Distribution of heavy metals in the clastic fine-grained sediments of Gavkhuni playa lake (Southeast of Isfahan,Iran)

The sedimentary basin of Gavkhuni playa lake includes two sedimentary environments of delta and playa lake. These environments consist of mud, sand and salt flats. There are potentials for concentration of heavy metals in the fine-grained sediments (silt and clay) of the playa due to existence of Pb/Zn ore deposits, industrial and agricultural regions in the water catchment of Zayandehrud River terminating to this area. In order to study the concentration of heavy metals and the controlling factors on their distribution in the fine-grained sediments, 13 samples were taken from the muddy facies and concentration of the heavy metals were determined. The results showed that the heavy metal concentrations range in the sediments (in ppm) are Mn (395.5–1,040), Sr (100.4–725.76), Pb (14.66–91.06), Zn (23.59–80.9), Ni (37–73.66), Cu (13.83–29.83), Co (5.73–13.78), Ag (3.03–4.76) and Cd (2.3–5.5) in their order of abundances. The concentration of Ag is noticeable in the sediments relative to the average concentration of this element in mud sediments. The amounts of Pb and Zn are relatively high in all the samples in comparison with the other elements. The concentration of Ni is relatively high in the oxidized samples. The distribution of Pb is directly related to organic matter content of the sediments. The concentrations of Zn, Sr, Cu, Co and Cd in the samples of the playa are lower than those in the delta. The amount of illite is another factor influencing Zn and Pb concentrations. Sr is more concentrated in the sediments with the high content of calcium carbonate. The distribution pattern of Cu, Co, Pb and Mn resembles to that of the clay content of the sediments. The clay content shows positive correlations with Co, Cu and Mn concentrations and negative correlation with Ag. The Sr and Ag concentrations are positively correlated with the amount of CaCO₃. The amounts of Co, Cu, Ni and Mn show negative correlations with the calcium carbonate content. Pb and Co are noticeably correlated with Mn.     

Spatial estimation of water-table depth by artificial neural networks in light of ancillary data

Proper estimation of the spatial distribution of water-table depth is highly important in most groundwater studies. Groundwater depth is measured at specific and limited points and it is estimated for other parts using spatial estimation methods. In this study, two multivariate methods, artificial neural network (ANN) and multiple linear regression (MLR), are examined to estimate water-table depth in an unconfined aquifer located in Shibkooh, Iran. The different ancillary data, including spatial coordinates, digital elevation model (DEM), aquifer bed elevation, specific resistivity and aquifer thickness were used to improve estimates based on these methods. It was proved that performance of the ANN surpasses that of the MLR method. Using the spatial coordinates, the aquifer bed elevation and aquifer thickness resulted in the optimum spatial estimation of the water-table depth. These parameters, directly or indirectly, affect the water-table depth estimation through techniques such as ANN capable of modelling of nonlinear relationships.     

Prospectivity modeling of porphyry copper deposits: recognition of efficient mono- and multi-element geochemical signatures in the Varzaghan district,NW Iran

Acta Geochimica - The Varzaghan district at the northwestern margin of the Urumieh–Dokhtar magmatic arc, is considered a promising area for the exploration of porphyry Cu deposits in Iran. In...     

Earthquake relocation in the Central Alborz region of Iran using a non-linear probabilistic method

In this study, we calculate accurate absolute locations for nearly 3,000 shallow earthquakes (≤20 km depth) that occurred from 1996 to 2010 in the Central Alborz region of northern Iran using a non-linear probabilistic relocation algorithm on a local scale. We aim to produce a consistent dataset with a realistic assessment of location errors using probabilistic hypocenter probability density functions. Our results indicate significant improvement in hypocenter locations and far less scattering than in the routine earthquake catalog. According to our results, 816 earthquakes have horizontal uncertainties in the 0.5–3.0 km range, and 981 earthquakes are relocated with focal-depth errors less than 3.0 km, even with a suboptimal network geometry. Earthquake relocated are tightly clustered in the eastern Tehran region and are mainly associated with active faults in the study area (the Mosha and Garmsar faults). Strong historical earthquakes have occurred along the Mosha and Garmsar faults, and the relocated earthquakes along these faults show clear north-dipping structures and align along east–west lineations, consistent with the predominant trend of faults within the study region. After event relocation, all seismicity lies in the upper 20 km of the crust, and no deep seismicity (>20 km depth) has been observed. In many circumstances, the seismicity at depth does not correlate with surface faulting, suggesting that the faulting at depth does not directly offset overlying sediments.     

Assessment of Various Fuzzy c-Mean Clustering Validation Indices for Mapping Mineral Prospectivity: Combination of Multifractal Geochemical Model and Mineralization Processes

This paper describes the application of an unsupervised clustering method, fuzzy c-means (FCM), to generate mineral prospectivity models for Cu?±?Au?±?Fe mineralization in the Feizabad District of NE Iran. Various evidence layers relevant to indicators or potential controls on mineralization, including geochemical data, geological–structural maps and remote sensing data, were used. The FCM clustering approach was employed to reduce the dimensions of nine key attribute vectors derived from different exploration criteria. Multifractal inverse distance weighting interpolation coupled with factor analysis was used to generate enhanced multi-element geochemical signatures of areas with Cu?±?Au?±?Fe mineralization. The GIS-based fuzzy membership function MSLarge was used to transform values of the different evidence layers, including geological–structural controls as well as alteration, into a [0–1] range. Four FCM-based validation indices, including Bezdek’s partition coefficient (V_Pc) and partition entropy (V_Pe) indices, the Fukuyama and Sugeno (V_FS) index and the Xie and Beni (V_XB) index, were employed to derive the optimum number of clusters and subsequently generate prospectivity maps. Normalized density indices were applied for quantitative evaluation of the classes of the FCM prospectivity maps. The quantitative evaluation of the results demonstrates that the higher favorability classes derived from V_FS and V_XB (N_d?=?9.19) appear more reliable than those derived from V_Pc and V_Pe (N_d?=?6.12) in detecting existing mineral deposits and defining new zones of potential Cu?±?Au?±?Fe mineralization in the study area.

     

Integrated Petrophysical Modeling for a Strongly Heterogeneous and Fractured Reservoir,Sarvak Formation,SW Iran

Introducing and applying an appropriate strategy for reservoir modeling in strongly heterogeneous and fractured reservoirs is a controversial issue in reservoir engineering. Various integration approaches have been introduced to combine different sources of information and model building techniques to handle heterogeneity in geological complex reservoir. However, most of these integration approaches in several studies fail on modeling strongly fractured limestone reservoir rocks of the Zagros belt in southwest Iran. In this study, we introduced a new strategy for appropriate modeling of a production formation fractured rock. Firstly, different rock types in the study area were identified based on well log data. Then, the Sarvak Formation was divided into nine zones, and the thinner subzones were used for further fine modeling procedure. These subzones were separated based on different fracture types and fracture distribution in each zone. This strategy provided sophisticated distribution of petrophysical parameters throughout the grids of the model, and therefore, it can handle strong heterogeneity of the complex reservoir. Afterward, petrophysical parameters were used to produce an up-scaled 3D gridded petrophysical model. Subsequently, maps of petrophysical properties were derived for each zone of the Sarvak Formation. Evidences achieved in this study indicates Sarvak Formation zone 2 as the target production zone with better performance of reservoir rock and the southwestern part of the field as area of maximum porosity.     

Stochastic Simulation of Patterns Using Distance-Based Pattern Modeling

The advent of multiple-point geostatistics (MPS) gave rise to the integration of complex subsurface geological structures and features into the model by the concept of training images. Initial algorithms generate geologically realistic realizations by using these training images to obtain conditional probabilities needed in a stochastic simulation framework. More recent pattern-based geostatistical algorithms attempt to improve the accuracy of the training image pattern reproduction. In these approaches, the training image is used to construct a pattern database. Consequently, sequential simulation will be carried out by selecting a pattern from the database and pasting it onto the simulation grid. One of the shortcomings of the present algorithms is the lack of a unifying framework for classifying and modeling the patterns from the training image. In this paper, an entirely different approach will be taken toward geostatistical modeling. A novel, principled and unified technique for pattern analysis and generation that ensures computational efficiency and enables a straightforward incorporation of domain knowledge will be presented.     

Seismic performance and design of bridge column-to-pile shaft pipe-pin connections in precast and cast-in-place bridges

Hinge or “pin” connections may be used in integral bridges to connect columns to pile shafts to reduce the foundation force demand. Used in combination with prefabricated columns, pins facilitate accelerated bridge construction (ABC). These innovative methods could improve the quality and economy of project compared with conventional construction in seismic regions. This study developed pipe pins that reduce moment transfer between the column and pile shaft under seismic excitations. The pipe pins consist of two steel pipes and a rod that transfer shear and tension while allowing rotation between the column and shaft. The primary objective of this research was to investigate the seismic performance and develop design guidelines of column-to-pile shaft pipe pins for cast-in-place and precast constructions. This research was composed of experimental and analytical studies. The experimental portion of the study consisted of testing of a large-scale bent model subjected to seismic loadings. The test results confirmed that the proposed design method meets the safety and performance requirements of the codes under seismic loadings. The pins maintained structural integrity with minimal damage, while the columns reached the full plastic hinge capacity. The analytical studies consisted of (a) a simple stick model to be used as a design tool, (b) a finite element model (FEM) for global analysis of bridges, and (c) an elaborate FEM to investigate the microscopic performance and interaction of the components. The analytical models were subsequently used in parametric studies.     

Building service life economic loss assessment under sequential seismic events

Aftershocks have been shown to exacerbate earthquake‐induced financial losses by causing further damage to structural and nonstructural components in buildings that have already been affected by a mainshock event and increasing the duration of disrupted functionality. Whereas seismic loss assessment under isolated events has been addressed thoroughly in previous studies, comparatively less has been accomplished in the area of loss assessment under sequences of mainshock‐aftershock ground motions. The main objective of the current study is to formulate a comprehensive framework for quantifying financial losses under sequential seismic events. The proposed framework is capable of accounting for the uncertainties in the state of structure due to accumulation of earthquake‐induced damage, the time‐dependent nature of seismic hazard in the post‐mainshock environment, and the uncertainties in the occurrence of mainshock and aftershock events. Application of the proposed framework to a 4‐story reinforced concrete moment frame shows that consideration of aftershocks could increase lifecycle earthquake‐induced losses by up to 30% compared with mainshock‐only assessments.