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فهرست مطالب نویسنده:

mohammad zamanzadeh

  • Ebrahim Sefidari *, Javad Amraie, Houshang Mehrabi, Mohammad Zamanzadeh
    This study focuses on the facies modeling and reservoir characterization of the Permian-Triassic age Dalan and Kangan formations, defined as the main reservoirs in the giant South Pars Gas Field in the Persian Gulf. Based on the main characteristics on petrographical observations, 12 facies are identified and classified into 4 facies associations representing tidal flat (LFAs 1), lagoon (LFAs 2), shoal (LFAs 3), and open marine (LFAs 4) conditions on a carbonate ramp. In uncored wells, a neural network approach (self-organizing maps) was employed to predict litho-facies and litho-facies associations (LFAs). The method was found satisfactory (87.5%) in litho-facies prediction using GR, DT, NPHI, RHOB, and PEF logs. The predicted LFAs were compared with the core-derived facies and rock types to generate a 2D facies model within the sequence stratigraphy framework for geologic modeling and subsequent reservoir simulation. Finally, geostatistical techniques are employed to prepare a 3D facies distribution and depositional model for the entire field. The stochastic simulation method was applied here to simulate and generate the 3D model of 4 major LFAs were involved in the modeling representing LFAs 1, LFAs 2, LFAs 3, and LFAs 4. Facies modeling of the formations indicates a gentle shallowing from zone K4 to zone K3. The connectivity of LFAs 3 is well observed in zone K4, whereas in zone K3 the connectivity of LFAs 2 is evident. Zone K2 is associated with dominant LFAs 3 and minor LFAs 4. The zone K1 is characterized by the dominance of LFAs 1.
    Keywords: Litho-Facies, Log Facies, Reservoir Simulation, South Pars Gas Field, Carbonate Reservoir, Persian Gulf
  • Mohammad Zamanzadeh *, Akbar Sadighi
    Utilizing Killing frames on homogeneous Finsler manifolds, we express the Berwald and mean Berwald curvatures in terms of Killing frames and get some rigidity results among them we prove that homogeneous isotropic weakly Berwald metrics reduce to weakly Berwald metric.
    Keywords: Homogeneous Finsler Metrics, Berwald Metric, Weakly Berwald Metric
  • Mohsen Ranjbaran *, Mohammad Zamanzadeh
    Qeshm Island is the largest island in the Persian Gulf, similar to a dolphin in shape. The island is located at the mouth of the Strait of Hormuz in Hormuzgan Province, Iran. The Island is dolphin-shaped, and most of the outcrops include sedimentary rocks. Qeshm is one of the most beautiful Islands of the Persian Gulf and due to its special geographic location has many beautiful natural and geological phenomena. Qeshm Island has a variety of cultural, handiworks, and local architecture as well as geological diversity. The geological formations of this belt may range from the late Precambrian to Cambrian in age and include diapirs called the Hormuz Series. Most of the mature salt diapirs formed in the Qeshm and the longest salt cave was created in the west of the island in a series of Hormuz Formation. The main geotourism attractions of the island include different forms resulting from erosion, as well as very attractive geomorphologic structures such as Star Valley, Khorbas Cave, Mangrove forest, Roof of Qeshm, and Chah-Kuh Gorge, Salt Cave, coral reefs, etc. Most of the landscapes are the product of wind and water erosion. Qeshm Island is one of the numerous places in Iran rich in many geologic, ecologic, cultural, and historic attractions and unique for geotourism and ecotourism. In addition to the geological and natural attractions of the region, the ancient and cultural features are included in the potential of the island’s tourism attraction. This study introduces geotourism attractions in Qeshm Island.
    Keywords: Geotourism, Qeshm Island, Persian Gulf, geosite salt dome, cultural tourism
  • ابوالقاسم گورابی*، محمد زمانزاده، مجتبی یمانی، پریسا پیرانی

    تغییرات مکانی پارامترهای فرکتالی عامل مهمی برای بررسی وضعیت زمین ساختی است. در هندسه فرکتال، بعد فرکتال در هر مقیاسی، حفظ می شود که بیانگر خاصیت اصلی فرکتال است. در این تحقیق به منظور بررسی کارایی روش فرکتال در بررسی زمین ساخت زاگرس شمال غرب، به مقایسه و آزمون یکسان بودن نتایج ابعاد فرکتالی گسل ها در نقشه هایی با مقیاس های مختلف، و زمین لرزه هایی با طول دوره و جزییات و مقیاس های مختلف بزرگا پرداخته شد. برای این منظور از 6 لایه اطلاعاتی استفاده گردید و ابعاد فرکتالی آن ها به روش مربع شمار محاسبه و نتایج بعد فرکتالی آن ها مورد تحلیل قرار گرفته اند. دو دسته داده گسلی مستقیما و دو دسته داده زمین لرزه (پژوهشگاه بین المللی زلزله و موسسه ژیوفیزیک) یکبار بدون تغییر و دیگر بار برای افزایش دقت با احتساب بزرگای کمال وارد محاسبات شدند. نتایج نشان می دهد که ابعاد هندسی گسل های منطقه فرکتالی است و تنها تفاوت در ثبت جزییات گسل ها سبب تغییری جزیی در ترتیب مناطق فعال در دو مقیاس شده است و نتایج دو مقیاس تقریبا مشابه است. در مورد داده های لرزه ای نتایج داده های از 1900 تا 2020 که از تعداد کمتر زمین لرزه و مقیاس مختلف ثبت بزرگا برخوردارند تطبیقی با واقعیت نشان نمی دهند، در صورتی که می توان به نتایج ابعاد فرکتالی داده های زمین لرزه های منحصرا سده 20 که از نظر دقت و مقیاس ثبت بزرگا یکسان هستند، اعتماد نمود. نتایج آن، فعال ترین منطقه از نظر بعد فرکتالی را محدوده غرب کرمانشاه نشان می دهد و  شاهد آن تمرکز زمین لرزه هایی با بزرگای بالاتر به ویژه زمین لرزه اخیر کرمانشاه با بزرگای 7/3 است که تلفات فراوانی به دنبال داشت.

    کلید واژگان: فرکتال، زمین ساخت، زاگرس شمال غرب، گسل، زمین لرزه
    Abolghasem Goorabi*, Mohammad Zamanzadeh, Mojtaba Yamani, Parisa Pirani
    Introduction

    Complexity of natural processes especially tectonic processes that shape landscapes cannot be evaluated by classic geometry. In comparison with integer dimension of Euclidean space, fractal geometry can analyze features with non-integer dimension (Turcotte, 1977:121). Fractal behavior in such features shows self-similarity that this component is independent of the accuracy of investigation (Baas, 2002, 311). In fact, fractal dimension, is scale-invariant (Phillips, 2002, 144). Spatial variations of fractal parameters are an important factor in studying the tectonic state of regions. By determining the fractal dimension of Linear structures such as faults, it is possible to compare their geometry disorder (Suk moon et al, 1996:5). This parameter affects seismic behavior of fault because earthquake is an event related to faulting (Bachmanov, et al, 2012: 221) and Their concentration in an area indicates tectonic activity. In this research we performed fractal analysis using box counting method on fault and seismic data of northwest of Zagros about different scales of fault and different time periods of earthquake epicenters of two organizations with various detail to find and examine their fractal behavior by fractal dimension.

    Methods

    Data in this research can be divided to three clusters: 1. Fault lines of two scales of geology maps (1:100000 and 1:250000), 2. Earthquake epicenters of two periods of times prepared by two organizations (20 century data of Institute of Geophysics and 1900-2020 data of International Institute of Earthquake Engineering and Seismology) and 3. The second cluster with exert of Magnitude of completeness of earthquakes that show the minimum magnitude above which the data in the earthquake catalog is complete. Fractal analysis applied on these data by box counting method. To achieve this goal firstly, under study area divided to 6 boxes that contain main fault trends horizontally and vertically (A: folded Zagros in west of Kermanshah, B: faulted Zagros around Kermansha and east of kermansha, C: folded Zagros near mountain front fault, D: An area between faulted and folded Zagros near Khoramabad, E: Area around Balarud fault and F: An area between Balarud and mountain front fault to faulted Zagros). To calculate fractal dimension of fault lines and distribution of earthquake epicenters, box counting method suggested by Turcotte (1997) were applied by using Hausdorff dimension, which in two quantity of size (side length of grids) and number (number of grid boxes containing earthquake epicenter or fault) are used to calculate FD (total fractal dimension) value (Schuller et al, 2001: 3). Relation between reciprocal of side length (quantity of size) and number of boxes containing point and linear features (quantity of Number) was drawn Logarithmically as a linear regression in Excel that shows fractal dimension.

    Result and discussion

    Larger values of fractal dimension indicate greater geometric disorder (Sukmono et al., 1996: 5). Analysis of faults of two scales represent that faults geometry is fractal and the amount of FD for scale of 1:100000 compared with scale of 1:250,000 is larger but their result approximately is same. The FD values for both scales are locate between 1 and 2 that expresses development of the fractal community of faults has a linear trend. On the other hand, for earthquakes, increase in FD values shows that earthquakes are not clustered and are distributed homogeneously (Oncel & Wilson, 2002: 339) along a line in understudy area. Calculated number-size values for faults and earthquakes represent both partial and popular FD changes. Based on partial FD, two populations can be classified: (a) Background with FD larger than popular FD; (b) Threshold with FD lower than popular FD.

    Conclusion

    Fractal analysis of faults of two scales of geology maps reveals that the order of active areas with high FD values in both scales are same but due to different details of faults in geology maps of geology survey and oil company, in scale of 1:100000 area labeled B and in scales of 1:250000 area labeled A is the most tectonically active region, however, area labeled E in both scales has lowest value. The order of active areas based on FD values for earthquake epicenters of 1900-2021 data of geophysics institute do not support other results because area labeled C with low density of faults and earthquake epicenters is in the first order and area labeled A is on the contrary of it. However, FD results of 20 century earthquake epicenters with exert of magnitude of completeness are reliable and higher magnitude of earthquakes spatially recent Ezgeleh earthquake in area labeled A is its evidence.

    Keywords: Fractal, Tectonic, Northwest Zagros, Fault, Earthquake
  • سید محمد زمان زاده، اسماعیل پاریزی، مهدی امینی
    دولین یکی از لندفرم های شاخص مناطق کارستی است که در اثر عوامل و فرآیندهای گوناگونی شکل می گیرد. مطالعه مورفومتریک این عوارض علاوه بر اینکه یک تحلیل کمی از محیط های کارستی را فراهم می کند، بلکه مقایسه پارامترهای متنوع دولین ها ممکن است منجر به طرح فرضیاتی در مورد نحوه تکامل آن ها شود. هدف از این پژوهش تجزیه وتحلیل کمی مولفه های مورفومتری دولین ها جهت مدل سازی و ارائه شاخص بعد فرکتال گسل ها برای ارزیابی فعالیت گسل ها در مناطق کارستی بین پرآو و شاهو است. در این راستا از روش های ژئومورفومتری، CCLs، شمارش جعبه ای هاسدورف و تکنیک های آنالیز رگرسیون استفاده شده است تا امکان تحلیل رگرسیون، مدل سازی و حل تابع لگاریتمی Number – Size فراهم شود. نتایج آنالیز رگرسیون خطی تک متغیره نشان دهنده این است که مولفه های محیط با قطر بزرگ، قطر کوچک با محیط، قطر بزرگ با مساحت، مساحت با محیط و عمق با مساحت به ترتیب با ضرایب تبیین 93/0، 86/0، 85/0، 83/0 و 668/0 از بیشترین میزان همبستگی معنی دار برخوردارند. همچنین حداکثر ارتباط معنی داری برای روابط درجه 2 و 3 در سطح معنی داری 99/0، بین مولفه های مساحت و محیط با ضرایب تبیین 940/0 و 945/0 و خطای برآورد 05/0 و 04/0 وجود دارد. نتایج رگرسیون چند متغیره خطی نیز موید ارتباط معنی دار عمق با پارامترهای شیب، قطر کوچک و مساحت با ضریب تبیین 834/0 و خطای برآورد 85/7 است. تخمین بعد فرکتال در مناطق مورد مطالعه موید آن است که منطقه شاهو و پرآو به ترتیب با مقادیر 24/1 و 15/1 دارای بیشینه و کمینه ابعاد فرکتالی گسل ها می باشند. در واقع ارزیابی میزان فعالیت گسل ها به وسیله هندسه فرکتال نشان داد که معادله Number – Size و شاخص بعد فرکتال روشی مناسب جهت ارزیابی گسل ها در مناطق کارستی می باشند.
    کلید واژگان: دولین، مورفومتری، آنالیز رگرسیون، بعد فرکتال، معادله Number، Size
    Mohammad Zaman Zadeh, E. Parazi, M. Amini
    Introduction Karst is a geomorphic and hydrologic system which is created due to the dissolution of soluble stones like lime, dolomite and Gypsum (Ozyurt et al., 2014). The development of a karstic system is dependent upon climactic, lithologic and structural (wrinkle, fault and gap) factors (Ford and Williams, 2013). The most important landforms in the created perspectives include carnic bands, dolines and swallowing gaps. These shapes are usually but not necessarily formed in the areas which suffer from a fracture or a gap (Kovacic & Ravbar, 2013). Nowadays the theory of fractal collections and multifractal measuring is extensively used in describing some natural processing like the activity of faults (Ayunova et al., 2007 & Feder, 1988). In fact the process of fault creation can be investigated through fractal concepts (Mandelbrot 1983 & Sarp 2014). As the behavior of the faults certainly nonlinear (Turcottee, 1990) and the fractal theory is a method for determining and predicting complex dynamic nonlinear behaviors (Yang et al., 2007) this method can be used to examine the behavior of faults (Torcotte, 1997).
    Materials and instrumentation Initially the dolines of the target areas were extracted on the basis of DEM10 meter and method CCLs. after extracting these dolines their morphometric factors which consisted of area, perimeter, depth, slope, large diameter and small diameter were calculated in GIS software. Following that the SPSS software was utilized for the descriptive and regressive analysis the morphometric parameters of dolines. To this end single and multivariable variable linear methods were employed and those models which were of more value were presented.
    1/100000 geological maps of Kermanshah, Kamiaran, Miyan Rahan and Paweh were used to determine the fault systems of the examined areas and extract their fault maps. Afterwards, since the faults followed a vector shape, the Number-Size equation was selected to calculate the fractal dimension of the faults. In this equation a self-similar exponential relationship exists which is affected by the number factors and the size of spatial quantities. Therefore, based on what was explained, Number-size equation can be explained according to equation 1 (Mehrnia, 2006).
    Equation 1): Log (Ns)= a K Log (s)
    In this equation Ns is the number of the phenomena (in this study the number of the faults), S is the size of the network, k is the coefficient of the line slope or the fractal dimension (Mandelbrot, 1983).
    Findings and discussion The results of the single variable linear regression shows that the relationships between perimeter with major diameter, area with perimeter, depth with area, minor diameter with perimeter and area with major diameter were statistically significant and the correlation coefficients were 0/93, 0.837, 0/668, 0/860, and 0/850. Moreover, the most degree of significant correlation for second and third degree equations was observed between perimeter and large diameter with correlation coefficients of 0/932 and 0/942 and the estimated error of 0/297 in the area has a possibility of error which is smaller than 0/01. The results of multiple regressions also revealed that the most significant correlation of the depth is with area, slope, and minor diameter with a correlation coefficient of 0/834 and estimated error of 7/85. The estimation of the fractal dimension in the investigated areas shows that Shahoo and Paraov areas have the maximum and minimum fractal fault dimensions which are 1/24 and 1/15 respectively.
    Conclusion This study was an attempt to analyze the dolines which exist between Shahoo and Paraov areas using quantitative geomorphology, statistic methods and fractal geometry. The existence of a high correlation between most of the morphometric factors of dolines indicates that that these landforms can be modelled with a high degree of accuracy provided that exact and sufficient data is existent. The employment of fractal geometry and Number-Size equation also showed that by estimating the fractal dimension through the above method the activity of the faults their relative effect on the solution of the soluble stones can be determined. As a matter of fact this method can be utilized as a new index in studying the faults of the karstic areas.
    Keywords: dolines, morphometry, regression analysis, fractal dimension, Number, Size equation
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