Geochemical and geochronological evidence for a Middle Permian oceanic plateau fragment in the Paleo-Tethyan suture zone of NE Iran

The mafic–ultramafic Fariman complex in northeastern Iran has been interpreted as a Paleo-Tethyan ophiolitic fragment with subduction- and plume-related characteristics as well as a basin deposit on an active continental margin. Contributing to this issue, we present geochemical, geochronological, and mineralogical data for transitional and tholeiitic basalts. Thermodynamic modeling suggests picritic parental magmas with 16–21 wt% MgO formed at plume-like mantle potential temperatures of ca. 1460–1600 °C. Rare pyroxene spinifex textures and skeletal to feather-like clinopyroxene attest to crystallization from undercooled magma and high cooling rates. Chromium numbers and TiO₂ concentrations in spinel are similar to those in intraplate basalts. ⁴⁰Ar–³⁹Ar dating of magmatic hornblende yielded a plateau age of 276?±?4 Ma (2σ). Transitional basalt with OIB-like trace element characteristics is the predominant rock-type; less frequent are tholeiitic basalts with mildly LREE depleted patterns and picrites with intermediate trace element characteristics. All samples show MORB-OIB like Pb/Ce, Th/La, and Th/Nb ratios which preclude subduction-modified mantle sources and felsic crustal material. Tholeiitic basalts and related olivine cumulate rocks show MORB-like initial ε_Nd values of +?9.4 to +?6.2 which define a mixing line with the data for the transitional basalts (ε_Nd ca. +?2.6). Initial ¹⁸⁷Os/¹⁸⁸Os ratios of 0.124–0.293 support mixed sources with a high proportion of recycled mafic crust in the transitional basalts. High concentrations of highly siderophile elements are in agreement with the high mantle potential temperatures and inferred high-melting degrees. It is argued that the Fariman complex originated by melting of a mantle plume component as represented by the OIB-like transitional basalt and entrained asthenosphere predominant in the MORB-like tholeiites. Two lines of evidence such as association of the Fariman complex with pelagic to neritic sedimentary rocks and the tectonic position at the boundary of two continental blocks defined by ophiolites and accretionary complexes of different ages suggest formation in an oceanic domain. Thus, we interpret it as a fragment of an oceanic plateau, which escaped subduction and was accreted as exotic block in the Paleo-Tethyan suture zone.     

Investigation of RS and GIS techniques on MPSIAC model to estimate soil erosion

Soil erosion due to surface water is a standout among the serious threat land degradation problem and an hazard environmental destruction. The first stage for every kind of soil conservation planning is recognition of soil erosion status. In this research, the usability of two new techniques remote sensing and geographical information system was assessed to estimate the average annual specific sediments production and the intensity erosion map at two sub-basins of DEZ watershed, southwest of Lorestan Province, Iran, namely Absorkh and Keshvar sub-basins with 19,920 ha, using Modified Pacific Southwest Inter-Agency Committee (MPSIAC) soil erosion model. At the stage of imagery data processing of IRS-P6 satellite, the result showed that an overall accuracy and kappa coefficient were 90.3% and 0.901, respectively, which were considered acceptable or good for imagery data. According to our investigation, the study area can be categorized into three level of severity of erosion: moderate, high, and very high erosion zones. The amount of specific sediments and soil erosion predicted by MPSIAC model was 1374.656 and 2396.574 m³ km^?2 year^?1, respectively. The areas situated at the center and south parts of the watershed were subjected to significant erosion because of the geology formation and ground cover, while the area at the north parts was relatively less eroded due to intensive land cover. Based on effective of nine factors, the driving factors from high to low impact included: Topography > Land use > Upland erosion > Channel erosion > Climate > Ground cover > Soil > Runoff > Surface geology. The measured sediment yield of the watershed in the hydrometric station (Keshvar station) was approximately 2223.178 m³ km^?2 year^?1 and comparison of the amount of total sediment yield predicted by model with the measured sediment yield indicated that the MPSIAC model 38% underestimated the observed value of the watershed.     

Nitrogen,phosphorus and sulfur mineralization as affected by soil depth in rangeland ecosystems

The potential mineralization and immobilization of soil nitrogen (N), phosphorus (P) and sulfur (S) are relatively high in natural ecosystems. This study was conducted to investigate the changes in essential plant macronutrients; N, P, and S status in response to different soil depth in rangeland ecosystems in vitro. The net nutrient mineralization was measured during 90 days at different depths (0–15, 15–30, 30–45 and 45–60 cm), using kinetic models to estimate the release rate. The net ammonification and mineralization of P and S were described using parabolic diffusion equation, while the power function equation was used to describe the net nitrification. The results indicated that the amount of released ammonium (NH₄ ⁺) decreased with time and depth and the rates of net ammonification were negative in all samples. Conversely, nitrification increased with time and depth and the rates were all positive. The net mineralization for both P and S reduced with time. The concentration of mineralized SO₄ ^2? increased with depth like nitrate (NO₃ ^?). Accumulation of SO₄ ^2? and NO₃ ^? in subsurface soils and NH₄ ⁺ and P at surface horizons can increase the potential of their loss by leaching or volatilization.     

Groundwater quality assessment using entropy weighted water quality index (EWQI) in Lenjanat,Iran

Human health is strongly influenced by water quality which is threatened by the poor quality of polluted groundwater. In this study, the groundwater quality and its suitability for drinking have been studied in Lenjanat plain aquifer, Iran. Fifty-nine groundwater samples from study area were evaluated based on WHO and Iranian standards for drinking water. Groundwater samples from selected monitoring sources were sampled seasonally during 2009–2010. Physical and chemical parameters of groundwater such as electrical conductivity, pH, total dissolved solids, Ca²⁺, Na⁺, K⁺, Mg²⁺, HCO₃ ^?, SO₄ ^2?, Cl^?, F^? and NO₃ ^? were determined. During the water quality index calculating process, the weight of each parameter is usually given by experts according to their practical experience, which is subjective, so much useful and valuable information about the water quality gets lost. In order to avoid personal judgments about the weight of parameters, an information entropy method was used to assign weight to each parameter. Calculation of entropy weighted water quality index (EWQI) for groundwater samples showed that in the wet season, over 57 and 74 % of samples were in the range of “excellent” to “medium” quality based on WHO and Iranian standards, respectively. Due to groundwater quality reduction during dry season, 42 and 62 % of samples were in the range of “excellent” to “medium” quality based on WHO and Iranian standards, respectively. The results indicate that application of the EWQI is very useful to help the public and decision-makers will be able to identify and to evaluate groundwater quality in Lenjanat, Iran.     

Lithological facies identification in Iranian largest gas field: A comparative study of neural network methods

Determination of different facies in an underground reservoir with the aid of various applicable neural network methods can improve the reservoir modeling. Accordingly facies identification from well logs and cores data information is considered as the most prominent recent tasks of geological engineering. The aim of this study is to analyze and compare the five artificial neural networks (ANN) approaches with identification of various structures in a rock facies and evaluate their capability in contrast to the labor intensive conventional method. The selected networks considered are Backpropagation Neural Networks (BPNN), Radial Basis Function (RBF), Probabilistic Neural Networks (PNN), Competitive Learning (CL) and Learning Vector Quantizer (LVQ). All these methods have been applied in four wells of South Pars field, Iran. Data of three wells were employed for the networks training purpose and the fourth one was used to test and verify the trained network predictions. The results have demonstrated that all approaches have the ability of facies modeling with more than 65% of precision. According to the performed analysis, RBF, CL and LVQ methods could model the facies with the accuracy between 66 and 68 percent while PNN and BPNN techniques are capable of making predictions with more than 72% and 88.5% of precision, respectively. It can be concluded that the BPNN can generate most accurate results in comparison to the other type of networks but it is important to note that the other factors such as consuming the amount of time taken, simplicity and the less adjusted parameters as well as the acquired precisions should be considered. As a result, the model evaluation analysis used in this study can be useful for prospective surveys and cost benefit facies identification.     

Numerical study of power production from tidal energy in the Khuran Channel and its feedback on background hydrodynamics

This study focuses on the development of a farm of tidal turbines in the Khuran Channel. The important factors include the location of turbines and their hydrodynamic effects on the environment. A three-dimensional circulation model for the Persian Gulf is employed for the comprehensive evaluation of the tidal energy potential throughout the study area. The model is validated by using in situ observations of water level and current data.The appropriate potential points for extracting the tidal e...     

The origin of oil in the Cretaceous succession from the South Pars Oil Layer of the Persian Gulf

The origin of the oil in Barremian–Hauterivian and Albian age source rock samples from two oil wells (SPO-2 and SPO-3) in the South Pars oil field has been investigated by analyzing the quantity of total organic carbon (TOC) and thermal maturity of organic matter (OM). The source rocks were found in the interval 1,000–1,044 m for the Kazhdumi Formation (Albian) and 1,157–1,230 m for the Gadvan Formation (Barremian–Hauterivian). Elemental analysis was carried out on 36 samples from the source rock candidates (Gadvan and Kazhdumi formations) of the Cretaceous succession of the South Pars Oil Layer (SPOL). This analysis indicated that the OM of the Barremian–Hauterivian and Albian samples in the SPOL was composed of kerogen Types II and II–III, respectively. The average TOC of analyzed samples is less than 1 wt%, suggesting that the Cretaceous source rocks are poor hydrocarbon (HC) producers. Thermal maturity and Ro values revealed that more than 90 % of oil samples are immature. The source of the analyzed samples taken from Gadvan and Kazhdumi formations most likely contained a content high in mixed plant and marine algal OM deposited under oxic to suboxic bottom water conditions. The Pristane/nC₁₇ versus Phytane/nC₁₈ diagram showed Type II–III kerogen of mixture environments for source rock samples from the SPOL. Burial history modeling indicates that at the end of the Cretaceous time, pre-Permian sediments remained immature in the Qatar Arch. Therefore, lateral migration of HC from the nearby Cretaceous source rock kitchens toward the north and south of the Qatar Arch is the most probable origin for the significant oils in the SPOL.     

Rock Type Connectivity Estimation Using Percolation Theory

Complicated sedimentary processes control the spatial distribution of geological heterogeneities. This serves to make the nature of the fluid flow in the hydrocarbon reservoirs immensely complex. Proper modeling of these heterogeneities and evaluation of their connectivity are crucial and affects all aspects of fluid flow. Since the natural variability of heterogeneity occurs in a myriad of length scales, accurate modeling of the rock type connectivity requires a very fine scheme, which is computationally very expensive. Hence, this makes other alternative methods such as the percolation approach attractive and necessary. The percolation approach considers the hypothesis that a reservoir can be split into either permeable (sand/fracture) or impermeable rocks (shale/matrix). In this approach, the connectivity of the permeable fraction governs the flow. This method links the global properties of the system to the density of the permeable objects distributed randomly in the system. Moreover, this approach reduces many results to some simple master curves from which all-possible outcomes can be predicted by simple algebraic transformations. The current study contributes to extending the applicability of the methodology to anisotropic systems as well as using the complicated and more realistic sandbody shapes (for example, ellipsoids). This enables us to attain a better assessment of the connectivity and its associated uncertainty of the complicated rock types. Furthermore, to validate the approach, the Burgan reservoir dataset of the Norouz offshore oil field in the south of Iran was used. The findings are in conformity with the percolation approach predictions.     

Seismicity Characterization of Iran: A Multivariate Statistical Approach

This paper presents the results of two multivariate analysis techniques—principal component and cluster analysis—as they are applied to the seismicity characterization of Iran. The seismic data used in this study covers a period of 50 years, from the beginning of 1957 to the end of 2006. The values of eight seismic variables were calculated on a grid of equally spaced points at one geographic degree spacing in both latitude and longitude. The data matrix was analyzed using principal component and cluster analysis. Principal component analysis identified two significant components, introduced in this study as the Seismic Frequency Index (SFI) and the Seismic Severity Index (SSI), responsible for the data structure. The SFI and SSI explain 34.34 % and 32.33 % of the total variance of the data set, respectively, and allowed grouping of the selected variables according to their common features. The standardized data matrix was analyzed using Ward’s clustering method. The resulting seismicity pattern recognition maps of the region at three levels of similarity are presented. From these maps, differentiated seismic zones are outlined in detail and compared quantitatively. Comparison between the seismic zoning maps obtained in this analysis and the general tectonic map of the region indicates that the seismic zones are consistent with the tectonic zones of the region. This study presents the necessity and usefulness of multivariate analysis in evaluating and interpreting seismic data catalogues with the goal of obtaining more objective information about the seismicity pattern of regions.