جستجوی مقالات مرتبط با کلیدواژه « مدل سازی » در نشریات گروه « زمین شناسی »

The science of system dynamics is a management tool capable of simulating complex systems in water resources. In this research, the model of the dynamic system of multi-purpose consecutive Kardeneh-Sana dams located in Bushehr province has been simulated. The purpose of this modeling is to realize the different needs of the dam (drinking, environment and industrial agriculture) before its construction and also to investigate the effect of construction of the upstream dam on the supply of the downstream dam. The results were studied after calculating the annual and monthly percentage of volume and time supply of the different needs and source of supply, as well as considering two drinking water wells to provide drinking water in the months when the dam is not able to provide drinking water and the maximum The discharge of the current drinking water pipeline of the region was carried out. Six management scenarios were considered for modeling, and finally the sixth scenario was considered as the most optimal scenario. In order to evaluate the model, the simulated values were compared with the observed values of the water volume of Sana Dam. The results indicate that the volume supply of drinking, environment and industrial agriculture needs of Kardeneh Dam is 97.66, 96.59 and 82.76 respectively, and also the volume supply of environment and agriculture needs from Sana Dam is 100, 48 respectively. It is 83.0%, which is within the acceptable range of the Ministry of Energy. Based on this research, it was determined that by modeling based on model evaluation indicators including percentage of volume supply and percentage of time supply of different needs, it is easy to determine the effect of management and exploitation policies on the way of determining and allocating resources. Water observed and made the most optimal decision.

The study area is a part of the Dez River Basin, which is located in the central part of the basin. In this area, due to the climatic conditions, the irregular availability in terms of time and space, the increasing use of water resources and surface water resources, there is a great dependence on the underground water of the region. The main objective of this research is to investigate the factors influencing  the fluctuations of the water level in the Dezful-Andimeshk plain during a statistical period of 20 years. For this purpose, using piezometric well level data and well logs of the study area in WinLog software, maps of the groundwater level and the bottom level of reservoir were prepared using theIDW method. The results of the research showed that the greatest drawdown occurred in north-eastern, south-eastern and western parts of the study area. Asthe amount of precipitation, evaporation and temperature are high in this part, one of the reasons for the decline in these parts can be attributed to the climatic factors of the region. Other factors in the decline of the reservoir level are the main river channel and the high slope of the area. Comparing the changes in the reservoir level with the flow of the Dez River showed that there is a high correlation between the changes in these two parameters with a time interval of one year. Therefore, according to agricultural activities, these limited resources should be harvested, scientifically and fundamentally, the region will be at risk of a serious water crisis in the future.

Studying the bedrock geometry in mining and oil exploration operations to obtain its 2D pattern requires nonlinear reverse computations. Local optimization methods for solving nonlinear inverse problems are based on linearizing the changes of the model similar to a primary model and finding an objective function of minimum error from the parameters of the model; however, these optimization methods are not able to select a suitable primary function that is close enough to the general optimal value. That is to say, every objective function can have several minimum and maximum solutions. The lowest minimum is called the global minimum while the rest of them are named local minima. Therefore, in local inverse methods, the goal is to find the minimum of an objective function, and also an objective function might have a few local minima with different values. In this case, it is not suitable to use gradient-based methods for exploration purposes, unless the primary model is very close to the actual answer, which is outside the control of geological structures or the geometry of the subsurface. Despite the easy execution and high convergence rate of the local methods, there is the possibility of being trapped in local minima because these methods are dependent on the primary model, and also finding more than one optimized point in 2D or 3D simulations; this is why local optimization methods are considered deterministic algorithms. Multi-objective metaheuristic optimization algorithms are capable of searching the feasible region and they also provide a solution independent of the primary model. Searching the feasible region means finding all the feasible solutions for a problem. Each point in this region is representing a solution that can be ranked based on its value. One of the important differences between local optimization and metaheuristic methods is constraining. Constraining metaheuristic global optimization methods are only used for constraining the feasible region based on previous knowledge or estimation relations, which is different from constraining local optimization that is used for stabilizing inverse simulation. The algorithm used in the present work includes non-dominated sorting genetic algorithm (NSGA-II). The NSGA-II is commonly used to solve problems with multiple, typically conflicting objective functions. This algorithm is capable of being developed and also has a high potential for solving unbounded multi-objective problems. In the present study, NSGA-II algorithm was verified and validated using the data produced by an imaginary and complex synthetic model. In the present research work, a hybrid technique of NSGA-II and TOPSIS algorithms was introduced and utilized as a viable search method for nonlinear modeling of the gravity data, and a substitute for the optimization methods. In order for a more precise examination of the performance of this algorithm, the imaginary synthetic data were used both with no noise and with up to 10% Gaussian white noise (GWN). Based on the gravimetric data of the Moghan basin and Atacama Desert, Chile, the results obtained from algorithm indicated good performance of the NSGA-II and NSGAII-TOPSIS algorithms.

Bazman volcano is a member of the volcanic arc of Makran subduction zone. According to previous eruptions, its future likely eruption may be accompanied by lava flow, tephra, and nuee ardente generation. Such indicators as mild erosion, thermal springs, fresh lavas, and continued subduction of the oceanic plate of the Oman sea reveal that Bazman can be reactivated in the future. Its eruption is estimated to be the volcano to sub-Plinian type with VEI of 3-5. For zoning the hazards, ARC GIS, ENVI as well as VORIS softwares were employed by using DEM and satellite pictures. For the construction of the tephra fallout map the convection-dispersion model, and for the construction of nuee ardente spread-out map, the Malin and Sheridan (1982) model were employed. Also, a simulation model was used for the generation of lava spreading map. According to the study, in accordant with prevailing western winds, the ashes will move towards the east. However, lava flows may spread in the north, west, and east direction. Nuee ardentes can spread in almost all directions. Bazman town is not under threat, but some parts of Bam-Iranshahr road may be threatened by ashes and lava flows. Additionally, ashes may reach several remote and small villages but the risk to them is low.

Today, hydrocarbon reservoir modeling methods used for optimal production, predicting reservoir behavior, and production management is very important. In this study, the geology of the Bangestan reservoir was analyzed along with the evaluation of a 3D geological model created by RMS software (structural and petrophysical models) of the Kaboud oil field. The petrographic study of the concerned samples indicates that the main lithology of Bangestan Reservoir in this field consists of limestone, shale, dolomite, and pelagic limestone. Using the merge of geological (paleologs), petrophysical, structural, and RMS output data, the Bangestan Reservoir was subdivided into 8 zones and 4 subzones. The results obtained by the geostatic models prepared by RMS showed that the most proper reservoir zone considering petrophysical features in Bangestan Reservoir is zone No. 4. The stratigraphic correlation of Bangistan Reservoir in Kabud oil field based on the studied wells showed that this zone has the highest thickness in well 1 and the least thickness in well 5. In the prepared cross-section prepared according to NTG, it is observed that the more the layers move towards the east of the field, the better the reservoir quality would be. Volumetric calculations verified that the volume in place of oil in normal conditions is 048/308/72 barrels which correspond to zone No. 4.

The purpose of this research is to show the use of neural networks in predicting the tides of the Caspian Sea. Forecasting the current level of seawater is very useful in the shipping industry and is one of the most important parameters in marine geodesy, oceanography, and geophysics. Sea level has been done in different ways. Among the factors that affect the instantaneous sea level changes, the tidal factor has been investigated in this research. Nowadays, artificial intelligence methods are used to predict tides, these methods can fill information gaps the above items are among the advantages of intelligent methods in analyzing and predicting tides. Accordingly, this study method has been used in the preparation of this research. The nature of this research is quantitative and applied, and a descriptive research method has been used. In this research, one of the types of artificial intelligence has been worked with, which is neural networks. Neural networks have been used to validate the primary data and predict the Caspian Sea tides in this research. According to the findings obtained by Geo Tide software and neural networks, the water level of the Caspian Sea is decreasing because is clear in this research. It was found that the neural networks are more effective for predicting the tides, the water level of the Caspian Sea will reach -28 meters from the open water level in the future.

The studied area is located in N-Sonqor and in the Sanandaj-Sirjan zone. Field relationships and petrographic evidence show that volcanic rocks of the north of Bashirabad comprise of trachydacite to trachyandesite (and altered basaltic trachyandesite) and in the south of this area, it consists of andesite to trachyte. Their texture is mainly porphyry. Geochemical data {total abundance of (Na2O+K2O), enrichment of large lithophile ion elements and rare light earth elements) indicate that these rocks belong to the alkaline series. Spider diagrams show enrichment in LREE and depletion HREE, and parallel patterns in all volcanic samples confirm their common origin. According to modeling magmatic processes, fractional crystallization, assimilation and crustal contamination have played an important role in the magma forming the studied rocks. The discriminating diagrams the tectonic setting the Bashirabad volcanic rocks indicate their subduction-related volcanic arc that was formed in an active continental margin environment with local tensions.

Global warming refers to the recent and ongoing rise in global average temperature near Earth's surface. It is caused mostly by increasing concentrations of greenhouse gases in the atmosphere. Global warming is causing climate patterns to change. However, global warming itself represents only one aspect of climate change. (Nakicenovic et al., 2000; Bytnerowicz et al., 2007).Over the past century, human activities have released large amounts of carbon dioxide and other greenhouse gases into the atmosphere. The majority of greenhouse gases come from burning fossil fuels to produce energy, although deforestation, industrial processes, and some agricultural practices also emit gases into the atmosphere.Greenhouse gases act like a blanket around Earth, trapping energy in the atmosphere and causing it to warm. This phenomenon is called the greenhouse effect and is natural and necessary to support life on Earth. However, the buildup of greenhousegases can change Earth's climate and result in dangerous effects to human health and welfare and to ecosystems. 

In this study, daily precipitation and daily maximum (Tmax) and daily minimum (Tmin) temperatures in the Kahnuj synoptic station, southeastern Iran were predicted for the future (2061-2080) by statistical downscaling outputs of 5 GCM models (EC-EARTH, GFDL-CM3, HadGEM2-ES, MIROC5, MPI-ESM-MR) under RCP 4.5 and RCP 8.5 emission scenarios.

The results of statistical downscaling outputs of 5 GCM models by LARS-WG model under RCP 8.5 emission scenarios (the business-as-usual) in Kahnuj station was modeled from 2061–2080. During this period the mean temperature will increase between 3.2 to 4.6 °C compared to the base period.At The Paris Agreement, the average increase in temperature was set at below 2 °C by the end of the 21st century, which includes the 0.9 °C increase Since the Industrial Revolution, to avoid adverse and unpredictable weather effects (IPCC, 2021; Millar et al., 2017; Rogelj et al., 2018). However, the results of this study show that southeastern Iran is firmly set on the path by increasing the current temperature by several degrees more by 2080. Based on the two modeled scenarios, the change in temperature will have an increasing trend in the coming years and is in good agreement with the recent assessments of future temperature changes in southwest Asia (Babar et al., 2016; Hamidianpour et al., 2016; Pal et al., 2016; Evans, 2009). Therefore, if greenhouse gas emissions continue at their present rate, earth's surface temperature in this region will pass the temperature threshold of 2 °C.

We compare simulated future precipitation based on RCP 4.5 and RCP 8.5 scenarios of global warming with real paleoclimatic changes that happened in the region. In this respect, the maximum and minimum temperatures and precipitation projection in the southeastern Iran is derived from the downscaling of the CMIP5 GCMs (EC-EARTH, GFDL-CM3, HadGEM2-ES, MIROC5, and MPI-ESM-MR) under RCP 4.5 and RCP 8.5 using the Lars WG model. Paleoenvironmental records from southeastern Iran is used to examine whether the predicted changes in precipitation and variability in MLW output based on the two scenarios of global warming are valid.GCMs predicted a considerable decrease in MLW precipitation in Kahnuj station. Similarly, HadGEM2-ES and GFDL-CM3 indicate a weak decline in precipitation compared to other GCMs at the Kahnuj station for RCP 8.5.The current study indicates that in the Jazmurian playa, MLW precipitation will decrease, and temperature will increase in future simulations. Infact, Consistent with several GCM studies and real paleoclimatic changes that happened during past warm/wet periods in the region, results emerging from the Jazmurian playa also show a weakening of the MLW under the RCP 8.5.

Sirjan-Beshneh copper deposit with 0.5 kilometer area is located in Kerman province 80 kilometers west of Sirjan city. The variety of exploration activities including remote-sensing, field traverses, geophysical explorations, surface explorations comprising surface sampling and geochemical analysis of 94 samples, drilling and surveying three trenches with sampling and analysis of six samples as well as drilling of eight deep exploration borehole with the total length of 414.5 meter, have been carried out in the metallic deposit. All faults in the region were mapped based on the remote-sensing and structural geology operations of the region. In the present research, all exploration activities carried out in the Beshneh copper deposit were analyzed through investigating their relationship with the faults in the region. To achieve this goal, various techniques including drawing rose-diagram of faults, processing of resistivity and chargeability data of rectangle survey and smoothed inversion of data for five dipole-dipole profiles, imaging isograde maps for the surface and trench samples as well as 3-D modeling of exploration boreholes assays of the region were employed. The results showed that locations of mineralization related to the fractures and faults present in the region since the trend of most mineralized veins is along the main faults. At the end, in order to complete the explorations of the previous stages to get a better recognition of the deposit, drilling of several new exploration boreholes was proposed based on all performed studies and integrating obtained results as an exploration key.

The Landslide is a natural phenomenon that has a decisive effect on the evolution and erosion of land forms. The importance of this phenomenon is especially longer when it occurs in the areas of human settlement or close to it. In this research, modeling the severity of landslide occurrence in the Mollaghafar Drainage basin using a fuzzy gray model has been studied. The most important factors in the analysis of slope landslide, the direction of gradient, height, land use, distance from the network of waterways, lithology, rainfall, and vegetation covered as the main and effective parameters in landslide zonation of the research basin of the research area are addressed. After preparing the data layer of these factors and their standardization, the weight loss model and the gray relationship analysis were used from the ArcGIS software, and ultimately, using statistical rules, the output lights for each layer of action and related maps were extracted. Also, after covering the layers, the landslide risk zonation map in 5 floors: huge, high, moderate, low and very low. The results obtained from the weight model and the analysis of the fuzzy gray relationship in the study area indicate that the parameters of lands were the highest (0.7028) and the network of waterways with (6892/0) obtained the lowest weight in landslide modeling of the Mollaghafar Drainage basin. Also, the high-risk area of landslides includes an area of nearly 294703 square meters of the total basin.

One of the main objectives of the agricultural sector in arid and semi-arid regions is to improve soil moisture conservation and water productivity. Evaporation from soil surface is non-beneficial losses in irrigation. Mulching is one of the most important agricultural managements in maintaining soil moisture and improving the physical environment of the soil. The use of mulch outside the growing season prevents the salinity of the topsoil. The purpose of this study was to investigate the effect of plant mulch on solute transfer, soil moisture, temperature and salinity outside the growing season, which using two laboratory lysimeters with a length of (1 m), a width of (0.5 m) and a height of (1 m) was investigated. During the 122-day simulation period, moisture and salinity values from 5 depths of soil profiles (50-40-30-20-10 cm) were measured. To compare the means of each treatment with each other, t-test was used in two software models, HYDRUS-2D and AquaCrop. RMSE, MBE, MAE and R2 statistical indexes were used to evaluate each model. The results show that the HYDRUS-2D model has a good ability to model moisture at depths of 10 to 40 cm, but for depths of 0 to 10 and 40 to 50 cm has not performed well in the simulation. Also, the results of AquaCrop model show that this model does not have a good ability to model moisture at depths and HYDRUS-2D model compared to AquaCrop model has the ability to better estimate and more acceptable relative accuracy of moisture at depths of 10 to 40 cm for simulation of solute transportation.This model does not have a good ability to model moisture at depths performed and HYDRUS-2D model compared to AquaCrop model has the ability to better estimate and more acceptable relative accuracy of moisture at depths of 10 to 40 cm for simulation

Hydraulic conductivity and Specific storage are known as the most important hydraulic characteristics of aquifers. Recently, due to software advances, the use of numerical models in the operation of groundwater aquifers has expanded. Modeling is one of the best tools for studying and simulating the state of water resources. One of the advantages of modeling is the simultaneous determination of several parameters such as hydraulic head, flow path and etc. Likewise, via modeling, it is possible to simulate the reaction of the basin against changes such as natural or artificial recharge and the amount of pumping, and by applying appropriate solutions, determine the best performance of the system then use it to manage the basin. In the present study, MODFLOW numerical model and GMS user interface were utilized to simulate and calibrate the model. Accordingly, the hydrodynamic properties of the Shabestar plain aquifer were evaluated regionally. As a result, the RMSE values of hydraulic head for the steady-state and non-steady-state models were 0.59 (m) and 0.95 (m), respectively. The obtained results demonstrated that the more heterogeneous the aquifer, the more diverse the hydrodynamic coefficients will be, and this variation does not follow a specific trend due to the existence of geological formations, the density and the porosity of the formations.

Climate change refers to any significant change in the existing mean climatic conditions within a certain time period (Jana and Majumder, 2010; Giorgi, 2006). Earth's climate change through history has happened (Nakicenovic et al., 2000; Bytnerowicz et al., 2007). 

In this study, daily precipitation and daily maximum (Tmax) and daily minimum (Tmin) temperatures in the Iranshar synoptic station, southeastern Iran were predicted for the future (2061-2080) by statistical downscaling outputs of 5 GCM models (EC-EARTH, GFDL-CM3, HadGEM2-ES, MIROC5, MPI-ESM-MR) under RCP 4.5 and RCP 8.5 emission scenarios. Figure 1: Major climate systems over West Asia (Gurjazkaite et al., 2018; Sharifi et al., 2015; Vaezi et al., 2019). and location of the Iranshahr station (marked as a red box). A) . Dotted lines indicate the approximate current location of the Intertropical Convergence Zone (ITCZ), Mediterranean winter precipitation zone lying between the dashed lines, and the Siberian Anticyclone; IOSM refers to the Indian Ocean Summer Monsoon, and a 30 years average of minimum and maximum monthly mean air temperature (°C) and mean monthly rainfall (mm) as recorded at Iranshahr.

The results of statistical downscaling outputs of 5 GCM models by LARS-WG model under RCP 8.5 emission scenarios (the business-as-usual) in Iranshahr station was modeled from 2061–2080. During this period the mean temperature will increase between 3.2 to 4.6 °C compared to the base period.At The Paris Agreement, the average increase in temperature was set at below 2 °C by the end of the 21st century, which includes the 0.9 °C increase since the industrial revolution, to avoid adverse and unpredictable weather effects (IPCC, 2021; Millar et al., 2017; Rogelj et al., 2018). However, the results of this study show that southeastern Iran is firmly set on the path by increasing the current temperature by several degrees more by 2080. Based on the two modeled scenarios, the change in temperature will have an increasing trend in the coming years and is in good agreement with the recent assessments of future temperature changes in southwest Asia (Babar et al., 2016; Hamidianpour et al., 2016; Pal et al., 2016; Evans, 2009). Therefore, if greenhouse gas emissions continue at their present rate, earth's surface temperature in this region will pass the temperature threshold of 2 °C.One of the mechanisms contributing to the poor monsoon rainfall simulation in CMIP5 and HadGEM3 models may be the Arabian Sea cold sea surface temperature biases that persist until summer and reduce moisture fluxes over the Arabian Sea (Levine et al. 2013; Levine and Turner 2012). In modern times, IOSM induced upwelling of cold water leads to reduce sea surface temperatures in western Arabian Sea in summer that in turn cause reduced evaporation over a cooler Sea and less moisture in the low-level monsoon jet (Levine et al. 2013; Saher et al. 2007). In order to evaluate this hypothesis, paleoclimate changes discussed in the southeastern Iran is useful. The multi-proxy climate record from southeastern Iran reveals that the regional hydrology of southeastern Iran since ca. 14.7 cal kyr BP is primarily governed by IOSM strength, which is linked to the position of the ITCZ in response to the orbital-scale changes in summer insolation (Fleitmann et al., 2007; Gupta et al., 2003; Overpeck et al., 1996).

As the first comprehensive (both future and paleo) climatic change study in the arid region of southeastern Iran on the north most border of IOSM, we compare simulated future precipitation based on different scenarios of global warming with real paleoclimatic changes that happened since ca. 14.7 cal kyr BP in the region. In this respect, the maximum and minimum temperatures and precipitation projection in the southeastern Iran is derived from the downscaling of the CMIP5 GCMs (EC-EARTH, GFDL-CM3, HadGEM2-ES, MIROC5, and MPI-ESM-MR) under RCP 4.5 and RCP 8.5 using the LARS- WG model. Paleoenvironmental records since 14.7 cal kyr BP from southeastern Iran is used to examine whether the predicted changes in precipitation (variability in IOSM and MLW output) based on the two scenarios of global warming are valid.we postulate that results of statistical downscaling outputs of the GCMs by LARS-WG model in Iranshar synoptic station did not have a sensitivity to simulate monsoon precipitation in this complicated region with various factors impacting climate change. Because the results dose not match the paleohydrological changes and Intensify of IOSM during past warm periods. We suggest, in the new generation of climate models, the effect of a consistent increase in seasonal mean precipitation during the summer monsoon under warming scenarios must be considered more for north most monsoonal domain area like southeastern Iran.

Proper modeling of groundwater quality is an important planning and decision-making tool in water resources management. In this study, in order to model the changes in groundwater quality variables in Ardabil plain, data from 60 wells in May 2013 were used. The data were chemically analyzed in the University Jihad Laboratory by West Azerbaijan Province. Descriptive statistics of data and the correlation matrix of the studied parameters were obtained using SPSS software. The qualitative parameters studied in this paper are: EC, TDS and TH. After standardization, the data were entered into MATLAB environment and groundwater parameters were predicted using ANFIS-FCM method. In this method, 70% of the data (42 samples) for the training data set and 30% of the data (18 samples) for the test data set were randomly selected. For ANFIS-FCM model training data set, EC values (R2 = 0.9142, MSE = 0.009391), TDS (R2 = 0.9703, MSE = 0.00515), TH (R2 = 0.9741, 0.00388 = MSE values were also obtained for the ANFIS-FCM model test data set (EC = 0.987, R2 = 0.003383, MSE), TDS (R2 = 0.8381, MSE = 0.00510), TH (= 0.625). R2 (MSE = 0.072) was obtained. Using the results obtained from this model, it was found that the estimated groundwater parameters in the study area had very good accuracy and high correlation with the measured values. As a result, the ANFIS-FCM intelligent method is an effective, efficient and accurate method for estimating the physical and chemical parameters of water.

Assessment and controlling groundwater quality have an important role in planning and developing water resources. Therefore, the use of an efficient method can greatly increase accuracy and reduce costs in this field. In this study, 6 optimization algorithms Consist of Particle swarm optimization (PSO), Genetic algorithm (GA), Imperialist competitive algorithm (ICA), Fireflies algorithm(FA), Cultural algorithm(CA) and covariance matrix adaptation evolution strategy- Evolution strategies (CMA-ES) were used to train and optimize the parameters of the neural-fuzzy inference system model (ANFIS) to model the groundwater quality of Bafgh plain in Yazd province. At first, to select the best combination of input for an estimate of the electrical conductivity (EC), sodium adsorption (SAR) and total hardness (TH), Pearson and Spearman's methods were used to analyze the sensitivity and correlation of other parameters. then qualitative modeling is done with hybrid methods and the performance of the models was measured by correlation coefficients (R2), root mean square error (RMSE), and Nash-Sutcliffe Efficiency (NSE). The results showed that all six combined methods showed a very good performance in modeling groundwater parameters. Also, the ANFIS-FA model was one of the best models in all three modeling parts. So that the value of R2, RMSE and NSE for the test part in TH was, 0.99, 0.41, 0.99, for SAR, 0.98, 1.11,0.95 and for EC 0.99, 305.7 and 0.99. Other methods have also succeeded in modeling and predicting the desired parameters with proper precision. According to the accuracy of the calculations, these methods are suitable alternatives for the prediction of groundwater quality variables.

The Lashotor stone quarry complex as the part of the Sanandaj-Sirjan structural zone is located in the south of the Isfahan city. The Cretaceous calcareous units are the main lithological unit extended in the area. Unscientific extraction is caused to produce many wastes in this stone quarry Complex. Investigation and modelling of structural discontinuities is an essential step in the mining to wastes reduction and economic efficiency improvements. Blocks with different geometric characteristics (number and volume of each block) resulted from the intersections between discontinuities and the faces directions. So, the attitudes of discontinuities (i.e. bedding, joints and stylolites) and their spacing and direction of the cutting step of each face were measured during field survey. The dominant strike of discontinuities are stylolites, which are parallel to the bedding planes based on rose diagrams of the strike direction obtained from field measurements. The average spacing of the stylolites is ~1-1.2 meters. Based on the results of the Modeling Using 3DEC software and the percentage of non-economic blocks was calculated and the volume-cumulative percentage diagrams the current faces were not extracted in correct directions. Therefore, modeling was repeated for different directions of the faces until reaching an optimal direction in order to reduce the waste and increase the efficiency. Finally, the best extraction direction was suggested.

Modeling of geological structures plays an important role in understanding the geometry of the structures and their relationships. In recent years, digital modeling using computers has attracted the attention of engineers as well as researchers in basic sciences. "MATLAB" is one of the softwares that is used with its extensive facilities for data analysis and modeling in various sciences, including structural geology. In this paper, possible models of interference patterns of the three generations of folds in metamorphic rocks of the Golpayegan area were reconstructed using the script written in MATLAB software. The required data include the attitudes of the mean axis and the mean axial planes of three consecutive generations of folds which were obtained during field measurements. Field studies show that the first and second generation folds are almost coaxial, however the third generation folds have a different axial trend. The results of modeling indicate that four classical fold interference patterns may be formed in horizontal (map view) and vertical sections in Golpayegan metamorphic rocks. Modeled fold interference patterns are closely consistent with the natural fold interference patterns observed in the outcrop and regional scales. Using the modeling, it can be determined that the different interference patterns of the folds in the northern Golpayegan metamorphic rocks are related to superposition of the related fold generations.

The subduction systems are located in the continental collision phase. Due to the tectonic regime reversion from the tensile phase to the compressive phase and due to the reactivation of the normal and transverse basement faults, constitute folded belts that are in their tectonic evolution, have experienced multiple fault interactions. Therefore, based on the angle of post-collision shortening axis, relative to each of these old basement faults, their reactivation in the form of thrust or strike-slip components and their effects on the structural pattern of the folds, are justified. In the Zagros foreland, there are several fault lineaments with different trends and mechanisms. They have been reactivated during the collision phase of the Iranian and Arabian sheets. The present study tries to show the effect of the Zagros thrust faults and the Arabian strike slip faults interaction on the development and structural evolution of the Rag Sefid and Tango anticlines using analog modeling.

In order to model the interaction of basement faults in the South Dezful embayment, first, in accordance with the structural realities of the region, the topography of the basement is simulated using the cutting of wooden boards. The arrangement and cutting of the boards are according to the slope of the Rag Sefid thrust fault. First the wooden board is cut at an angle of 47 degrees. Also, considering that about one third of the Rag Sefid anticline has an axial curvature, and due to the slope of approximately 80 degrees at Hendijan fault, which is perpendicular to the Rag Sefid fault, the wooden board is cut into two unequal parts with an 80-degree slope. According to the interpretation of reflective seismic sections and drilled well data, the stratigraphic sequences detectable in the southern Dezful embayment are Aghajari, mobile Gachsaran formation and Middle Resistance Group between Asmari to Gadvan, respectively. Therefore, in order to model these stone units, clay with a thickness of 3 and 2 cm was used for upper and middle resistant units, respectively. Also, in order to simulate the Gachsaran moving formation, a combination of sifted rock powder and 3 cm thick engine oil is used at the beginning of modeling.

The northwest-southeast trend of Rag Sefid anticline located in Zagros foredeep, has been raised due to the Zagros orogenic phase in the Pliocene. After the collision of the plates from the Late Eocene onwards, in addition to folding on the northwest-southeast faults, the north-south basement faults during the Late Cenozoic have been reactivated by the entry of the Zagros deformation front into the study area. The reactivation of these faults has caused changes in sedimentary cover, such as facies change and sediment thickness as well as changes along the axis of surface anticlines. Oblique convergence after collision between Iran and the Arabian Plate has shortened the succession of the Zagros basement; so that the northwest-southeast longitudinal faults that were extensional at the time of the rift formation are now basement thrusts in this belt. The north-south faults, which have trends similar to those of the north-south basement fault in the eastern Arabian Block, are reactivated as a result of this compression.

Due to the general compression trend of N22E in southwestern Iran and the trend of the southern part of the Hendijan fault (N20E), the small-scale fold at the Tango anticline located on the Hendijan fault is due to the parallelism of this transverse fault and the overall compression direction. In contrast to the Rag Sefid anticline, where the trend of the main fault is approximately perpendicular to the direction of total compression (N100), a clear fold with large structural dimensions is created in the Rag Sefid anticline. Our results show that with the entry of the Zagros deformation front into the foreland of the orogenic region in the Pliocene, in addition to the Tango anticline rising at the top of the Hendijan fault, the Rag Sefid anticline has rotated axially by 30 degrees clockwise due to the movement of the right-hand slip in the Hendijan fault. Our modeling shows that the reason for the higher wavelength of the western part of the Rag Sefid anticline is due to the high thickness of the salt layer and also the high value of the ratio number. Due to the location of the western part of the Rag Sefid anticline in a right-sided fault zone and the resulting structural rotation, the widening and increasing wavelength of the anticline is facilitated.

The Asmari Formation (Oligocene – Miocene), as one of the most important oil reservoirs, consists of a thick sequence of carbonate – terrigenous rocks in southwestern Iran. In order to determine the structural geometry of this formation, the stratigraphic forward modelling method has been used in this study. So, 8 oilfields, including Yadanaran, Omid, Jufeyr, Sunsangerd, Khorramshahr, Mansuri, Dorquain and Azadegan have been selected in the Zagros sedimentary basin. Dionisos Flow Software has been used to determine the structural geometry of the sedimentary basin of the Asmari Formation in the studied fields. The studied wells in the oilfields are composed of three to five sedimentary sequences. Identifying each of the sequences that make up the wells per unit of time is the basis of the work. The results of sequence stratigraphic, gamma log and sedimentary environment data are the most important input parameters to the software for modelling. The present study shows that the geometric structure of the sedimentary basin of Asmari Formation in the studied fields has been controlled by parameters such as bathymetry, tectonic processes (rising and falling of the basin floor), global changes in sea level and accommodation space. The geometric structure of the sedimentary basin of Asmari Formation during the Oligocene – Miocene in the studied area was predicted as a progressive geometric structure with a gradual and cumulative nature towards the basin.