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Lead and zinc geochemical behavior based on geological characteristics in Parkam Porphyry Copper System, Kerman, Iran

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Journal of Central South University 2015年第11期22卷 4274-4290页

作者： Seyyed Saeed Ghannadpour ardeshir hezarkhani Department of Mining & Metallurgical Engineering Amirkabir University of Technology(Tehran Polytechnic)

Parkam(Sarah) porphyry system is located on the metallogenic belt of Kerman, Iran. Due to existence of some copper-rich resources in this region, finding out the exact statistical characteristics such as distribution of data population, mean, variance and data population behavior of elements like Cu, Mo, Pb and Zn is necessary for interpreting their geological behavior. For this reason, precise calculation of statistical characteristics of Pb and Zn grade datasets was performed and results were interpreted geologically. The natures of Pb and Zn distributions were initially identified and their distributions were normalized through statistical treatment. Subsequently, the variograms were calculated for each exploration borehole and show that both Pb and Zn geochemical variates are spatially correlated. According to the similarity of the behavior of Pb and Zn in these calculations, it is decided to measure their exact behavior applying K-means clustering method. K-means clustering results show that the Zn grade varies linearly relative to that of Pb values and their behavior is similar. Based on the geochemical behavior similarity of Pb and Zn, throughout the pervasive secondary hydrothermal activity, they are remobilized in the similar manner, from the deep to the shallow levels of the mineralization zones. However, statistical analysis suggests that hydrothermal activity associated with secondary waters in Parkam is effective in remobilizing and enriching both Pb and Zn since they have similar geochemical characteristics. However, the process does not result in generation of economic concentrations.

关键词： Parkam porphyry copper Pb Zn statistical analysis

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Studying distribution of rare earth elements by classifiers,Se-Chahun iron ore,Central Iran

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Acta Geochimica 2017年第2期36卷 232-239页

作者： Mohammadali Sarparandeh ardeshir hezarkhani Department of Mining and Metallurgical Engineering Amirkabir University of Technology (Tehran Polytechnic) Tehran Iran

The increased production and price of rare earth elements(REEs) are indicative of their importance and of growing global attention. More accurate and practical exploration procedures are needed for REEs, and for other geochemical resources. One such procedure is a multivariate approach. In this study, five classifiers, including multilayer perceptron(MLP), Bayesian, k-Nearest Neighbors(KNN), Parzen, and support vector machine(SVM),were applied in supervised pattern classification of bulk geochemical samples based on REEs, P, and Fe in the Kiruna type magnetite-apatite deposit of Se-Chahun,Central Iran. This deposit is composed of four rock types:(1) High anomaly(phosphorus iron ore),(2) Low anomaly(metasomatized tuff),(3) Low anomaly(iron ore), and(4)Background(iron ore and others). The proposed methods help to predict the proper classes for new samples from the study area without the need for costly and time-consuming additional studies. In addition, this paper provides a performance comparison of the five models. Results show that all five classifiers have appropriate and acceptable performance. Therefore, pattern classification can be used for evaluation of REE distribution. However, MLP and KNN classifiers show the same results and have the highest CCRs in comparison to Bayesian, Parzen, and SVM classifiers. MLP is more generalizable than KNN and seems to be an applicable approach for classification and predictionof the classes. We hope the predictability of the proposed methods will encourage geochemists to expand the use of numerical models in future work.

关键词： Geochemical exploration of REEs Supervised pattern classification Geochemistry of Se-Chahun ~Central Iran

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Discrimination geochemical interaction effects on mineralization at the polymetallic Glojeh deposit,NW Iran by interative backward quadratic modeling

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Acta Geochimica 2020年第2期39卷 236-254页

作者： Farshad Darabi-Golestan ardeshir hezarkhani Department of Mining and Metallurgical Engineering Amirkabir University of Technology424 Hafez AveTehran 15875-4413Iran

The physico-chemical exchanges between hydrothermal fluids and the host rock are usually controlled by elemental interaction effects.A criterion-based backward elimination approach applies the iterative regression analysis and analysis of variance to investigate the geochemical features of the polymetallic Glojeh(Au-Ag-CuPb-Zn)deposit in NW Iran.A statistical definition of the elemental interaction effects(X(i-j)^2,Xi×Xj)could elucidate the relationship between variables and the performance of a full quadratic polynomial model(QPM).The model optimization procedure was carried out by the removal of insignificant predictors(P value 95%CL)based on R^2(pred.)*** order to straighten the convergent trend with R^2 and R^2(adj.),R^2(pred.)gradually increased from 0%to 77.8%by 15-steps *** miniature-scale geochemical changes indicate double ordinal Au(Ag,Pb)and Au(Ag,Zn)interactions within the vein and host rock,in *** show that the Au(Pb-Zn)commonly presents ordinal effect at the vein and disordinal interaction at the host *** ordinal-disordinal interaction revealed that elements Pb and Zn have similar geochemical features during *** addition,Akima's polynomial contour map confirms the results from Pb-Zn interaction effects by dependency tracing between Au-Pb-Zn at different ***,it is noteworthy that Pb and Zn occur together in the second phase of Pb-Zn-Cu±(Ag±Cd)sulfide mineralization at Glojeh,which implies intergrowth and interaction of Pb-Zn on Au *** and Zn demonstrate relatively high mobility and are generally concentrated in the near surface *** is an immobile element during alteration and high content Hg zone is mainly restricted to narrow stripes above ore vein and veinlets.

关键词： Backward Elimination Quadratic polynomial model Miniature-scale changes Ordinal–disordinal interaction effect Akima's polynomial contour map Immobile element

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A method for extracting anomaly map of Au and As using combination of U-statistic and Euclidean distance methods in Susanvar district,Iran

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Journal of Central South University 2017年第11期24卷 2693-2704页

作者： Seyyed Saeed Ghannadpour ardeshir hezarkhani Mostafa Sharifzadeh Department of Mining & Metallurgical Engineering Amirkabir University of Technology (Tehran Polytechnic) Department of Mining Engineering and Metallurgical Engineering Western Australia School of MineCurtin University

Quantitative descriptions of geochemical patterns and providing geochemical anomaly map are important in applied geochemistry. Several statistical methodologies are presented in order to identify and separate geochemical anomalies. The U-statistic method is one of the most important structural methods and is a kind of weighted mean that surrounding points of samples are considered in U value determination. However, it is able to separate the different anomalies based on only one variable. The main aim of the presented study is development of this method in a multivariate mode. For this purpose, U-statistic method should be combined with a multivariate method which devotes a new value to each sample based on several variables. Therefore, at the first step, the optimum p is calculated in p-norm distance and then U-statistic method is applied on p-norm distance values of the samples because p-norm distance is calculated based on several variables. This method is a combination of efficient U-statistic method and p-norm distance and is used for the first time in this research. Results show that p-norm distance of p=2(Euclidean distance) in the case of a fact that Au and As can be considered optimized p-norm distance with the lowest error. The samples indicated by the combination of these methods as anomalous are more regular, less dispersed and more accurate than using just the U-statistic or other nonstructural methods such as Mahalanobis distance. Also it was observed that the combination results are closely associated with the defined Au ore indication within the studied area. Finally, univariate and bivariate geochemical anomaly maps are provided for Au and As, which have been respectively prepared using U-statistic and its combination with Euclidean distance method.

关键词： mineral anomaly Susanvar district U-statistic method Euclidean distance bivariate anomaly map

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Application of K-means and PCA approaches to estimation of gold grade in Khooni district(central Iran)

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Acta Geochimica 2018年第1期37卷 102-112页

作者： Neda Mahvash Mohammadi ardeshir hezarkhani Abbas Maghsoudi Department of Mining and Metallurgical Engineering Amirkabir University of Technology

Grade estimation is an important phase of mining projects, and one that is considered a challenge due in part to the structural complexities in mineral ore *** overcome this challenge, various techniques have been used in the past. This paper introduces an approach for estimating Au ore grades within a mining deposit using k-means and principal component analysis(PCA). The Khooni district was selected as the case study. This region is interesting geologically, in part because it is considered an important gold source. The study area is situated approximately 60km northeast of the Anarak city and 270km from Esfahan. Through PCA, we sought to understand the relationship between the elements of gold,arsenic, and antimony. Then, by clustering, the behavior of these elements was investigated. One of the most famous and efficient clustering methods is k-means, based on minimizing the total Euclidean distance from each class center. Using the combined results and characteristics of the cluster centers, the gold grade was determined with a correlation coefficient of 91%. An estimation equation for gold grade was derived based on four parameters: arsenic and antimony content, and length and width of the sampling points. The results demonstrate that this approach is faster and more accurate than existing methodologies for ore grade estimation.

关键词： K-means method Clustering Principal component analysis(PCA) Estimation Gold Khooni district

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Assessing Lateral Continuity within the Yammama Reservoir in the Foroozan Oilfield, Offshore Iran: An Integrated Study

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Acta Geologica Sinica(English Edition) 2018年第6期92卷 2405-2415页

作者： Payam HASSANZADEH Ahmad Reza RABBANI ardeshir hezarkhani Saeed KHAJOOIE Department of Petroleum Engineering Amirkabir University of Technology Department of Mining and Metallurgy Engineering Amirkabir University of Technology Department of Reservoir Engineering Exploration Directorate of National Iranian Oil Company (NIOC-EXP)

Located in Iranian sector of the Persian Gulf, Foroozan Oilfield has been producing hydrocarbons via seven different reservoirs since the 1970 s. However, understanding fluid interactions and horizontal continuity within each reservoir has proved complicated in this field. This study aims to determine the degree of intra-reservoir compartmentalization using gas geochemistry, light hydrocarbon components, and petroleum bulk properties, comparing the results with those obtained from reservoir engineering indicators. For this purpose, a total of 11 samples of oil and associated gas taken from different producing wells in from the Yammama Reservoir were selected. Clear distinctions, in terms of gas isotopic signature and composition, between the wells located in northern and southern parts of the reservoir(i.e. lighter δ13 C1, lower methane concentration, and negative sulfur isotope in the southern part) and light hydrocarbon ratios(e.g. nC 7/toluene, 2,6-dmC7/1,1,3-tmcyC5 and m-xylene/4-mC8) in different oil samples indicated two separate compartments. Gradual variations in a number of petroleum bulk properties(API gravity, V/Ni ratios and asphaltene concentration) provided additional evidence on the reservoir-filling direction, signifying that a horizontal equilibrium between reservoir fluids across the Yammama Reservoir is yet to be achieved. Finally, differences in water-oil contacts and reservoir types further confirmed the compartmentalization of the reservoir into two separate compartments.

关键词： reservoir compartmentalization gas geochemistry light hydrocarbons reservoir engineering Yammama Reservoir Foroozan Oilfield Iran

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The Parkam Exploration District, Kerman, Iran： Geology, Alterations, and Delineation of Cu- and Mo-Mineralized Zones Using U-Spatial Statistic with Associated Software Development

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Journal of Earth Science 2017年第2期28卷 283-294页

作者： Seyyed Saeed Ghannadpour ardeshir hezarkhani Armin Sabet-Mobarhan-Talab Department of Mining and Metallurgical Engineering Amirkabir University of Technology(Tehran Polytechnic)

The Parkam exploration district represents an area of approximately 4 km^2 located 50 km north of Shahr-E-Babak（Kerman Province, Iran）, and has several traces of old copper mining and smelting activities. This area lies in the Kerman Copper Belt which is part of the larger Sahand-Bazman igneous and metallogenic zone hosting numerous known porphyry copper deposits and systems. The geology of the Parkam exploration district demonstrates that the area contains a diorite-type porphyry copper system hosted by volcanic and pyroclastic rocks of predominantly andesitic composition. Based on field and microscopic investigation, it was determined that the dominant types of alteration were propylitic, phyllic, argillic, and potassic, and the alteration map of the study area was produced. Expect for the propylitic alteration which was observed mainly in the host rocks, the other types of alteration are associated mainly with the dioritic subvolcanic body. Accompanied by subordinate amounts of primary sulfides, fracture-filling malachite is widespread in the potassic and phyllic zones and comprises the dominant style of mineralization at the surface of the porphyry system. Lithogeochemical data resulting from 377 samples were analyzed, and the results of background and anomaly separation by means of conventional and the U-spatial statistic method were compared. The Cu and Mo mineralizations were subsequently delineated using the U-spatial statistic. The delineated Cu mineralization is closely associated with the defined zone of potassic alteration, which is also consistent with the field and microscopic observation of the Cu mineralization in this alteration zone. The Mo mineralization delineated by the U-statistic method is mostly associated with the phyllic alteration and is spatially conformable with the zone defined for it. The source code for a software program, which was developed in the MATLAB programming language in order to perform the calculations of the U-spatial stat

关键词： Parkam U-statistic anomaly separation Cu Mo

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Quadratic investigation of geochemical distribution by backward elimination approach at Glojeh epithermal Au(Ag)-polymetallic mineralization, NW Iran

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Journal of Central South University 2018年第2期25卷 342-356页

作者： Darabi-Golestan Farshad hezarkhani ardeshir Department of Mining and Metallurgical Engineering Amirkabir University of Technology

The correspondence analysis will describe elemental association accompanying an indicator *** analysis indicates strong mineralization of Ag,As,Pb,Te,Mo,Au,Zn and to a lesser extent S,W,Cu at Glojeh polymetallic mineralization,NW *** work proposes a backward elimination approach(BEA)that quantitatively predicts the Au concentration from main effects(X),quadratic terms(X2)and the first order interaction(Xi×Xj)of Ag,Cu,Pb,and Zn by initialization,order reduction and validation of *** is done based on the quadratic model(QM),and it was eliminated to reduced quadratic model(RQM)by removing insignificant *** the QM optimization process,overall convergence trend of R2,R2(adj)and R2(pred)is obvious,corresponding to increase in the R2(pred)and decrease of *** RQM consisted of(threshold value,Cu,Ag×Cu,Pb×Zn,and Ag2-Pb2)and(Pb,Ag×Cu,Ag×Pb,Cu×Zn,Pb×Zn,and Ag2)as main predictors of optimized model according to288and679litho-samples in trenches and boreholes,*** to the strong genetic effects with Au mineralization,Pb,Ag2,and Ag×Pb are important predictors in boreholes RQM,while the threshold value is known as an important predictor in the trenches *** RQMs R2(pred)equal74.90%and60.62%which are verified by R2equal to73.9%and60.9%in the trenches and boreholes validation group,respectively.

关键词： correspondence analysis first order interaction reduced quadratic model (RQM) optimized model order reduction and validation strong genetic effects

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Application of Self-Organizing Map for Exploration of REEs’ Deposition

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Open Journal of Geology 2016年第7期6卷 571-582页

作者： Mohammadali Sarparandeh ardeshir hezarkhani Department of Mining and Metallurgical Engineering Amirkabir University of Technology (Tehran Polytechnic) Tehran Iran

Varieties of approaches and algorithms have been presented to identify the distribution of elements. Previous researches based on the type of problem, categorized their data in proper clusters or classes. This means that the process of solution could be supervised or unsupervised. In cases, where there is no idea about dependency of samples to specific groups, clustering methods (unsupervised) are applied. About geochemistry data, since various elements are involved, in addition to the complex nature of geochemical data, clustering algorithms would be useful for recognition of elements distribution. In this paper, Self-Organizing Map (SOM) algorithm, as an unsupervised method, is applied for clustering samples based on REEs contents. For this reason the Choghart Fe-REE deposit (Bafq district, central Iran), was selected as study area and dataset was a collection of 112 lithology samples that were assayed with laboratory tests such as ICP-MS and XRF analysis. In this study, input vectors include 19 features which are coordinates x, y, z and concentrations of REEs as well as the concentration of Phosphate (P2O5) since the apatite is the main source of REEs in this particular research. Four clusters were determined as an optimal number of clusters using silhouette criterion as well as k-means clustering method and SOM. Therefore, using self-organizing map, study area was subdivided in four zones. These four zones can be described as phosphate type, albitofyre type, metasomatic and phosphorus iron ore, and Iron Ore type. Phosphate type is the most prone to rare earth elements. Eventually, results were validated with laboratory analysis.

关键词： Self Organizing Map (SOM) REEs Geochemistry Choghart Central Iran

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Delineation of Geochemical Anomalies Based on Cu by the Boxplot as an Exploratory Data Analysis (EDA) Method and Concentration-Volume (C-V) Fractal Modeling in Mesgaran Mining Area, Eastern Iran

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Open Journal of Geology 2016年第10期6卷 1269-1278页

作者： Mohammadreza Agharezaei ardeshir hezarkhani Department of Mining and Metallurgy Engineering Amirkabir University of Technology (Tehran Polytechnic) Tehran Iran

The target in this investigation is separation and delineation of geochemical anomalies for the single element Cu in Mesgaran mining area, eastern Iran. Mesgaran mining area is located in south part of Sarbishe county with about 29 Km distance to the county center. This region is part of an Ophiolite sequence and the copper anomalies seem to be related to a volcanic massive sulfide (VMS) deposit whose main part (massive sulfide Lens) has been eroded. In order to delineate Cu anomalies, the boxplot as an Exploratory Data Analysis (EDA) method and concentration-volume (C-V) Fractal modeling are employed. Both of the methods reveal low-deep anomalies which are highly correlated with geological and geophysical studies. As the main result of this study we show that Fractal modeling in spite of the Boxplot, is not recommended for complex geological settings. The proved shallow anomalies recorded by geophysical studies and defined by the used methods are in accordance to the stringer zone of a volcanic massive sulfide (VMS) deposit in Mesgaran mining area which means this region is the bottom of a VMS deposit and geochemical anomalies are related to the remained parts of the deposit.

关键词： Mesgaran Geochemistry Fractal Modeling The Boxplot VMS Deposit

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