مجله ژئوفیزیک ایران
سال هفتم شماره 4 (پیاپی 19، زمستان 1392)

The reliability of seismic mapping is strongly dependent upon the quality of the records. Seismic records are usually affected by various types of noise such as ground rolls, multiples, random noise, reflection and reflected refraction from near surface structures, and so on. Random noise resulted from random oscillation during acquiring data is one of the most important and harmful noises that exist in seismic data over entire time and frequency. Random noise attenuation is an important step in seismic data processing affecting the data interpretation. Many efforts have been made to remove this type of noise from the seismic data. The predictive filter is an ordinary method commonly used for random noise attenuation from seismic data. This filter can be used in various domains, such as the f-x domain (Haris and White, 1997) and the discrete cosine domain (Lu and Liu, 2007). Jones and Levy (1987) removed events which were not coherent trace-to-trace events by means of the Karhunen-Loeve transform. Karsli et al. (1996) applied complex trace analysis to seismic data to suppress random noise and improve the temporal resolution of the data.Terickett (2008) attenuated the random noise from the seismic data by Cadzow filtering of a constant frequency slice in an f-xy domain. Bekara and Baan (2008) attacked the random noise problem using the empirical mode decomposition technique. In this study, we used non-local means filtering (Buades et al., 2005) developed for image denoising for random noise suppression in seismic data. In this method, a seismic record can be considered as an image. The non-local means method is based on the assumption that the image content is likely to repeat itself within some neighborhood. The neighborhood of a pixel is generally chosen to be a square with a dimension size of three to nine centered upon the pixel of interest. However, the size and shape of the neighborhood can vary. In this method, for each pixel i with a neighborhood N i, the pixels j with the neighborhoods N j similar to that of the interest pixel are found. The denoised value of a pixel i is determined by a weighted average of all the pixels in the image. The weight of each pixel j can be calculated by the similarity between the two pixels i and j computed using the Gaussian weighted Euclidean distance between the neighborhood around the pixel i and the neighborhood around the pixel j. To investigate the efficiency of the proposed method, we tested the non-local means algorithm on both synthetic and real seismic data. We also compared the obtained results by that of the traditional mean and median algorithm for seismic data denoising. To investigate further, we applied the three denoising methods to synthetic seismic data with different amounts of signal-to-noise ratios. After analyzing all of the results, the non-local means algorithm proved to be a better algorithm for seismic data denoising and had the best performance among the three methods.

Located in the Persian Gulf, the gas field studied in this research is one of the largest gas fields in the world. Its gas-in-place is estimated to be about 14.2 trillion cubic meters while amount of its condensate-in-place might be around 18 billion barrels. This gas field has also an oil layer containing about 6 billion barrels of oil-in-place. In this study, Kangan and Dalan formations of this field were considered. Kangan formation has three main facies: clean carbonate facies, basic clay and shale facies, and evaporate carbonate facies. Dalan formation contains four facies: shore restricted carbonates, shore organic carbonates, carbonates of the open sea, in-shore carbonate-clastic. These two formations have gas & condensate fluids. Since this field is a heterogeneous carbonate system, lithofacies characterization is the best solution for overcoming the problem of heterogeneity in determining the petrophysical properties of the reservoir rock, reservoir modeling and identifying producing zones. However, coring as the most robust method of lithofacies identification is very expensive, time consuming and limited to a few number of wells. Therefore, this study is focused on determining the lithofacies of the study formations from available well logs. For this purpose, multi-resolution graph-based clustering (MRGC) technique which is a dot-pattern recognition method based on non-parametric K-nearest neighbor and graph data representation was applied to sonic, density, neutron porosity and gamma ray logs to define electrofacies similar to core-derived facies determined as eight distinct facies.The cluster of the MRGC method is defined from a model with a specific character associated with the group of lithofacies. Then, Kernel representative index was used to calculate the optimal number of clusters. Small facies groups were formed based on utilizing the neighboring index to determine a K-nearest neighbor attraction for each point. At last, final clusters were constructed by combining the small clusters which lead to identifying eight facies of this gas field from well logs of high accuracy. When electrofacies of one of the wells is built basd on its lithofacies, its cross-plots will be plotted and the certainty of electrofacies with respect to lithofacies will be checked. If the model is acceptable, it is applied to the data from two other wells and their electrofacies will be obtained. For testing facies, the cross-plots of these two wells were also drawn and painted based on facies. If there are similar petrophysical properties for each facies, the model created in the wells without cores is confirmed. MRGC is a fast method that allows the geologist or petrophysist to analyze and test different combinations of data in a short amount of time. It is also not limited by the dimensions of the data and number of the clusters. The method used in this study has obviated the need for extensive coring in this field which caused saving large amounts of money and time; and it can help to optimize the determination of new well locations and optimum pay zones.

Blocking is one of the most important weather systems in mid-latitudes that have significant effects on atmospheric air flow and regional weather conditions. In this study, climatology of Asian and European blockings was investigated for the period of 1950– 2010. The data used in this study were 500-hPa geopotential heights from the National Centers for Environmental Prediction/ National Center for Atmospheric Research (NCEP/NCAR) reanalysis dataset with 2.5°×2.5° resolution. The blocking events were detected using two indices; the first one, a one-dimensional index, was the new version of the Tibaldi and Molteni (1990) index presented by Barriopedro et al. (2005) and the second one, a two-dimensional index, was presented by Diao et al. (2006). Then, applying these indices, the characteristics of detected blockings such as frequency, duration, intensity, position of center and extension were obtained and compared with each other. In the period of this study, 1054 and 729 blocking events were identified using the first and second indices, respectively. The spatial and temporal distribution analysis showed that blocking was most prevalent in the longitude band between 30 °W and 47.5 °E and most of the maximum intensity occurrence was in the east of Atlantic sector between 3 °W and 5 °E. It was found that blocking events were more frequent in the Atlantic-European sector than in the other sectors in winter, spring and autumn, but more persistent in the Atlantic- European sector than in the Asian sector for all seasons. Additionally, the maximum amplitude of intensity was 3.0 for the first index and 150 gpm for the second index. A comparison of the blocking events in the Asian sector with the Atlantic-European sector indicated that the intensity of winter events in the European sector was higher than that of the other seasons. This may be due to synoptic-scale eddies and planetary waves which are more active and stronger in winter compared to the other seasons. The trend analysis displayed that the number of blocking events in the period of this study was decreasing slightly in the entire region, including Iran. The number of events was significantly more in the west and northwest of Iran than in the central and eastern parts. Also, the results of two indices showed that the latitude band of blocking occurrence and its maximum frequency was similar in the different seasons for the first index, whereas this band changed for the second index. The maximum frequency of blocking event was seen in latitude 55 N for winter, spring and autumn and in latitude 62.5 N for summer. Thus, it indicated that blockings occurred in a higher-latitude band in summer than the other seasons. In addition, it was found that there was a good consistency between the longitude band of blocking event, including the Asian and European sectors, and its frequency in summer and autumn using the two indices. In the other seasons, the longitude band of the Asian and European blocking events, especially in the eastern part of the Asian sector, was different for the two indices. The other noticeable point was that the activity centers of blocking events in winter, spring, and autumn obtained by the second index were located more westward of the Atlantic-European sector and more eastward of the Asian sector than those obtained by the first index. The main conclusion was that since the Diao et al. (2006) index is a two-dimensional one, it is able to identify better and more precisely the blocking events and their characteristics as compared to the Barriopedro et al. (2005) index.

The analytic signal and its derivatives have been used in magnetic data interpretation such as estimation of the edge, depth and slope of the magnetic bodies for several years. Nabighian (1972, 1974, 1984) extensively described the principles of the analytic signal method for the location of the 2D sources. The analytic signal shape can be used to determine the depth of the magnetic sources. Atchuta et al (1981) used the anomaly width at half the amplitude to derive the depths. W. R. Roest and his collaborators used the 3D analytic signal amplitude to estimate the magnetic source depth (Roestetal.,1992) and to identify remanent magnetization (Roest and Pilkington, 1993). However, their applications and many conclusions are based on a 2D vertical- magnetic-contact model assumption. Further implementation of this technique was made by Hsu et al. (1996) who developed an enhanced analytic signal applied to a higher order vertical derivative of potential - field anomalies and thus providing a better visualization of the outlines of magnetic bodies. This enhanced analytic signal was adapted as an automatic interpretation tool (Debeglia and Corpel, 1997; Hsu et al., 1998). Hsu et al, 1998 used the enhanced analytic signal to estimate the depth of step models and the thin dike. They also proposed an algorithm for the type of these models afterwards. Bastani and Pedersen (2001) have developed an algorithm for the automatic estimation of the source parameters, including the dip and susceptibility contrast, from the analytic signal in the case of magnetic profiles. Salem and Ravat (2003) proposed a combined method (ANEUL) based on the Euler equation and the analytic signal. Li (2006) discussed a 3D analytic signal and proposed that, generally, in three dimensions, the analytic signal is dependent on everything that the total magnetic intensity (TMI) itself may depend on i.e. the direction of the inducing field, the direction of the remanent magnetization, the dipping angle of the source body, and the depths to the top and bottom of the source body. In this study, the equations of analytic signal and its derivatives were developed based on their effective parameters for contact, thin dikes and horizontal cylinder models. Afterwards, using the maximum value of the ratio of analytic signal and its derivatives, an equation for depth and structural index estimation was obtained which was exactly similar to the equations in the AN–EUL method. Then, assuming a priori knowledge about the shape of magnetic body, other equations were obtained for the depth detection of contact, thin dike and horizontal cylinder. To evaluate the precision of these methods, we have used a dike model with constant width located at deferent depths. In this modeling study, we proved that the estimated depth from the AN-EUL method was dependent on the depth-to-width ratio. Using the AN-EUL method, it is not possible to detect the depth of bodies with their depth-to-width ratio less than two. To solve this problem, we used proposed equations for different models. This method was used for the depth detection of the Aliabad iron deposit, and its results were compared to the results from drilling exploration data. The correlation coefficient between the exact depth and the estimated depth was equal to 85 percent.

Vast areas of the Northern Hemisphere are influenced by the North Atlantic Oscillation (NAO) and the Madden-Julian Oscillation (MJO). Revealing the interaction between them can help us predict the phase and amplitude of each one based on the conditions of the other. Statistical-dynamical study on critical events of MJO and NAO during the Northern Hemisphere winter in a 37-year period (1974-2011), reveals a considerable connection between NAO and MJO. In a statistical method, the computed mean value of NAO index for different phases of MJO associated with 5 to 25-day lags, showed a causal relation between the two phenomena. Phase 7 (3) of MJO was observed 20 to 25 days after the positive (negative) phase of NAO. On the other hand, 5 to 15 days after phase 3 (7) of MJO, positive (negative) phase of NAO occured. Lagged composite maps of 200-hPa zonal wind anomaly and the outgoing long-wave radiation (OLR) anomaly were computed for different phases of critical NAO in order to analyze the dynamical impact of NAO on MJO. Within 5 to 25 days after the positive NAO, maximum 250-hPa westerly anomalies in the Africa-Asia jet region propagate eastward from Africa to central Indian Ocean. On the other hand, OLR anomaly patterns propagate eastward in the same period and same region after the positive NAO that might be induced by the propagation features of 250-hPa zonal wind anomalies. On the 25-day lag relative to the critical positive NAO, both 250-hPa westerly anomalies over the central and eastern Indian Ocean and the development of positive OLR anomalies in the same region were consistent with the conditions of phase 7 of MJO. However, on the 5 to 25- day lags relative to the critical negative NAO, 250-hPa zonal wind anomalies showed the attenuation of the westerly Africa-Asia jet leading to the favorable conditions for evolution of the easterly anomalies over the Indian Ocean. On the other hand, the OLR anomaly patterns displayed either little or no westward propagation. On the 25-day lag relative to the critical negative NAO, the development of both 250-hPa easterly anomalies and negative OLR anomalies over the central Indian Ocean corresponded to the conditions of phase 3 of MJO. Lagged composites of 500-hPa geopotential height anomaly for different phases of MJO were also computed in order to analyze the dynamical impact of MJO on NAO. On the 5 to 15-day lags relative to phase 3 of MJO, a Rossby wave train was observed over the Pacific Ocean extending to the North America and Atlantic region. The waves were oriented in the South West – North East direction. On the 10-day and 15-day lags, the waves started to gradually break anticyclonically over the North America and North Atlantic regions. On the 15-day lag, a dipolar pattern formed in the Atlantic region associated with a negative anomaly center of 500-hPa geopotential height in the northern part of the North Atlantic and a positive anomaly center in the central part of the North Atlantic, leading to the formation of the positive NAO phase. On lag days after phase 7 of critical MJO, a similar wave train was also extended from the Pacific and North America to the Atlantic region; however, the orientation of the waves was South East-North to West at this time. On the 5 and 10-day lags, a cyclonic wave breaking was observed over the North America and North Atlantic regions. Ultimately, on the 10-day lag a dipole structure similar to the negative NAO phase was formed over the North Atlantic region.

Crustal velocity structure of a seismically active region such as the Alborz located in North of Iran has a great influence on the precise location of earthquakes, attributing the seismicity to the active faults, and improving the reliability of the seismic hazard assessment. In spite of several researches carried out on the Central Alborz crustal structure, very little is known about the structure and thickness of the crust beneath the Western Alborz which is significant due to occurrence of the 1990 Manjil-Tarom earthquake with Ms = 7.3. In this study, we intend to examine the thickness and structure of the crust beneath three stations of Zanjan, Roudbar and Ghazvin located in Western Alborz by joint inversion of the receiver functions and Rayleigh wave group velocity dispersion measurements. A combined inversion of Rayleigh wave group velocities and body wave receiver functions increases the uniqueness of the solution over separate inversions and also facilitates explicit parameterization of layer thickness in the model space. The time-domain iterative deconvolution procedure, which has higher stability with noisy data compared to frequency-domain methods, is employed to deconvolve the vertical component of the teleseismic P waveforms from the corresponding horizontal components and obtain radial and transverse receiver functions for two broadband stations of ZNJK and RUD, and one short-period station of GZV. The waveforms were corrected from the instrument response before proceeding with the receiver function deconvolution. High frequencies were filtered using a Gaussian filter, at 2.5, 1.6, and 1.0, giving an effective high-frequency limit of about 1.2, 0.8 and 0.5 Hz, respectively. As the structure may vary with azimuth and with epicentral distance, all the observations were grouped by azimuth (< 10°) and distance (Δ < 10°). To increase the signal-to-noise ratio of the deconvolved traces, the individual receiver functions were aligned according to the P-wave arrival and point-to-point stacked waveforms. The stacked receiver function was then allocated an average slowness and the back-azimuth of every event was included in the stack. Rayleigh wave group velocity dispersion came from tomographic images in a time period between 10 s and 70 s produced by a study of regional fundamental modes of Rayleigh waves propagating across Iran and surrounding regions. Fundamental-mode Rayleigh wave group velocities to each stations were taken from the corresponding tomographic cell containing the station. The results show that the crust beneath the Roudbar station has a thickness of 36 ±3 km. A shallow low velocity sedimentary layer, of about 4 km thickness, and a velocity discontinuity at a depth of ~12 km is observed in the crustal model of this station. Beneath the Zanjan Station, the Moho depth varies from 38 to 42 km. The same sedimentary layer as beneath the Roudbar station and an interface at about 15 km depth are observed. Toward east, beneath the Ghazvin station, the thickness of the crust increases up to 52 km which is close to that proposed for the crust of the Central Alborz. Our seismological results show that the Western Alborz has a moderate crustal root but of insufficient thickness to compensate the elevation of the range.

Structural interpretation in geologically complex structures is a controversial task in the field of seismic interpretation. In recent years, Seismic imaging technology continues to make remarkable progress in imaging of complex structures such as sub-salt, fault andthrust areas and mud volcano bearing areas. The latest advances in the areas of migration and velocity estimation are the reverse time migration, pre-stack reverse time-depth migration, common reflection surface stack, partial common reflection surface and common diffraction surface stack methods. The continuous advances in computing facilities make such data-driven approaches feasible which have increasingly gained in relevance in recent years. In these methods, the subsurface structures are imaged without deriving a complete model for the elastic properties of the layers. In this case, just an implicit knowledge of the elastic properties directly derived from data would be sufficient. Common reflection surface stack method is one of the data-based seismic imaging methods which simulate the zero offset section. It has the great advantage that it is independent from the velocity model. By paraxial ray theory, the second order traveltime equation of the common reflection surface would be derived which gives a surfaceshape operator that works as the stacking surface. The basic idea of this method is to take the kinematic reflection response of a segment of the reflector with defined curvature and orientation by two hypothetical experiments providing the wavefronts of the so-called eigenwaves. One eigenwave is obtained by placing a point source at the reflector that produces the upgoing normal incidence point wave. An exploding reflector experiment yields the second upgoing eigenwave called the normal wave. The curvature and the raypath of the wavefronts of these waves are known as the parameters of the stacking operator. To simulate the zero offset section, three parameters or kinematic wavefield attributes are needed one of which is related to the emergence angle of the central ray or to the orientation of the reflector segment, while two others are related to the curvature of the reflector. Therefore, the common reflection surface stack method, unlike the common mid-point stack method, is not restricted to a subset of multicoverage data, and it also works on the full data volume. Seismic data from a complex structure in the Southwest of Iran was processed by the common reflection surface stack method to overcome some of the ambiguities of seismic imaging in such regions. In the first step, some preprocessing was done on the data to be prepared for seismic imaging. Then, the data was processed with two imaging methods. The results obtained by the conventional method showed lots of ambiguities in the final seismic section. To solve these problems, the common reflection surface stack method was applied to the data. However, the result was not promising and some sort of optimization on the method was performed. This optimization gave the best kinematic wavefield attributes in complex structures. However, due to large computation time and a large amount of sections that this method gives, theoptimized common reflection surface stack was used from the beginning. The result of the latter method proved that using this method in geologically complex regions could be trusted and helpful in obtaining high quality images.

Detection of subsurface installations and knowing their characteristics and accurate burial places are some challenges that the engineers involved always face with. Urban development, and thus, the necessity for the development of new and convenient installation networks and also the need for maintenance of old installation networks indicate the significance of accurate placement of the subsurface installations. In this regard, non-destructive methods have been considered to be used by many engineers in this field in order to save time and costs and also to reduce the disturbances due to unnecessary drillings in urban areas. In general, geophysical methods are among the most important non-destructive methods. One of shallow subsurface geophysical methods which has obtained some degree of success in this regard is the ground penetrating radar (GPR) method. In this research work, the GPR method is applied in several case studies having different subsurface conditions, and thus, the capability of the GPR method is investigated for accurate placement of subsurface installations in these case studies. Furthermore, we use a different procedure in data interpretation and analysis to analyze the characteristics of amplitude, phase and frequencies of GPR pulses in order to derive maximum information from GPR sections. Three-dimensional (3D) data survey in one of case studies carried out in this research work had made it possible to process, interpret, and visualize subsurface structures in 3D form. Besides, resistivity surveys in the study area had provided us with the possibility of investigation and correlation of the GPR data results with the resistivity findings. Considering that a survey line had been carried out on the subsurface media containing high electrical conductivities, the unfavorable influence of the conductivities of survey media on the GPR measurements made along the survey line was indicated. Since the resistivities (or conductivities) of the subsurface media play an important role in the penetration of GPR waves, we can estimate the resistivities of the subsurface media by analyzing the frequency spectrum of the GPR pulses propagated in the media. Furthermore, the systematic noise affecting the GPR measurements is recognized by this frequency–spectrum analysis as this noise has frequencies different from those of signals. This study also considers GPR and resistivity investigations along a survey line crossing subsurface metallic and non-metallic installations, and thus, detailed investigations made on these subsurface targets. In this area, an estimation of the diameter of the non metallic pipe installed for transferring of water in the subsurface has been made with a good accuracy from the acquired GPR time section along the survey line. Moreover, the analysis of amplitude and phase characteristics of the GPR pulses from some parts of the survey line has made it possible to distinguish or separate GPR responses of metallic installations from non-metallic ones. Finally, by considering GPR measurements along a survey line passing a subsurface non-metallic pipe, we investigated the effect of the fluid inside the pipe.

In many earthquake source studies, the seismic source is assumed to have a double couple (DC) source mechanism, matching shear motion on a planar fault. Observations of increasing quality and coverage, however, resolve departures from the DC model for many earthquakes and find some earthquakes, especially in volcanic and geothermal areas, that have strongly non-DC mechanisms. Burdick and Mellman (1976) used a timedomain inversion method to determine some of the complexity of the source time function. Several attempts have been made to explain the complexity of body waves from large earthquakes by using a multiple event model (Kikuchi and kanamori, 1982). Deviation of earthquakes from the double-couple (DC) mechanism is an important, but delicate tool to study their source processes. It is believed that the earthquake focal mechanisms not only provide information regarding the stress field, but also give information about the rupture phenomena e.g. crack opening. Hence, the deviation from the double-couple mechanism is a matter of investigation. In fact, the study of the non- DC components makes opportunity to provide information about the earth processes. This information may be used to facilitate the operation of the geothermal energy and help predict volcanic activity. On the other side, the complex time history of energy release is a common attribute of large earthquake failures, as is the presence of non-uniform surface displacement along the outcrop of surface-breaking faults. An interesting topic is the search for the connections between the non-DC events, multiple-double-couple events, segmentation of faults and their fractal properties. Critical papers emphasize difficulties in obtaining reliable non-DC components, e.g. due to noise, poor station coverage or incomplete structural models. Understanding non-DC earthquakes is important both for studying the process of faulting in detail and for identifying nonshear-faulting processes that apparently occur in some earthquakes. To assess the non-double-couple component, a new method is suggested, i.e., a hierarchic grid search of the centroid position and time, during which the double-couple percentage (DC%) convergence is studied (Sokos and Zahradnik, 2008). This article uses the iterative deconvolution of multiple point sources, based on Kikuchi and Kanamori (1991), often used to study complexity of earthquakes. The method was modified for regional distances by Zahradnik et al. (2005). The modification involves the full Green’s functions (Bouchon 1981, 2003). Possibly complex events are represented by multiple point source models, which may represent their isolated asperities (Zahradnik and Sokos, 2008). ISOLA calculates the moment tensors (MT) by the least-square fitting of the complete waveforms in the time domain (Zahradnik and Sokos, 2005). Due to the significance of an earthquake rupture process and investigating whether an event of high non-DC percentage can consist of several subevents with slight spatial and temporal intervals, this survey involves more accurate investigation using synthetic seismograms and their analysis. In this study, synthetic seismograms are produced using CPS software package and the seismograms of the main earthquake and its subevent were summed together and the resulting seismogram provided a basis for further studies. In fact, by modeling a source of high non-DC percentage (resulted from summing two 100 DC subevents), the ability of ISOLA to distinguish two subevents with different focal mechanisms is analyzed. Frequency band, crustal velocity model, moment ratio of earthquakes and the added noise value are determined as factors affecting successful retrieval of the two subevents.

In some countries such as Iran with large deserts and sparse rain gauge network satellitebased precipitation estimates have great potential for a wide range of applications. However, satellite-based precipitation estimates are not operational for decision making applications because of a lack of information regarding the associated uncertainties and reliability of these products. Obviously these data sets like others have error. To reduce the error, precipitation data users must have enough information about error characteristics over different parts of the world. In this analysis, satellite-based precipitation estimate data derived from the “Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks” (PERSIANN) is compared with ground-based data over Iran. The PERSIANN gridded precipitation data with 0.25°×0.25 latitude/longitude spatial and 3-hourly temporal resolution are used for evaluation of the satellite product. In this study, satellite-based precipitation data were accumulated to daily and then monthly totals for comparison with accumulated monthly gauge precipitation for the period 2003-2007 over Iran (25°-40° N, 44°-63°E). This rain gauge network included more than 2000 rain gauge stations over Iran. The arithmetic monthly mean of gauge precipitations calculated for every pixel. A comparison of the mean annual precipitation maps between these two networks over Iran shows that for the study period the spatial variation pattern of annual precipitation is reasonably accurate in PERSIANN, but it underestimates the precipitation amount over most parts of Iran. In the next step, the correlation coefficient and the scatter plot of the monthly precipitation for PERSIANN and gauge data were calculated for grid cells which included at least one gauge. Then in an attempt to better evaluate precipitation and reduce the effect of gauge uncertainties, the study was limited to pixels, each of which contained at least five rain gauges. The results for both of them (pixels which include one rain gauge and pixels which include five rain gauges) show that this satellite product underestimates the monthly precipitation. The correlation coefficient between satellite and gauge monthly precipitation for all pixels which include at least one gauge is equal to 0.3035 (99% significant). The correlation coefficient for pixels which include at least five gauges is 0.2598 (99% significant). For a comparison between these two data sets in different topography and climates, the time series of satellite and ground monthly precipitation are plotted for five cells which included at least five rain gauges. A pixel located in mountainous area of Zagros which most of annual precipitation falls in winter and summer is almost a dry season. Another pixel is in the most humid region in the coast of Caspian Sea which precipitation falls in almost all months of the year. One of the selected pixel located in the desert area of the eastern part of country. The two others located at North West and North East of country which have wet cold climate. The results show that PERSIANN underestimates the precipitation in Zagros, and it also has a very poor performance over the Caspian coast. On the other hand, this satellite product overestimates the precipitation over dry eastern area.

A step-by-step numerical solution to dynamic or nonlinear systems depends on the inputtime history record of the strong ground motion. Well-known seismic design codesrecommend using a set of scaled records instead of only one. That is because a singleinput motion is not reliable enough to cover the seismic characteristics of all possibleearthquakes for engineering design purposes. As a current state of practice, the scaling coefficients are taken similar and the result does not necessarily lead to a close compatibility of the resulted mean spectrum with the standard target. In this regard, the coefficients as floating-point numbers should be searched in the form of an optimization problem. Such a problem deals with a continuous type of search space with an infinite number of points. Thus complex optimizer engines are required to deal with it and seek a true global optimum set of scaling coefficients in order to suitably combine the selected ground motion records for further seismic design purposes. Particle Swarm Optimization, PSO, is one of the multi-agent meta-heuristic methods successfully applied to a variety of engineering design problems. The present work formulates the problem of seeking optimal scaling factors using a utilized version of swarm intelligence as this method is best suited for continuous search spaces. In addition to inertial, cognitive and social terms of design point directions, an extra term is also utilized to improve the algorithm performance. In the first case, it is a new design vector with its elements selected one by one from other vectors in the current population of the swarm particles. The second modification is ordinating the velocity vector toward a randomly re-initiated particle position. In addition to the standard form of the particle swarm optimization, the aforementioned PSO versions are thus utilized, employed and further compared in the present work. A variety of real-world ground motion records are picked from an available earthquake. The target spectrum is selected according to the Iranian Standard No.2800 for the soil type III and five percent damping considering the case of practical building structures. For each earthquake, the response spectra are generated for its longitude and transverse excitations and then combined using the Square Root of Sum of Squares (SRSS) method. The resulting SRSS acceleration response spectra are then averaged with the scaling factors with respect to the design target assigned by the developed optimization algorithms. For the sake of true comparison, the same control parameters are chosen for three proposed versions of PSO, taken 2 for all the social, cognitive and extra congregation or combinatorial term except for the inertial coefficient which is taken 0.4. An error function is also defined to evaluate the compatibility of such weighted average spectrum with the target. The optimizer then samples various combinations of the scaling coefficients for the SRSS spectra and evaluated the error function for every such set. It seeks the optimal set among the continuous search space using the utilized artificial swarm intelligence for a pre-assigned number of particles and algorithm iterations. Consequently, the achieved results in the treated example show superiority of the optimized set over those in the code practice and considerable convergence/effectiveness improvement in the proposed methods over the standard particle swarm optimization.

Open aggregate storage piles are used more and more in industrial sites. In industrial areas, emitted particulate matters from piles of row material can affect the quality of life of workers and employees and also the quality of the environment. Study of dispersion patterns and concentration of particulate matters over a landscape is important for the strategy of monitoring and controlling particulate matter. Within an industrial facility, dust emission may be generated by wind erosion of open aggregate storage piles and therefore, it pollutes the environment and wastes the row materials. Emission of particulate matters from surface of a pile depends on many parameters such as characteristics of wind (e.g. wind speed and wind direction), specifications of particles (e.g. particle diameter, density, shape, etc.) and erosion properties of surface. Therefore, for emission calculation of particulate matters from a pile and also for simulation of dispersion of emitted particles, it is necessary to simplify the physics of this phenomenon. Simplifications have been carried out based on governing equations and also applying the empirical relations obtained by field studies. Based on these theoretical and empirical investigations, a few methodologies are available for atmospheric wind erosion calculations from storage piles of row materials. The U.S. Environmental Protection Agency (EPA) method is one of the most famous approaches to this kind of calculation. It focuses on estimating the wind erosion and it cannot be used for dispersion pattern prediction. On the other hand, some models and methods have been developed to calculate the dispersion of pollutant in near and far distances from sources. One can combine the calculation of particulate matters emission with dispersion models in order to determine the particulate matters concentration at the environment. In the present work, two methods including the U.S. EPA wind erosion estimating approach combined with Von-Karman's scheme for dust settlement and computational fluid dynamic (CFD) method using Fluent 6.3.2 Software are applied to predict particulate matters dispersion patterns from an iron ore pile. The Von-Karman's method is based on the length and time of the particulate matter settling. In the present work, the concentration of particulate maters in different distances from the source has been calculated using these parameters. In the CFD technique, the geometry of a pile is generated in Gambit Software using a structured mesh tool. The number of the generated mesh on the pile is 104,214. In this study, the flow condition is assumed to be incompressible, turbulent and steady state. Turbulence modeling is carried out based on two types of modeling namely k  and k  theories. Atmospheric wind profile is assumed to be in neutral conditions and defined by a user-defined function (UDF) tool from Fluent Software. The results from the two methods are compared with concentration of particulate matters measured based on 10 points. The maximum concentration position predicted by the CFD approach is more precise than that predicted by Von-Karman's method. Good quantitative and qualitative agreements are observed between the CFD predicted deposition and the measurement results. The determination coefficient for CFD and Von-Karman methods are 0.71 and 0.35, respectively. Also, Von-Karman method underestimates the concentration of particulate matters in all 10 measurement points.