فهرست مطالب

Earth Sciences - Volume:11 Issue: 4, Oct 2019

Iranian Journal of Earth Sciences
Volume:11 Issue: 4, Oct 2019

  • تاریخ انتشار: 1398/07/09
  • تعداد عناوین: 6
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  • Uwe, M. Troppenz *, Sven Littkowski Pages 239-243
    The authors show that the Mesoproterozoic (1.6-1.0 bn year before present) was no “boring billion” but a “bustling billion” - not only with Stromatolites and their apex in the Calymmian and Ectasian but also with the presence of multicellular organisms. To make it visible a graphical reconstruction was created. For a long time, it was assumed that there existed no noteworthy biosphere on Earth before the Ediacaran (635-542 m year before present) – aside from bacteria which were responsible for the Stromatolites.  In literature, they called this age the “boring billion”. This term is preserved until today, despite that scientific research came to another result. In the books “Wohin die Spuren führen” (Troppenz 2015) and The New Precambrian“ (Troppenz 2017) the actual status of knowledge was compiled, and term “boring billion” replaced by “bustling billion”. Term “Montana Biota” (first location of Horodyskia) was established for the definitely existing biosphere. For the first time, the authors make an attempt to reconstruct life in the period between 1.88 and 0.78 bn, and revive the “bustling billion”.
    Keywords: Precambrian, Mesoproterozoic, multicellular life, boring billion, bustling billion, Montana Biota, reconstruction
  • Somayeh Ghandhari, Arash Amini *, Ali Solgi, Hamed Rezaei Pages 244-255
    This study was performed to recognize the loess texture in Golestan Province, Iran using the microstructure analysis according to the electron microscopic images. Loess microstructure study allows for investigating the characteristics of particle shape, fabric, cement and porosity in microscopic images. In recent years, computer analysis has been replaced with manual calculation due to its high speed, precision and ease of use. Since the scanning electron microscope (SEM) digital image analysis method can quantitatively determine the loess microstructure and identify the microstructure changes, it was used to analyze the loess texture. The obtained results showed that the loess microstructure changed from north and northeast to south and southwest of Golestan Province. According to microstructural and sedimentology parameters, Golestan Province loess can be divided into 4 zones. The results also showed that microstructural study of loess sediments in Golestan Province could be a useful tool for loess zoning and separating loess sediments from loess-like deposits.
    Keywords: Loess, Microstructure Analysis, Particle Shape, Fabric, Scanning Electron Microscope (SEM)
  • Hamed Abdoli Sereshgi, Alireza Ganji *, Afshin Ashja Ardalan, Habibollah Torshizian, Jafar Taheri Pages 256-266
    The Zouzan area is located in the SE of Torbat-e- Heydarieh city (NE Iran). This area is located on north part of the Lut block which consists of basaltic andesite, tuff and porphyritic andesite. The purpose of this research is to investigate the enrichment of metal elements in the Zouzan area and provide a metallic geochemical model. For this purpose, 488 stream samples were analyzed using by ICP-MS. The results were interpreted using staged factor analysis to determine the components that are rich in the study area. However, Concentration-Number (C-N) fractal modeling was used for interpretation of these data and presenting a final model. The results of this study indicate the concentration of anomalies of the Au, Ag, Cu, Pb and Zn as main elements in the central, NE and SW of the Zouzan area. Moreover, results obtained by the staged factor analysis shows the elements of the specified components by this method that enriched together in the study area. The place of enrichment is in the central NE and SW parts of the study area.
    Keywords: Zouzan, Geochemical anomalies, Staged factor analysis, Concentration-Number (C-N) fractal modeling
  • Ata Eshaghzadeh *, Sanaz Seyedi Sahebari, Roghayeh Alsadat Kalantari Pages 267-276
    In this paper, modular neural network (MNN) inversion has been applied for the parameters approximation of the gravity anomaly causative target. The trained neural network is used for estimating the amplitude coefficient and depths to the top and bottom of a finite vertical cylinder source. The results of the applied neural network method are compared with the results of the least-squares standard deviation method. The inverse modeling has been tested first on synthetic gravity data. The synthetic data are infected with random noise to evaluate the effect of noise on performance of the methods. Both methods show satisfactory results, with and without random noise. The MNN and least squares standard deviation approaches have been applied to two real gravity data due to two salt domes from Iran and USA, where the results comparison shows good agreement with each other. The computed standard errors indicate the generated gravity response of the estimated parameters from MNN has better conformity with the observed gravity anomaly than the generated gravity response from the least squares method. The results of the MNN inversion show the top and bottom depths of the salt dome situated in Iran are about 24.5 m and 63.8 m and for the salt dome situated in USA are about 1451 m and 9263 m, respectively.
    Keywords: Salt Dome, Finite Vertical Cylinder, Least-Squares Standard Deviation, Modular Neural Network (MNN)
  • Mehdi Kianpour, Seyed Mahmoud Fatemi Aghda *, Mehdi Talkhablou Pages 277-289

    The purpose of this study was to develop a model for the estimation of rock mass classification of Sarvak limestone in the Bakhtiari dam site, south-west (SW) Iran. Q system had been used as the starting point for the rock mass classification. This method was modified for sedimentary rock mass which is known as Qsrm. Because Qsrm considers a wide range of rock mass properties, it has become a tool for rock mass classification that more correlates with geophysical parameters. This study tried to revise and empower the correlation between P-wave velocity (Vp) with Q and Qsrm in Sarvak limestone. By using data sets of Bakhtiari Dam Site (BDS) in SW Iran and multivariate regression and the Fuzzy Inference System (FIS), models were rendered for prediction of Q and Qsrm. About 700 sets of data were used for modeling and Vp was considered as the input parameter. The regression equations showed the relationship between Vp with Q and Qsrm,under conditions of quadratic relations, obtained coefficients of determination (R2) of 0.49 and 0.66, respectively. The correlation coefficient was calculated as 0.82 for the Qsrm obtained from FIS models. Also, Variance Accounted For (VAF) and Root Means Square Error (RMSE) indexes were also used for evaluation of prediction accuracy of models. Results showed that Vp has better performance in prediction of Qsrm than Q and theFIS model showed the best prediction results. Because these models have accuracy, they could be used in similar conditions.

    Keywords: Rock Mass Quality, Sarvak Limestone, P-Wave Velocity, Empirical Equations, Fuzzy Inference System
  • Bita Javidfakhr *, Seiran Ahmadian Pages 290-304
    Active deformation in Alborz range is due to N-S convergence between Arabia and Eurasia. This paper provides geomorphic traces of regional deformation in NW Iran in order to characterize active faulting on major faults. Soltanieh and North Zanjan fault systems are involved in convergence boundary extent between South Caspian Basin and Central Iran. Soltanieh and North Zanjan faults are major reverse faults in the study area. Soltanieh fault has been probably responsible for historical Soltanieh earthquake in 1803. Accurate mapping accompanied by field observations enabled offset determination along active faults. We presented geomorphic documents indicating left-lateral strike-slip movements in Soltanieh fault zone. Kinematics is achieved through analyzing inversion results obtained from kinematic measurement sites which are generally scattered along Soltanieh fault zone. Fault kinematic data inversion results (slip-vector measurement in fault planes) indicate a dominant NE trending horizontal maximum stress axis (σ1). Kinematic inversion results infer reverse faulting mechanism accompanied by strike-slip component.
    Keywords: Zanjan, Soltanieh Fault, Earthquake, Quaternary, Offset