnia formation. The final amounts ​​of seismic acoustic impedance inversion (AI) at the bottom of the field are mostly in the range of 8000-15000 [(m/s)*(g/cm3)], which can be related to the calcareous formations. Based on the Logratio matrix obtained from the fractal velocity-volume (Vp-V) model, the maximum overall accuracy (OA) in the dominant limestone intervals is 0.74. It indicates a high correlation of the Vp cube model obtained from the combination of sequential Gaussian simulation (SGS) and co-kriging models with AI. The uncertainty studies of Vp model in blind wells are about 50%, which is acceptable considering the large well numbers.

Signal analysis approaches are a powerful and widely used tool in processing multi-spectral satellite images for detection of alteration zones. The main goal of this work is application of the spectrum-area fractal methodology based on the Landsat 8 OLI satellite images’ data for separation alteration zones for iron oxides at the Tarom region (NW Iran). These alteration zones, Normalized Difference Vegetation Index (NDVI), and Normalized Difference Water Index (NWDI) are detected using the band-ratio and band combination methods. Then the calculated values are categorized by Spectral Angle Mapper (SAM), k-means, and S-A fractal model. Considering a positive correlation of iron oxides alterations along with magnetite mineralization as an index of mineralization at the studied region, the promising areas are classified by a decision-making model using the TOPSIS method with an acceptable accuracy for presenting in the exploration models.

The goal of this research work is to recognize the metallic mineralization potential in the Ahar 1:100,000 sheet (NW Iran) using the remote sensing data based on determination of the alteration zones. This area is located in the Ahar-Arasbaran metallogenic zone as a significant metallogenic zone in Iran and Caucasus. In this research work, the Landsat-7 ETM+ and advanced space borne thermal emission and reflection radiometer (ASTER) multispectral remote sensing data was interpreted by the least square fit (LS-Fit), spectral angle mapper (SAM), and matched filtering (MF) algorithms in order to detect the alteration zones associated with the metallic mineralization. The results obtained by these methods show that there are index-altered minerals for the argillic, silicification, advanced argillic, propylitic, and phyllic alteration zones. The main altered areas are situated in the SE, NE, and central parts of this region.

Tirka area is situated in NE Iran as a part of the TCMB which consists of Paleogene sediments and volcanic rock units with a combination of Eocene intermediate to basic rocks. The research aim is to determine the alteration zones using C-N fractal model based on ASTER satellite images. First, the ASTER data was processed using SFF method for determination of iron oxide, propylitic, phyllic, and argillic alteration zones. The C-N fractal model is utilized for the separation of different parts of alteration zones. The results derived via the C-N fractal model showed that the main trend of the alteration zones is in NE-SW direction. Also, based on the C-N log-log plots, there are six geochemical populations for iron oxide alteration, four geochemical populations for argillic and phyllic alterations, and five geochemical populations for propylitic alteration. There is a high intensity of alteration zones commences with 223 for iron oxide, 204 for argillic, 199 for propylitic and phyllic alteration zones. In order to validate the results, field observations and petrographical studies based on thin-polish sections were carried out. These data confirmed the alteration zones obtained by the modeling. the data obtained from the combination methods, were verified by Logratio matrix,

The Kushk-e-Bahram Manto type copper deposit is located in the central Iran zone and   is Uremia-Dokhtar Magmatic Arc (UDMA) belt which includes copper porphyry deposits and related mineralization types, including the Manto type copper deposits (Jebeli et al., 2018a, b). Based on the type of mineralization and the presence of sulfides, high electrical conductivity (low electrical resistivity) can be detect in this deposit such as the Manto type deposits (Mehrnia, 2013., Mehrnia, 2016., Teymoorian Motlagh et al., 2012). On the other hand, Induced Polarization (IP) and electrical resistivity (RS) were used in the Kushk-e-Bahram deposit.

The relationship between geoelectrical parameters and the mineralization process were recognized in geophysical assessments of the Kushk-e-Bahram de posit. It is necessary to obtain information about the shape and distribution of the orebody. According to exploratory data of the Kushk-e-Bahram deposit (Jebeli et al., 2018a, b), Cu mineralization has been extended. Therefore, the location and number of geoelectrical profiles were selected, based on previous studies which was generated in the ArcGIS software. The exchanges in the RS and IP values were measured, along three profiles (P1, P2, P3) and Dipole-Dipole arrangement with electrode distance of 10 meters. The device type used is WDJD-3 and 1620 harvest points were surveyed. IP–RS profiles with azimuth 30 to 40 degrees were used in order to identify mineralization areas based on the highest variability of conductivity and load-bearing properties.  Moreover, they were designed and surveyed perpendicular to the mineralization process of the area. Considerations were taken into account based on the location of trenches and the mineralization sequence of this area. The P1 and P2 profiles with an approximate length of one kilometer and P3 profile with an approximate length of 370 m were designed and harvested under a 30 degree azimuth.

In this research study, a number of geoelectrical sections were selected and their surface changes in a two-dimensional environment were refined and internalized by the algorithm used in the diffraction-distance distribution function. According to the position of P1 and P2 profiles, all three quantities of RS, IP and self-Potential have been interpolated to match the alteration zones and faults of the study area in the P3. The quantity of Spontaneous Potential (SP) is not measured and it just suffices to internalize specific electrical changes and IP and their conformity with the effects of alteration and faults in the region. Interpolation of geo-electrical data by the inverse distance weighting estimation method and nearest neighborhood algorithms were carried out (Mehrnia, 2016; Teymoorian Motlagh et al., 2012).Based on the fractal dimension, four targets around the P1 and P2 profiles and eight priorities have been identified around the P3 profile. Based on the results, geo-electrical data distribution pattern was obtained using diffraction-distance model and changes in the fractal dimension of electrical resistivity, induced polarization and self-generating electric potential according to the differences of the fractal dimensions for IP, RS and SP in the Kushk-e-Bahram deposit. It is necessary to interpret geo-electrical sections based on fractal dimension exchanges to avoid the oblique error caused by the fitting of disproportionate quantities as much as possible. Consequently, exchanges in the level of electrical resistivity and induced polarization were calculated. There is no corresponding trend along P1 and P2 profiles. Thus, the results of the diffraction-distance model were correlated with mineralization potential in the depth of the deposit. Continuation of exploration activities (detailed phase) along the P1, P2 and P3 profiles are suggested. Based on inferring from the  Brownian mechanism distribution of electrical resistivity quantities and inductive polarization, priority of P1 and P2 profiles with vein and disseminated mineralization in P3 profile is obtained.

The studied area in this research is the Esfordi phosphate mine in the Bafq metallogenic state, which apatite, magnetite and hematite are its main mineralization. As one of the high phosphorus iron – apatite mine in the region, this mine contains significant mineralization of rare earth elements with a maximum and average grade of 1.7% and 0.5% (as monazite, zircon and allanite minerals in apatite), and has LREE enrichment and Eu negative anomaly.  In order to primary assessment of REEs concentration status in study area, the outlook coefficient of REEs (Koutl), which is based on the classification of REEs by the level of industry demand, was used. This coefficient is the ratio of the amount of critical REEs (Dy, Tb, Nd, Y, Er and Eu) to the amount of surplus REEs (Ce, Ho, Tm, Yb and Lu), which can be used to investigate mineralization of different types in newly discovered deposits and active mines. The results indicate the highest outlook coefficient (Koutl=0.67) for microgranite to rhyolite with amphibole unit, and also promising average outlook coefficient of 0.53. The Esfordi mine despite the lower grade, it is closer to the ideal composition compared to China's Bayan Obo mine (Koutl=0.2). Thus, can portend a bright future for REEs in this mine, if focus on exploration of these elements and further geochemical and mineralogical investigations are carried out.

Long-term production scheduling in open-pit mines is a crucial issue in mining planning and determines the distribution of cash flow throughout the life of the mine. The purpose of the planning is to maximize the net present value by taking into account all operational constraints such as slope, mixing of different grades, mineral production, and extraction capacity. The uncertainties associated with model data play an important role in optimizing long-term production plans. Among the uncertainties, grade uncertainty plays a major role. In this paper, hybrid models are presented by the Lagrangian relaxation (LR) method, augmented Lagrangian relaxation (ALR) method, and firefly algorithm (FA) to solve the long-term production scheduling problem of open-pit mines with the assumption of deterministic and also considering the grade uncertainty. The firefly algorithm is used to update the Lagrange multipliers. The newly proposed approaches are based on optimizing Lagrangian multipliers and comparing them with the results of combined Lagrangian relaxation method and augmented Lagrangian relaxation with the Genetic Algorithm (GA), and the traditional sub-gradient (SG) method. For solving and validating the obtained model, Chadarmelo iron ore mine is considered as a suitable case study. The results of the case study show that the combined strategy (ALR-FA) can provide a near-optimal solution over other methods such that, over a given period, the net present value using the proposed hybrid approach is 20.11% higher than the traditional method is available. Also, the CPU speed of the proposed model is 4.7% more than the other methods.

Gardaneshir carbonate-hosted Pb-Zn deposit on the ground of study area located southwest of Ardestan in Isfahan province. Base on lithostratigraphy,the main structure, besides the small outcrops of Jurassic shales, has been made up of carbonate and detrital rock materials depending on Paleozoic,Triassic and Cretaceous time stages. Dolomitic carbonate which is attributed to Shotori Formation , played the major role of host rock in ore-mineralization. Ore-mineral description obtained from the mineralized zone and caused the following ore-paragenesis in ascending order.of:pyrite,chalcopyrite,galena,sphalerite,malachite,cerussite,smithsonite,iron oxides and gangues of barite, quartz and calcite. Physico-chemical information of ore-solutions performed by entrapped fluid inclusion studies in gangue minerals. Liquid-rich two phase(L+V) inclusions as predominant types were recognized. These type of inclusions are homogenized into liquid state with a range of TH and related salinities between; TH :78 to 183 and 216 to 283°C, Salinity:3.5 to 9.7 and 10.2 to 25 wt% NaCl eq. The microthermometric data reflect the nature of two population of fluid inclusions originating from different sources. The source materials could have been provided by basinal brines, derived during compaction of sediments in a shallow sea environment and by movement into sediments, the stratabound Pb-Zn deposit are formed. Furthermore, the negative delta value ranges(δ34S) from -0.6 ‰ to -20.4 ‰ that have been extracted by galena can be an evidence of bacterial sulfate reduction in a subsidence sedimentary basin. In conclusion, based on field, mineralogical, fluid inclusion and sulfur isotope evidence, we propose that Gardaneshir Pb-Zn deposit is a stratabound carbonate hosted of Mississipi Valley Type(MVT).

This work aims to classify the gas content zones for coking coal deposits using a Number-Size (N-S) fractal modeling considering the explosive and free gas data. The case study is the C1 coking coal seam in the Parvadeh-4 coal deposit in the central Iran. Following this, the N-S log-log plots are created, which indicate three populations regarding both the explosive and gas data exist. Proper zones for both data in the C1 coking coal seam have explosive and free gas contents lower than 9.5 m3/ton and 1.3 m3/ton, respectively. The low-value gas content zone is located in the western part of the studied area, which is in the lowest depth of this coal seam. In addition, a high-value content zone exists in the E, NE, and SW parts of this area with explosive and free gas contents higher than 13.8 m3/ton and 2.2 m3/ton, respectively. These parts of the C1 seam are dangerous due to a high volume of gas content. Moreover, the explosive and free gas contents have a positive correlation with high risk gas volume based on the famous standards.

Summary:

One of the main problems of mine planning is long-term production scheduling, which is very important in the theoretical research of open-pit mining and determines the distribution of cash flow throughout the life of the mine. In fact, the purpose is to maximize the net present value of the future profits generated. Among the uncertainties, grade uncertainty will play a major role in the accuracy of long-term production scheduling. In this paper, a hybrid model is presented by the Lagrangian relaxation method and bat algorithm to solve the problem of long-term production of open-pit mines, in which the uncertainty of the grade is also considered. The new approaches proposed are based on optimizing Lagrange coefficients and comparing them with the traditional method. The bat algorithm is used to update the Lagrange coefficients. The results of the case study show that the hybrid strategy can provide an acceptable solution compared to the traditional approximation method so that over a given period the net present value using the proposed hybrid method is 6.69% higher than the traditional one.

In recent years, a new approach to cheaper computational algorithms, such as meta-heuristic techniques, has attracted more attention from researchers to solve production scheduling problems. Although these techniques do not guarantee optimization as a final solution for production, they can provide suitable solutions for production at a lower computational cost.

Methodology and Approaches:

In this paper, an optimal hybrid model by the Lagrangian relaxation method and bat algorithm is presented to solve the problem of long-term production of open-pit mines, where the uncertainty of the grade is also considered. The newly proposed approach is based on optimizing Lagrange coefficients and comparing it with the traditional method. The results of the proposed approach are also compared with the combined approach based on the Lagrangian relaxation method and genetic algorithm. The bat algorithm is used to update the Lagrange coefficients.

The results of a case study show that the Lagrangian relaxation method can provide a suitable solution to the main problem and the combined strategy can produce a more effective solution than the traditional approximation method. It was also found that the proposed method has advantages, such as stable convergence property and prevention of early convergence. Over a given period, the net present value using the LR-BA hybrid method is 6.69% higher than the traditional method and also 5.58% higher than the LR-GA method.

Summary:

In this paper, the blasting data and rock mass characteristics of Chogart, Chadormalu, and Sechahum mines were used to predict the size distribution of rock fragmentation (D80). Rock fragmentation is affected by various parameters such as rock mass properties, in-situ blocks shape, blasting geometry, etc. To quantify the shape of in-situ blocks, fractal geometry is a suitable method. To predict the rock fragmentation (D80) based on independent variables (rock mass characteristics, in-situ block shape, and blasting geometry); linear/nonlinear regression and neural networks were used. The results showed that the nonlinear regression and neural network were the ability to predict the size distribution of rock fragmentation. 

Due to economic reasons, drilling and blasting methods have been used in mining, quarrying industries, and civil projects. The results of blasting can be categorized into two i.e. favorable results (rock fragmentation, heave and move material) and unfavorable results (air overpressure, back break, ground vibration, and fly rock). Rock fragmentation due to blasting is influenced by several factors that are classified into three namely; explosive parameters, rock mass characteristics, and blast geometry. In recent decades, several empirical models have been proposed to predict rock fragmentation due to blasting. Nowadays, based on computer science advances,    regression analysis and artificial intelligence (AI) have been employed for rock fragmentation prediction.

Methodology and Approaches:

In this research, fractal geometry was used to describe the rock mass shape. The fractal dimension of in-situ blocks was determined by the box-counting method. On the other hand, the uniaxial compressive strength (UCS) and longitude wave velocity (laboratory and in-situ) were considered as rock mass characteristics. Also, the powder factor (PF) was representative of blasting geometry and explosive parameters. The linear/nonlinear regression and neural network were used to investigate the relationship between the rock fragmentation and independence variables (rock mass characteristics, blasting geometry, rock mass shape).

In this research, an attempt was made to predict the size distribution of rock fragmentation (D80)at the Central iron ore mines (Chogart, Chadormalu, and Sechahun) by linear/nonlinear regression and neural network. Linear regression results revealed that the independent variables have a significant effect on the dependent variable (D80). The results were shown the neural network has the superiority to the prediction of rock fragmentation.

It is significant to discover a global optimization in the problems dealing with large dimensional scales to increase the quality of decision-making in the mining operation. It has been broadly confirmed that the long-term production scheduling (LTPS) problem performs a main role in mining projects to develop the performance regarding the obtainability of constraints, while maximizing the whole profits of the project in a specific period. There is a requirement for improving the scheduling methodologies to get a good solution since the production scheduling problems are non-deterministic polynomial-time hard. The current paper introduces the hybrid models so as to solve the LTPS problem under the condition of grade uncertainty with the contribution of Lagrangian relaxation (LR), particle swarm optimization (PSO), firefly algorithm (FA), and bat algorithm (BA). In fact, the LTPS problem is solved under the condition of grade uncertainty. It is proposed to use the LR technique on the LTPS problem and develop its performance, speeding up the convergence. Furthermore, PSO, FA, and BA are projected to bring up-to-date the Lagrangian multipliers. The consequences of the case study specifies that the LR method is more influential than the traditional linearization method to clarify the large-scale problem and make an acceptable solution. The results obtained point out that a better presentation is gained by LR–FA in comparison with LR-PSO, LR-BA, LR-Genetic Algorithm (GA), and traditional methods in terms of the summation net present value. Moreover, the CPU time by the LR-FA method is approximately 16.2% upper than the other methods.

Lahrud is situated in NW Iran, between 47º 30´ to 48º longitudes and 38º 30´ to 39º latitudes, based on the structural units this area is part of the Eocene age trending  Alborz-Azerbaijan magmatic belt .The volcanic rocks of Eocene age mainly comprise of alkaline series.

 Fractal modeling has been widely used in various fields of earth sciences and mineral exploration since the 1980s. One of the most important methods is the Concentration-Number fractal method; this method is based on the inverse relationship between the concentration and the cumulative frequency of each concentration and higher concentrations. In 2003, about 600 samples of Lahroud 1: 100,000 sheet stream sediments were randomly sampled by the National Geological and Mineral Exploration Organization and analyzed by ICP-MS. In this study, classical statistics operations, factor analysis, fractal Concentration-Number of operations and element geochemical anomaly maps were prepared. Classical statistics have a structural weakness for not taking into account the spatial position of the data which causes systematic errors. Factor analysis is one of the most popular multivariate analyses, which is used as a powerful tool for visualizing large three-dimensional spatial data based on the variance and covariance matrices. In this method, a large set of geochemical variables are combined with several factors. The basis of the factor analysis work is, that after the initial stages of data preparation, at each stage, the elements that have a number higher than 0.6 should be selected and the rest of the elements should be removed.

 Factor analysis was performed in SPSS software and had four stages; All disruptive elements (Mo, Be, Hg, Pb, Ag, Sr, Se, and Bi) were removed after four stages of factor analysis, and As, Sb, Sn, W, Co, Mn, Zn, Ti, Ba, Ni, Cr, Au, Cu and B were classified into five groups. Graph diagram of the C-N of invoice points was drawn and their values determined the maps of geochemical communities. The interpretation of airborne geophysical data is done both qualitatively and quantitatively. In interpreting this data, geological structures such as the location of intrusive masses, faults or hidden faults, contacts, special structures such as folds, various alteration zones and various lithologies and their changes are considered. The Oasis Montaj geophysical software offers a variety of filters and applications for analyzing and, interpreting aerial magnetic data. Geophysical surveys of the Lahrud area were performed on 48 flight lines, including longitude, latitude, and magnetic field for each point.

The presence of Andesite and Andesite-basalt rocks on the surface (geological study of area) reinforces the possibility of the presence of dioritic intrusive mass. This, has caused some of the rocks around the intrusive mass and fractures to rise through the weak points around it, and it has flowed as lava on the earth's surface. Finally it has formed the Andesite rocks of the region. Due to the size, depth and alterations of the rocks around the southern intrusive mass of the region, this, type of rooted batolite was detected with a slope to the south. The presence of Sb in the southwestern region confirms the performance of a hydrothermal system; the system, rises through the existing faults and affects the alteration rocks, creating Alunitization, Kaolinitiezation and Silicification alterations in the southwest and center of the sheet. Most of the anomalies are around the intrusive mass south of the region, where hydrothermal fluids have caused alterations, followed by mineralization. Concentration-Number fractal calculations, step-by-step factor analysis, preparation of geochemical anomalies of Gold, Antimony and Copper elements, studies and preparation of geophysical maps indicate that the anomalies of the elements are significant. They correspond to alteration areas and intrusions. This, indicates a close and notable connection between the alterations, faults and, intrusive masses of the Lahrud 1:100,000 sheet with the anomaly of the elements, especially Au and Cu. Therefore, the best exploration items in this sheet are Gold and Copper.

Detection of mineralized zones based on ores and gangues is important for mine planning and excavation operation. The major goal of this research work was to determine the zones based on ores and gangues by a combination of fractal and factor analysis in the Chah Gaz iron ore (Central Iran). The Concentration-Volume (C-V) fractal method was carried out for Fe, P and S, which indicated that the main mineralized zones consisted of the Fe, S, and P values ≥ 57%, ≤ 0.4%, and ≤0.3%, respectively. Factor analysis categorized variables in two groups including factor 1 (F1) and factor 2 (F2) for ore and gangue, respectively. The C-V fractal modeling on the derived factors showed four zones for F1 and F2. Based on the correlation among the results of fractal modeling on the elements and factors, the first and second zones of F1 were proper for exploitation. Furthermore, the last and first zones of F1 and F2 could be assumed as the main waste for mining excavation.

The Urumieh-Dokhtar Magmatic Arc (UDMA) is recognized as an important porphyry, disseminated, vein-type and polymetallic mineralization arc. The aim of this study is to identify and subsequently determine geochemical anomalies for exploration of Pb, Zn and Cu mineralization in Mial district situated in UDMA. Factor analysis, Concentration-Number (C-N) fractal model and Local Linear Model Tree (LOLIMOT) algorithm used for this purpose. Factor analysis utilized in recognition of the correlation between elements and their classification. This classified data used for training the LOLIMOT algorithm based on relevant elements. The results of the LOLIMOT algorithm represent anomalies in areas with no lithogeochemical samples. Although, the C-N log-log plot for target elements were generated based on stream sediment and lithogeochemical samples which could be delineated mineral potential maps of the target elements. Results obtained by the LOLIMOT and fractal modeling show that the SW and the Eastern parts of the area are proper for further exploration of Cu, Pb, and Zn.

The traditional approaches of modeling and estimation of highly skewed deposits have led to incorrect evaluations, creating challenges and risks in resource management. The low concentration of the rare earth element (REE) deposits, on one hand, and their strategic importance, on the other, enhances the necessity of multivariate modeling of these deposits. The wide variations of the grades and their relation with different rock units increase the complexities of the modeling of REEs. In this work, the Gazestan Magnetite-Apatite deposit was investigated and modeled using the statistical and geostatistical methods. Light and heavy REEs in apatite minerals are concentrated in the form of fine monazite inclusions. Using 908 assayed samples, 64 elements including light and heavy REEs from drill cores were analyzed. By performing the necessary pre-processing and stepwise factor analysis, and taking into account the threshold of 0.6 in six stages, a mineralization factor including phosphorus with the highest correlation was obtained. Then using a concentration-number fractal analysis on the mineralization factor, REEs were investigated in various rock units such as magnetite-apatite units. Next, using the sequential Gaussian simulation, the distribution of light, heavy, and total REEs and the mineralization factor in various realizations were obtained. Finally, based on the realizations, the analysis of uncertainty in the deposit was performed. All multivariate studies confirm the spatial structure analysis, simulation and analysis of rock units, and relationship of phosphorus with mineralization.

The Khankeshi stratabound copper deposit is located in Markazi province, 80 Km SW of Tehran. The area is covered by a sequence of  E-W trending  lava flows and  pyroclastic of Late Eocene age. The volcanic rocks can be classified as  trachyandesite and andesite.The rocks contain a high fraction of  potassium calc-alkaline and their geochemical characteristics attribute them to back arc basin and extentional processes. The oldest rocks of the study area are Elta unit , composed of  green andesitic  tuff  located in south eastern of the khankeshi. This part indicates a basin with volcanic activities and exhalites, and green tuff with thin lamination combined with microcrystalline carbonates. On the other hand, presence of carbonate of micrite with framboidal pyrite in this part indicated reducing environment and Exhalites activity by source of sulfur in manto type mineralization in the khankeshi. The host rock is Elt type latite andesite with mega porphyritic texture and involved major ore chalcopyrite, bornite with pyrite and minor chalcocite, covellite, hematite, Goethite and malachite with dolomite and dolosparite veins. Framboidal pyrite is replaced with forms of fine and circle chalcopyrite and bornite in primary micritic background and subhedral crystals into dolosparite veins of crystallized micrititic carbonate micrite in forms of  epigenetic that produce the supergene secondary production. This unit with pyroclastics and tuff breccias(Elta unit), indicated volcanic cycle that mineralization of copper, in forms of stratabound, has taken place in it. Local alteration associated with copper mineralization includes weak chloritization, oxidation with local argillic, serecitic and zeolitic. Mineralization is stratabound and  copper  mineralization occurs as disseminated, vein-veinlet,open space fillings and  replacements. Based on fluid inclusion studies on coexisting calcite, Homogenization temperatures are between 129.4 to 227.1(with an average of 175°C).Salinity varies between 1.91 to 13.40(average 12) wt٪ NaCl eq. The depth of  fluid inclusion trapping is estimated to be less than 200 meters and ore formation has occurred at pressure values less than 74 bars. Geological, ore mineralogy, ore texture, structures and  fluid inclusions characteristics in the  khankeshi deposit are similar to those reported from Manto type copper deposits.