IRANIAN JOURNAL OF GEOPHYSICS
Year:2018 | Volume:12 | Issue:1 |Papers Count:11

Ever increasing attention is being paid to the use of Numerical Weather Prediction (NWP) models in the convection-permitting mode for providing high-resolution forecasts. In such applications, the use of NWP models and comparison among the simulations of models help us to understand the problems associated with these scales and to unravel the systematic errors of the models. In this study, two weeks of “ model simulation experiments” have been conducted with the HARMONIEAROME and the WRF-ARW meso-scale NWP models at 2. 5 km horizontal resolution, in order to partly resolve convective phenomena on the same domain over the mountainous areas of the west of Iran for the period of 1– 15 December 2013. All experiments have been conducted by using the ECMWF ERA-Interim reanalyses for the lateral boundary conditions, and for this reason, they are called “ model simulation experiments” . The HARMONIE Verification System has been used for the validation, and operational radiosonde and SYNOP observations from the ECMWF have been used for the verification. The precipitation observations from some climatological stations of Iran have also been used. The model simulations described in this study were run up to +72 h. The motivation for this long simulation time is to investigate any possible systematic model problems that could hide possible impact of data assimilation in the planned data assimilation forecast experiments. Generally, the WRF and HARMONIE have a comparable performance, both of which have similar results for some variables at all forecast lead times. For 24-hour accumulated precipitation forecasts, the correlation coefficient, the bias and the root mean square error (RMSE) were used to compare the performance of both models over the same area. For the correlation coefficient and the RMSE, the WRF has slightly better verification scores at all lead times. The results for the temperature at 2 m, wind speed and direction at 10 m, and specific humidity (mixing ratio) at 2 m are verified by using different verification scores. A similar behavior is found for both models in the error standard deviation (STDV) verification score; although some minor differences are observed at some lead times and for some variables. A more significant difference is related to the bias of specific humidity at 2 m for the WRF and HARMONIE as over-estimation of moisture for the HARMONIE and its under-estimation for the WRF. Considering the upper air profiles of the bias and the STDV of the error, both similarities and differences were shown for the vertical structures of various quantities as obtained by the two model simulations. While the strongest similarity was seen in the bias and the STDV of the temperature error profiles, the relative humidity at 850 hPa exhibited the largest differences in both measures of error. A dry bias, which increased with the forecast time, was noticed for the WRF at low levels (850 hPa) as verified against the radiosonde data as well as the SYNOP data at 2 m level.

The simulation and prediction of pollutants dispersion entering into the atmosphere (such as material releases from the chimneys of industries and power plants) are important in different views, long-term environmental monitoring and dose calculations as well as issuing an appropriate warning in the event of an accident. To this end, a system of coupled meteorology-dispersion model can be used. In fact, a numerical weather prediction model is coupled to a dispersion model. In the present work, the weather research and forecasting (WRF) model is used to provide the meteorological data for the HYSPLIT (HYbrid Single Particle Lagrangian Integrated Trajectory) dispersion model. Sensitivity and validation of the WRF model are conducted by utilizing different combinations of physical parameterization schemes (microphysics, longwave radiation, shortwave radiation, surface layer, land surface, boundary layer and cumulus convection) for the prediction of meteorological parameters in an area containing the Bushehr power plant. For this purpose, eight different configurations are used. Then, for several dates, sensitivity, and validation of the model results is carried out to find the proper configuration of the model. Assessment of the predictions of the WRF model is carried out by computing the statistical parameters including correlation coefficient (CC), root mean square error (RMSE), and comparing with the collected observational data (on-site the meteorological tower and Sodar system in Bushehr power plant and synoptic meteorological stations nearby). After determining the proper configuration of the WRF model, dispersion simulations and annual effective dose for the adult age group are carried out by WRF-HYSPLIT coupled model under normal conditions for Bushehr power plant. The predicted annual effective dose for the adult age group by the coupled model for the years 2014, 2015 and 2016, provided 5. 8×10-8 (Sv), 6. 7×10-8 (Sv) and 1. 1×10-7 (Sv) respectively, in return value 7. 7×10-8 (Sv) for Bushehr power plant final safety analysis report (FSAR report). Comparing these results show that the simulation and prediction of dose by the coupled WRF-HYSPLIT model are in good agreement with observations and indicates the validity of the simulations. The ratio of predicted annual effective dose to dose limit for normal operation is obtained less than 0. 2 percent (<0. 2 %), which shows that public annual exposure dose for normal operation of Bushehr power plant is negligible compared to the legal limit. The results of the present work showed that the coupled WRF-HYSPLIT model can be used as a promising tool for the prediction of dispersion and dose calculations for Bushehr power plant under normal operation. In addition, the results of this coupled model can provide the required information for emergency management to forecast the movement and direction of radioactive plume and exposure dose calculations.

Retaining walls are designed to withstand lateral earth and water pressures, the effects of surcharge loads, and the self-weight of the wall and, in special cases, earthquake loads in accordance with the general principles specified in this section. Retaining walls are constructed for a certain service life based on consideration of the potential long-term effects of material deterioration on each of the material components comprising the wall. Permanent retaining walls are designed for a minimum service life of 50 years. Temporary retaining walls should be designed for a minimum service life of 5 years. Gravity retaining walls rely on their self-weight to resist lateral earth pressures. Analysis of the seismic behavior of gravity retaining walls during earthquake loading is a quite complex task. Seismic wall movements can occur as sliding or rotational displacements. In some cases, only one of these displacements can be dominant and for some of them, both sliding and rotation can occur. Foundation soil deformability, backfill, wall stiffness, and input record motion as the main variables used in the analysis of walls are subjected to a strong earthquake. The analysis of the seismic stability of walls retaining back ll soil is based on the following assumptions: (1) the wall– soil system is long enough for ignoring the end effects (plane strain condition); (2) the soil is homogeneous, dry, and cohesion-less; (3) the retaining wall is subjected only to horizontal displacements; (4) the seismic action is uniform horizontally distributed in the whole mass of the system; and (5) the failure wedge is a plain. Furthermore, the upper bound limit analysis is based on the assumption that soil will be deformed according to the associated ow rule and the convexity of the soil yield condition. In the following analysis, we assumed that these conditions are met. For many decades, the seismic analysis of retaining walls has been based on the simple extension of Coulomb’ s limit equilibrium analysis, which has become widely known as the Mononobe-Okabe method. The method modified and simplified by Seed and Whitman has prevailed mainly because of its simplicity and the familiarity of engineers with the Coulomb method. Designing walls for stability against earthquake risks in seismic zones is done through the analysis of the seismic behavior of the soil-structure system. The methods established using newmark sliding block procedure are based on forces (pseudo-static and pseudo-dynamic) and allowable displacements. These methods are frequently used in the seismic design. Dynamic analysis of retaining walls can also be done by finite-element methods. ABAQUS is among the computer programs that suite for finite-element analysis. In this study, a series of finite elements were carried out in ABAQUS in order to find out typical wall movements including rotation and lateral top and base displacements. This research presents that many variables such as maximum acceleration, properties of foundation and backfill soils, and characteristics of the wall affect the seismic behavior. Design charts were derived from the numerical analyses to predict both lateral displacements at base and top. The proposed charts consider the most relevant factors in the system response. The result obtained can be used to develop an optimum design procedure for gravity retaining walls.

Meteorological phenomena are complex systems with different parts that are in contact with each other as well as their surroundings. The purpose of this research is to demonstrate the efficiency of neural networks in predicting meteorological variables. For this purpose, the prediction of horizontal visibility that is widely used in meteorology and aviation especially at airports has been selected for analysis. The data of this study are a compilation of Metar and Synop reports of Bandar Abbas synoptic station in the period from 1 to 30 March 2014. To implement this network, at first, the whole data were randomly divided into three categories with proportions of 75, 15 and 15 percent for learning, testing and validation of network and saved in other files. The seven variables for inputs (temperature, dew point temperature, atmospheric pressure, sky cloud coverage, wind speed and wind direction) of the network with 28 various composites tested with a feedforward network and their correlation with the output and amount of root mean square (RMS) error of network have been studied. The results show, the compositions that containing the present air phenomena are most correlated with the horizontal visibility. Besides, the dew point temperature, atmospheric pressure and the amount of cloud cover are variables that alone do not have an affect on the horizontal visibility. In this research, a network which works with training neural networks by resilient backpropagation algorithm is used. This is a learning heuristic for supervised learning in feedforward artificial neural networks, which only the sign of the partial derivative is used to determine the direction of the bias and weight updates and the magnitude of their derivative has no effect on their updates. Of course, the size of their change (increment and reduce rates) is determined by a separate update value. This network with eight neurons and sigmoid transfer function in the hidden layer and the linear transfer function in the output layer is used for predicting of horizontal visibility. This network was performed with two standardization data sets between intervals 0. 0-1. 0 and 0. 1-0. 9; also, different learning rates, incremental and reduced rates for weights and biases. The results show that the normalization is not appropriate between zero and one. The appropriate amounts of learning rate, incremental and reduced rates for this network are 0. 0001, 1. 2 and 0. 35, respectively. The values of the coefficient of determination for training, test and validation data for a running network with all variables were 0. 9972, 0. 9866 and 0. 9839, respectively. These values show that nearly 99 percent of the measured horizontal visibility is affected by these independent variables and the rest of its variations are dependent on other factors.

Permeability is a property of the reservoir rock, which deals with the flow of fluid from the reservoir and is an important factor in oil and gas production. This parameter is measured via coring and core laboratory analysis, which is an expensive and time-consuming process and also is not a feasible approach for every oil and gas field. Nowadays, the permeability can also be calculated using the data of petrophysical logs by means of statistical and intelligent techniques. The present study uses four wells drilled in Kangan and Dalan formations within South Pars gas field to predict permeability using fuzzy logic. Out of totally eight features extracted from each well, four more effective features were selected using correlation-based feature selection tools. Then, regression, multilayer perceptron, RBF neural network, Local Linear Model Trees (LOLIMOT), type-1 and type-2 fuzzy systems were utilized for permeability prediction. The results indicated that due to the uncertainty in the petrophysical and permeability parameters, type-2 Fuzzy systems cover better the uncertainties. The aforementioned method predicts the best number of rules using the GSA-GA (Gravitational Search Algorithm-Genetic algorithm) combined algorithms. Fuzzy membership functions were also improved using the K-means clustering algorithms. These improvements led to increased accuracy of the predicted permeability with a coefficient of 0. 9768, and a decrease in the root mean square error to 0. 1602.

The European Space Agency (ESA’ s) Soil Moisture and Ocean Salinity (SMOS) satellite mission was launched in November 2009. SMOS carries the first L-band (1. 4 GHz) 2-D synthetic aperture microwave radiometer that produces multi-angular dual polarized (or fully polarized) brightness temperature. The objective of SMOS mission is to provide global surface soil moisture maps over the land surfaces with an accuracy of 0. 04 m3m 3. The SMOS soil moisture retrieval algorithm was developed, which processes Level 1C products (multi-angular brightness temperatures) to Level 2 SM products (soil moisture maps). This algorithm is based on the comparison between the brightness temperatures from SMOS and the simulated brightness temperatures data (simulated TB) using L-MEB model. Thus, the evaluation of SMOS brightness temperatures is a necessary step before using of Level 2 Soil Moisture products. Therefore, the objective of this research is to evaluate the horizontal and vertical full polarized brightness temperatures data (TBh, TBv) from the SMOS MIR_SCLF1C products at the five meteorological stations in the west and southwest of Iran. Evaluation of SMOS brightness temperature data (SMOS TB) was done through a comparison between the SMOS TB and simulated TB from the L-MEB model. The SMOS MIR_SCLF1C (Level 1C Full Polarization Land Science measurements) products, which were provided through the ESA, contains the multi-angular brightness temperatures at the top of the atmosphere in the antenna polarization reference frame. In this study, the MIR_SCLF1C products, version 505 for the period 2012-2013 were evaluated. The ESA’ s SMOS Matlab codes on Linux was used to reading and deriving TB, Incidence angles, Geometric and Faraday rotations and other required data from MIR_SCLF1C products. The L-MEB (L-band Microwave Emission of the Biosphere) model is the radiative transfer model, which has been specifically developed to simulate the L-band microwave emission (brightness temperature) over land surfaces. In this research, the simulation of TB (TBh, TBv) at the five meteorological stations was carried out using L-MEB model (MATLAB function) and ground-based measurements. The model was simulated TB at the Earth’ s surface reference. Therefore, SMOS TB data was projected from the antenna reference frame to the Earth’ s surface reference frame using an algorithm provided by the CESBIO (Centre d’ Etudes Spatiales de la BIOsphé re) team. Four statistical metrics and Taylor diagram were used for the evaluation of results; the Root Mean Squared Difference (RMSD), the centered Root Mean Square Difference (cRMSD), the Mean Bias Error or bias and the correlation coefficient (R). The Taylor diagrams are used to represent three statistical metrics (R, cRMSD and standard deviation) on two dimensional plots to graphically describing how closely SMOS TB matches simulated TB. Based on the research algorithm, the Evaluation model for the SMOS brightness temperatures data (TBh, TBv) was obtained. The Evaluation model was run for five metrological stations and simulated TB data from L-MEB model and SMOS BT from the MIR_SCLF1C product was saved as the output of the model to evaluation. The results of the comparison between the SMOS TBh, TBv data and simulated TBh, TBv show that SMOS TB have an underestimation at Ahvaz, Sararod, Sarableh stations, whereas an overestimation of the SMOS BT was detected at Darab, Ekbatan stations. According to RMSD results, the SMOS TBh data at Ahvaz, Sarableh stations and the SMOS TBv data at Ahvaz, Darab, Sarableh stations have the highest accuracy. The Taylor diagrams shows the strong correlation (RTBh = 0. 8-0. 9 and RTBv =0. 81-0. 93) between the SMOS TB and simulated TB data at all stations. Besides, the lowest value of the cRMSD of the SMOS TB data was obtained at Ahvaz (TBh =5. 34, TBv = 5. 67 K) and Darab stations (TBh =8. 54, TBv = 5. 9 K). In addition, these diagrams indicate that the standard deviation of SMOS TBh data at Sarableh, Ahvaz, Sararod stations and SMOS TBv data at Sarableh, Darab, Ahvaz stations are closer to the simulated TB data than other stations. Overall, the findings of this paper give valuable information about the uncertainties and errors of SMOS brightness temperatures data (MIR_SCLF1C) in the study area. Therefore, this research could be as a reference for using the SMOS soil moisture products (Level 2 Soil Moisture) in hydrology and meteorology studies in Iran.

Natural gas is accumulated in the reservoirs as either separate gas reservoir or the gas cap in an oil reservoir. Besides, gas is also injected into a hydrocarbon reservoir for IOR/EOR or gas storage purposes. Due to the reservoir heterogeneity or fault pattern in reservoir, gas could move to unplanned parts of the reservoir or could even be leaked, which in turn, deviates from the purpose of the gas injection. To overcome this problem and to monitor the fate of injected gas, 4D seismic data has recently been employed by oil and gas companies. 4D seismic, that is indeed, the repeated 3D seismic through the time has been recently revealed to be a successful tool for this purpose. However, there has been reported some challenges about the quantitative estimation of injected gas using 4D seismic data. The source of this challenge is mainly due to the non-linear response of elastic properties of saturated rock versus gas saturation. Once the gas is injected into core plug in the laboratory, the compressional velocity is significantly decreased for a few percents of gas saturation. Nonetheless, for higher gas saturation variation, not a considerable change is observed in compressional velocity. Because of this extremely non-linear behaviour, some researchers have concluded that the quantification of gas response is not possible using seismic data. In this research, it is tried to understand the reservoir scale gas distribution that is found to be different from the laboratory scale. Gas is migrated towards the upper part of the reservoir due to the gravity effect. It is quickly reached at a fixed gas saturation that is around maximum gas saturation (1-Swir). Continuation of gas injection increases gas thickness from top to base of reservoir, while gas saturation is practically fixed. Therefore, unlike the laboratory scale, the only variable on the reservoir scale would be the gas thickness, and not gas saturation. This is the key observation that would assist to understand proper 3D and 4D seismic response to injected gas. Two main 4D seismic attributes are chosen in this paper to understand those responses. The response of time shift and amplitude change were derived analytically and investigated numerically. The variety of reservoir models with different thickness and heterogeneities were made to analyze the seismic response. It can be concluded that for the medium to high-quality reservoirs, seismic response to the injected gas is simply linear; therefore, 4D seismic is still a powerful tool to quantitatively estimate the volume, distribution and migration path of the injected gas. It is proposed to continue this research to understand the seismic response on low quality (permeability and porosity) reservoirs.

The attenuation quality parameter (Q) is a phenomenological quantity depending on the observations and on the underlying theoretical models. Attenuation of seismic waves is expressed with inverse quality factor (Q-1) and helps understand the physical laws governing the propagation of seismic waves in the lithosphere. Attenuation is often found to be anisotropic (directionally dependent) due to a variety of factors such as the intrinsic anisotropy of the material, the presence of aligned fluid-fractures (Batzle et al., 2005), or interbedding of thin layers with different properties (Zhu et al., 2007). The magnitude of attenuation anisotropy can be much higher than that of velocity anisotropy, and the symmetry of the attenuation coefficient can be different than that of the velocity function (Liu et al., 2007). The observed seismic-wave amplitudes usually decay exponentially with increasing travel distance after the correction for geometrical spreading, and decay rates are proportional to Q 1 that characterizes the spatial attenuation for SH-wave. Qeshm Island, the largest island of the Persian Gulf, is important because of various aspects such as population, economics and some oil and gas reservoirs. Since the most destructive part of the elastic waves, is the horizontal component of the shear waves, estimation of attenuation of the horizontal component will provide us with very useful information. Horizontal components of shear waves are also affected by the structure of the earth. In this study, 661 well-located aftershocks are selected and 18342 seismograms are used to the calculation. by rotation of the components, the horizontal part of the shear waves are separated and horizontal shear wave quality factor was determined by using the Coda normalization method in five frequency bands 1-2, 2-4, 4-8, 8-16, 16-32 (Hz) with a central frequency of 1. 5, 3, 6, 12, 24 Hz, in the lapse time of 30 seconds. Based on the calculations, the frequency dependence relation for shear waves: QSH = (11 ± 1. 2)f(1. 2± 0. 105). The relationship between the frequency dependence for horizontal shear waves shows the attenuation in the Qeshm Island is very high and consequently the region is seismically active. Besides, a small amount of the quality factor for horizontal shear waves associated with the low velocity of shear wave propagation in the crust that may relate to the presence of gas and oil fluids and some salt dome. In the azimuthal study, the attenuation of horizontal shear waves are calculated in two directions: northeast-southwest and northwest-southeast. For low frequencies, the attenuation in the northeast-southwest direction is close to northwest-southeast direction, which seems the horizontal component of the shear waves are not affected by tectonic structures, so it seems mostly to be dependent on the material of the earth, whereas for high frequencies greater than 6 Hz, there are significant differences between two azimuthal attenuation, that can be due to some small-scale heterogeneity of the region.

The gravity field effects of topography-isostasic masses are one of the most source variations in gravity observations. The removal of the gravitational effect of topography on gravity anomaly is the important task in geodesy and geophysics. In geodesy, the topographical effect is used to make a harmonic gravity space in solving the GBVP. In geophysics, the topographic effect is applied to better detection of anomalous subsurface densities. In addition, in the removing of the topographic effect, the reduced signal is so smooth that it provides the perdition or approximation with higher accuracy. The removal effect of topography mass will produce a large effect on potential and gravity so called indirect effect. This implies that the effect of topography is compensated by an isostasy mechanism. Therefore, far two well-known ideal models, i. e., Pratt and Airy, were frequently used in local and regional gravity field modeling. Naturally, the effect of isostatic mass is related to the medium wavelength corresponded to the regional scale such as 100 km. The present study aimed to evaluate the various topographic/isostatic models success in smoothing gravity anomaly signal. In addition, the Veining Meinesz-Moritz (VMM) model and Bouguer anomalies are compared with Pratt and Airy. It is tried to find an answer for the three following questions: 1-Are the isostatic anomalies smoother than Bouguer ones? 2-What is the wavelength of the gravitational effect of isostatic masses? 3-Does the VMM isostatic model succeed in smoothing gravity anomalies with respect to ideal models of Pratt and Airy? To answer these questions, the numerical assessment was done on about 27000 points observed gravity in Colorado, USA. The topographic and isostatic effects are evaluated by the numerical integration using the 90 meters SRTM DEM. The VMM isostatic effect is computed with respect to Moho, computed by gravity inversion using Sjoberg’ s method. The global gravity model, EGM08 and the harmonic topography model, DTM2006 are used to the computation of the Moho depth in the test area. 2D Least square spectral analysis (LSSA) method was used for a detailed examination of the calculated signal anomalies smoothness. For better detection of high frequencies, first, wavelengths greater than different radius 10, 100 and 200 km are filtered out from the data using a Gaussian filter in the spatial domain. The LSSA spectrum of reduced signals indicates that Pratt and Airy models compared to the Bouguer have more oscillations in high frequencies. Besides, the spectral content of Bouguer and VMM signals are very similar in high frequency. The results show that the isostasy has no effect on the local smoothness of the Bouguer gravity anomaly signal. Moreover, the numerical results indicate that the gravitational effect of all isostatic models does not affect the wavelength below 50 km