مجله ژئوفیزیک ایران
سال هشتم شماره 4 (پیاپی 23، زمستان 1393)

In this study, the spectra of 14 micro-earthquakes occurred in 2007-2008 were investigated. The waveforms of these events were recorded with the local seismological networks (2007-2008 and 2008) of the Geological Survey of Iran and also of the Institute of Geophysics, University of Tehran. Magnitude (ML) range of these micro-earthquakes was 1.0-4.0. They were recorded from 2007/10/12 to 2008/12/30 and they were well located using 29 stations from the above-mentioned networks. Parameters related to the earthquakes sources, e.g. source dimension, scalar moment, P and S corner frequencies, dynamic parameter of stress drop and moment magnitude, which are applicable in seismology, are calculated and processed using their spectral contents. The exact values of the above mentioned parameters are not reasonably extractable, but changes in these parameters with time or space and comparison with each other could be virtually processed. They could be considered as physical characteristics and properties of the shallow earth crust. In this study, spectra of different events recorded with three components of one station and also the spectra of a specific event recorded in different stations in three components were processed. Processing concluded that there was a little difference in the corner frequency and high-frequency decay between micro earthquakes recorded in different stations. All the spectral diagrams in this study were computed using a Fast Fourier transform program. The relationship between corner frequency and sample duration, corner frequencies of P and S waves, amplitude and epicentral distance, scalar moment and source dimension and finally local magnitude and source slip of the earthquakes were investigated. We tested the effects of the signal truncation on spectra of some events. The geometrical spreading of the wave path medium was inversely proportioned to the hypocentral distance in the Eastern Alborz. The amplitude decay was about f-2 in the frequency (f) spectra. The maximum stress drop of these earthquakes was 126 bar (related to the earthquake of magnitude 4.0 occurred at 2008/7/16 over the most active Chashm thrust fault within the area) which was noticeably greater than the others. Finally, for the first time at the Eastern Alborz, an empirical relationship between the local magnitude of the earthquakes and their source slips was derived.

In the present study, the TRMM 3B43 precipitation database was validated as one of the TRMM products. This precipitation database estimates rainfall by applying both satellite observations and rain gauge data. This database utilizes two groups of data: microwave and infrared data. GPCC data are used in the database as supplementary data. The launch of the Tropical Rainfall Measuring Mission (TRMM) satellite in November 1997 by National Aeronautics and Space Administration (NASA) of the US and the Japanese Aerospace Exploration Agency (JAXA) provided more than fifteen years of quality rainfall data for tropical and subtropical rainfall studies. The TRMM3B43 precipitation output comprises 0.25×0.25 grid cells for every month with a spatial extent covering a global belt (180W to 180E) extending from 50S to 50 N latitude. In the present study, Asfezari and TRMM3B43 gridded precipitation databases were compared to each other from 1998 to 2004 that is the joint period of time between the two databases. Asfezari national database has been made using more than 1400 weather stations in Iran. In the Asfezari database the data of synoptic, climatology, and rain stations have been applied to construct it. It covers the period of 1961 to 2000. The correlation coefficient was 0.97 which showed a significant correspondence between Asfezari and TRMM 3B43. The bias of TRMM 3B43 was calculated on 2491 grid cells at a resolution of 0.25 * 0.25 geographical degrees of latitude and longitude for all the seasons. Results showed that there was not a considerable difference between the two databases in a large extent of Iran. Most of the bias has been calculated to be along the Alborze and Zagrous mountains. It seems that most faults of the satellite data are on highlands where the estimation of the rainfall is not as accurate as in other parts of the country. Overall findings showed that the satellite data underestimated the amount of rainfall on the central parts of Zagrous Mountains. The satellite data underestimate the rainfall between 5 to 2 mm in an annual timescale in this part of the country. In some parts of the Alborze and Zagrous mountains, there was an overestimation of precipitation by TRMM 3B43. The amount of this overestimation was between 9 to 25 mm in an annual timescale. In the other parts of the country, the bias of precipitation was -4 to +9 mm. It seems that this database has a fault in the estimation of precipitation that originates from the factor of mountains and the difficulty that the aforementioned satellite data has over highlands. It seems that it underestimates the precipitation over some highlands and overestimates it on some other highlands as well.

4D (or Time-lapse) seismic study is based on repeating 2D or 3D seismic surveys over the same area with the same acquisition parameters, in different times and measuring the difference in seismic data in terms of both amplitude and reflection time. This technique has been increasingly utilized to monitor the fluid flow during the hydrocarbon production, or during the enhanced oil recovery to assess unswept target zones through miscible or immiscible flooding. An overview of reservoir properties such as porosity, pore pressure, temperature, and water/oil/gas saturation changes as a result of depletion or injection could be investigated through 4D seismic analyses. Time lapse studies are usually subject of investigation on reflection seismic data. However, this technique could be applied to any other seismic techniques such as Vertical Seismic Profiling (VSP). In 4D seismic studies, subtle changes in the reservoir properties could be studied via change in seismic wave properties, if good quality seismic data is available. A feasibility study is a prerequisite in 4D seismic acquisition, due to high cost of repeating a seismic survey (especially in a vast area with 3D coverage, such as oil and gas fields in Iran). Gassmann rock physics model is widely in use for fluid replacement to predict seismic properties in porous rocks such as sandstones with high porosity and permeability. Carbonate rocks usually have a higher density and elastic modulus than sandstones, and include less porosity and permeability. Also the pore shapes and their connections in carbonates are more complex and different from sandstones (penny shapes rather than spherical). Since the Gassmann model does not count for the pore shape type and geometry, other rock physics models such as Kuster-Toksoz model is required to be utilized to study fluid replacement effect on seismic wave parameters in carbonate rocks. Kuster-Toksoz model is also considering the effect of mineralogy as well as pore shape and geometry. In this research, as a 4D feasibility study, the change in seismic wave parameters due to hydrocarbon production (fluid replacement) in a well of carbonate oil reservoir located in South- West of Iran has been investigated. Based on inverse Kuster-Toksoz rock physics model, percentage of different porosity types (spherical, disk, and needles) in the considered well is modeled. As a result, however, the spherical porosity in the well was dominant (45% of total pores), other porosities included a considerable share (55% of total pores). Considering the pore shape and geometry and the proportional porosity percentages via Kuster-Toksoz rock physics model, the average change in P and S velocity, bulk modulus and density due to hydrocarbon production (replacing oil by gas) was about 380 m/s, 63 m/s, 2.6 Gpa and 78 kg/m3 respectively; while using Gassmann rock physics model which did not include the pore shape and geometry and the proportional porosity percentages, the primary wave velocity and the bulk modulus were 163 m/s, 1.35 Gpa respectively. This suggests that the field could be subject of 4D seismic study for fluid flow detection, if high repeatability of the seismic survey could be achieved and seismic data could be considered as high quality data.

An accurate estimation of evapotranspiration is a key issue in running climate models, especially for the calculation of surface fluxes. In recent years, by development of global and regional climate models, long-term predictions of weather parameters affecting evapotranpiration have been done more easily. The ability of the RegCM regional climate model (Version 3) in simulating the potential evapotranspiration over Mashhad in Northeastern Iran was evaluated during the base period of 1961 to 1985 and the future period of 2021-2035. Due to lack of a measured amount of evapotranspiration, the Penman–Montith (P-M) equation was chosen to estimate actual values of ET in the base period. For initialization of the RegCM3 model, boundary conditions from EH5OM General Circulation Model (GCM) were used as initial and boundary conditions to feed the RegCM3 regional model. Future predictions of evapotranspiration were done under A1B emission scenario. A horizontal resolution of 50 km was considered for the model. Based on the assumed conditions in running the model, the results showed that the nonpost- processed RegCM model outputs cannot be used for the estimation of potential evapotranspiration. However, after post processing using multivariate regression, results were closer to those calculated by P-M equation. Temperature and radiation parameters were considered as independent variables in the multiple regression models to perform post-processing. Our results showed that the mean annual evapotranspiration in the future period (1075 mm) will be increased by 16.34%, compared to the base period (924 mm). On the whole, the average potential evapotranspiration will be increased in April, May, June, August, September and October, while it will be decreased in January, February, July, November and December, compared to the base period. The outcomes of the present study reveal that the maximum evapotranspiration in the future period will be in June, while in the base period the maximum amount of evapotranspiration occurs in July.

A vertical reference surface was used as a reference to measure the heights of the points on the earth surface. A vertical datum can also be defined by computing the geopotential number of the origin point (tide gauge station) using its ellipsoidal height and absolute gravity value. In this research, after determining the mean geopotential for the sea level, three local vertical datums (LVDs) were described for three tide gauge stations namely, Bushehr, Hormozgan, and Chabahar, on the southern coast of Iran. Since the mean sea level is not constant, the equipotential surfaces which create the local datums are not coincided and show some deviation from each other to an undefined extent. These offsets are calculated by using a Global Navigation Satellite System (GNSS) with ellipsoidal height, normal-orthometric height and height anomaly of the datum. Therefore the data can be related to each other. One goal of the modern geodesy is the global unification of vertical data so that height data from them can be properly integrated. The unification of these LVDs may be performed by using a regional gravimetric quasigeoid model and also the ellipsoidal height data on each datum. For this purpose, the iteration method was applied. Using the LVD offset of the related datum compared to quasigeoid, the gravity anomalies of each datum was reduced to a quasigeoid model. The quasigeoid was computed by combining two global geopotential models, namely EGM96 and EGM2008, with a set of the gravity data obtained from Bureau Gravimetrique International (BGI) including the total number of 8582 stations across Iran and the digital elevation model (DEM) with three arc second resolution. The reductions were applied to the gravity observation to produce the free-air and complete Bouguer anomalies. Because many countries do not have gravity observations along all the precise leveling routes, the computation of orthometric or normal heights is not strictly possible. To overcome this limitation, the normal-orthometric height system was developed. In this research, the normal-orthometric height system was used to reduce the measured gravity values from the earth surface to the quasigeoid. The normal-orthometric heights for the BGI stations as well as for the tide-gauge stations in Bushehr, Hormozgan and Chabahar were calculated based on a program prepared in Matlab. The solution converged after three iterations. Creating these data, and unification of them, the height of the stations located in the area of these three local vertical data can be calculated. A relation for determination of the dependency of these offsets to the heights of the data was also presented. It should be noted that the mean offsets and the information relevant to each datum were calculated separately. The base of this calculation was the determination of reduced anomalies for all points of the data and the related preliminary values of the offsets for each datum. Finally, it may be concluded that the quasigeoid models resulted from the iteration method perform a vital role in the vertical datum unification. Comparison of such quasigeoids with those obtained in previous researches, and also considering the standard deviation of 0.6 m showed that the iteration method may be a suitable method to determine the quasigeoid in coastal areas. Furthermore, the combination of the described quasigeoids with the obtained offsets can be applied to transfer the reference ellipsoid as a datum to each one of the LVDs.

Seismic data interpretation methods provide useful information about underground structures. Since many years ago, several methods have been developed to aim this goal. Seismic facies analysis is one of the new methods in seismic interpretations. This method can produce a classified section using reflection seismic data and/or seismic attributes. Classified sections can reveal lateral changes in seismic facies which may relate to geological facies changes. Using different pattern recognition methods, several seismic facies analysis methods have been developed in recent years. However, in this study, an agglomerative hierarchical clustering algorithm has been utilized to produce classified sections. Seismic facies is a group of data whose attributes are different from those of neighbor groups. Each attribute can extract additional information about underground. Using a single attribute makes it difficult to get more information. However, by combining several attributes in a hierarchical clustering algorithm, it is possible to interpret seismic data in a more appropriate way. In hierarchical clustering, all time samples are divided into similar clusters. At first, each sample is assigned to one cluster. Dissimilarity matrix is constructed based on a distance definition such as Euclidean distance between samples. This matrix is then used to cluster all samples in a hierarchical procedure. In each step, more similar clusters merge into a new cluster and the dissimilarity matrix is updated. Finally, all samples merge into one cluster. Before clustering it is common to perform a principal components analysis, PCA. PCA is a statistical technique to perform dimension reduction. Using PCA, we can find the directions in data with the highest variation and reduce the dimensionality of a large data set with interrelated variables without considerable loss of information. In this study, the PCA was utilized to attenuate the redundant and random noisy data. Prior to the PCA, it is necessary to normalize the data. Clustering algorithm in this study was applied to three synthetic models as well as 2D and 3D real seismic data of an oilfield, Southwest of Iran. The first model was a horizontal-layer one with lateral changes in facies. The second model was a horizontal-layer one with a normal fault which caused a movement of layers. The third model was an anticline one with lateral changes at the top of the anticline. Real seismic data from an oilfield in the Southwest of Iran was used for this study. Nine seismic attributes were calculated using the Paradigm software to extract more information from migrated seismic data. These nine attributes and the primary seismic data were normalized and entered into the PCA. Seven principal components were selected based on the PCA. These data were used to apply to clustering algorithm. Our results showed that the seismic facies analysis can provide useful information about the underground structures and lateral changes. In the cases of the first and second models, lateral facies changes were revealed for signal-to-noise ratios of up to 4 dB. Regarding the third model, the results were acceptable for signal-to-noise ratios of up to 8 dB. In addition, it was shown that defining more number of clusters could not lead to better results. By comparing 2D and 3D data clustering, it is concluded that the resolution of seismic facies in 3D clustering is quite related to 2D one.

The oceanic and atmospheric models have been developed on different numerical grids. The Arakawa's C grid is well-known because of the advantages of the C-grid discretization at high resolutions. The C grid, however, is well suited for reproducing high frequency inertia-gravity waves in resolved cases, but there are difficulties in dealing with the Coriolis terms and low-frequency processes. In particular, the C-grid approach is unfavorable in the under-resolved cases with grid-scale noise. Several fixes have been proposed for the C-grid problem. One such method is the C-D grid approach which improves spectral properties of the inertia-gravity waves at low resolutions. The C-D grid approach employs a combination of the C and D grids such that all terms are the same as in a conventional C-grid discretization except for the Coriolis terms where the D-grid velocities are used so that they require no interpolation. Another grid is the LE grid that comprises the same structure of Arakawa’s E grid with a different grid space. Most of these studies apply the traditional second-order finite difference method to spatial differencing on the C-D grid, but the application to higher accurate finite difference methods is lacking. Finite difference methods are commonly used to simulate the dynamical behavior of geophysical fluids. Numerical simulations of the complicated flows such as vortices, turbulent currents and instabilities need high accuracy methods as well as high resolutions. The compact finite difference methods are powerful ways to reach the objectives of high accuracy and low computational cost. The super compact and combined compact finite difference methods can be considered as promising methods for large scale computations in atmosphere–ocean dynamics with high accuracy. In this study, we derived the general discrete dispersion relations of inertia-gravity and Rossby waves on the C-D and LE grids. The linearized single-layer and two-layershallow-water models were used to describe these kinds of waves which play an important role in the setup of the ocean circulation. These relations were used to assess the performances of the sixth-order super compact finite difference (SCD6) and sixthorder combined compact finite difference (CCD6) schemes on the C-D and LE grids. The results on these grids were compared to Randall’s Z grid and Arakawa’s C and D grids. The general discrete dispersion relations of inertia-gravity waves on the C-D grid were similar to the LE grid at both single layer and two-layer models, but they were different for Rossby waves. The results of the present work revealed that the CCD6 scheme exhibits a substantial improvement over the SCD6 scheme for the frequency and group velocity of inertia– gravity waves on the C-D and LE grids. In the same manner, for the frequency of Rossby waves, the performance of the CCD6 scheme is better than that of SCD6 scheme, but for the group velocity of Rossby waves, the SCD6 scheme is slightly more accurate than CCD6 scheme. In general, the C-D grid is, however, composed of Arakawa’s C and D grids which are susceptible to grid scale noise but its behavior is favorable for both inertia-gravity and Rossby waves. In addition, for inertia-gravity waves, it could be observed that the accuracy of the SCD6 scheme on the C-D grid is similar to the Z grid and even the CCD6 scheme exhibits higher accuracy on the C-D grid.

Since the earth acts as a low-pass filter, it changes frequency content of passing seismic waves. Therefore, the seismic data are non-stationary signals. Due to the non-stationary property of seismic data, spectral decomposition based on Fourier transform cannot reveal the appropriate characteristics of them. It cannot show changes of frequency content of the seismic signal with respect to time. Since, the spectral components of a non stationary signal are functions of time, a simultaneous representation of time and frequency will be very useful for the analysis of such signals. Time-frequency transform upgrades the spectral decomposition to a new step and can show time and frequency information simultaneously. Spectral analysis of seismic data using time – frequency transforms, converts the seismic amplitudes, which are a function of space and time, to spectral values, which are a function of frequency, time and space. Nowadays, the time-frequency transforms have been widely used in the seismic data processing and interpretations. They can be used in estimation of layer thickness, reservoir characterization and exploration, estimation of absorption coefficient, burial channel detection, random and coherent noise attenuation and, etc. The time-frequency distribution can be computed by various methods, each of which has their advantages and disadvantages. Short-time Fourier transform (STFT) is one of the conventional spectral decomposition methods. The STFT spectrum is obtained as the Fourier transform of various windows of signal with various time centers. The windowed form of Fourier transform and the Heisenberg uncertainty principle affects the resolution of time and frequency in the STFT spectrum. According to this principle, the time and frequency resolution of the STFT spectrum cannot be simultaneously increased. Various methods have been introduced to simultaneously increase the time and frequency resolution in an STFT spectrum. Fourier transform can be written as a matrix equation. In the case of underdetermined inverse problems, there are numerous solutions for the matrix equation of Fourier transform. The least squares solution is one of the many available solutions which is the smoothest solution. Daubechies et al. (2008) introduced an algorithm that obtains a sparse solution for an inverse problem using the constrained least squares method. This method is an iterative algorithm. We can improve the resolution of STFT spectrum by replacing the conventional Fourier transform with the mentioned algorithm. The efficiency of this method is evaluated by applying to both synthetic and real seismic data. The results of the synthetic example showed that the constrained least squares spectral analysis (CLSSA) had a better resolution than the conventional STFT method. We used the CLSSA to illuminate the low-frequency shadow corresponding to a gas reservoir at one of the gas fields in the South-West of Iran. The results of the real data example showed that the CLSSA has a much better resolution than the STFT.

Velocity model building is a crucial step for construction of seismic image of the subsurface in depth imaging. A wide variety of different velocity model building methods are available. Reflection tomography is one of those methods. One of the drawbacks of tomography method is that it requires picking reflection events in the prestack data. Picking procedure is extremely time consuming and can become difficult if the signal to noise ratio in the data is low. In this study, a new version of tomography called Normal Incidence Point (NIP) wave tomography is used for construction of velocity model. This technique makes use of traveltime information in the form of kinematic wavefield attributes. These attributes are coefficients of the second order traveltime approximations in the midpoint and offset coordinates and can be extracted from prestack seismic data by means of common reflection surface stack method. The required input data for NIP tomography inversion are taken from stacked results at number of pick locations, while these locations do not need to follow a continuous horizon in the section. The problem of building the velocity model by tomography method is solved in an iterative manner here. During iterations, difference of observed and modeled data is minimized and the model is updated. This procedure would continue until the misfit falls below a specified value. Modeling observed data for the first time requires an initial velocity model. Initial velocity model in normal incidence point tomography contains a constant near surface velocity which increases linearly with depth. In the present study, four different functions, introduced by different researches, used besides linear function to produce initial velocity model. In addition to these functions, the stacking velocity derived from kinematic wavefield attributes was used in NIP tomography, as initial velocity model. Accuracy and consistency of these velocity models were evaluated by application to a 1D and a 2D synthetic data. Result of these data showed that different initial velocity models due to different functions used in NIP tomography, have different effects on the final velocity model. In 1D data example, the result showed that the NIP tomography method with new velocity function introduced to the tomographic algorithm will gives accurate velocity model after little iteration with acceptable error and high consistency with the data. In case of 2D synthetic data example, five different velocity models obtained by normal incidence point tomography with four velocity function besides the stacking velocity as initial velocity model. Different final velocity models obtained here show different ability of functions in handling lateral heterogeneities. However, the velocity functions introduced in other studies showed that besides the importance of initial velocity model in normal incidence point tomography, they could not serve as a suitable initial velocity model. Although these models were consistent with the data, they were not able to separate close velocity anomalies. However, the velocity model obtained by stacking velocity as initial model in normal incidence point tomography shows higher accuracy and consistency with the data and could handle lateral velocity changes in tomographic procedure, too. These techniques were applied to a real dataset. This dataset contains geometric complexity and lithological complexes. Therefore it could clarify the ability of these velocity equations in producing acceptable migrated section. All of the equation used to make velocity model for this dataset are then used for post stack migration. By comparing the migrated section obtained, the linear function and stacking velocity function showed that they could perform better in the presence of lateral velocity heterogeneities. Later on, these two models were used to produce acceptable prestack depth migration sections. The stacking velocity used for the initial model for NIP tomography gave better result in presetack depth migration. This result was compared with the result of conventional prestack depth migration. The velocity model for the latter case was obtained by the migration velocity analysis technique. Results of both methods were comparable. However, the NIP tomography model was so simple and smooth and also obtained in so much less time compared to the complex migration velocity analysis model.

Super storm Gonu is one of the strongest tropical cyclones which have occurred after the deadliest and most destructive hurricane Katrina (which occurred over the Gulf of Mexico during 23rd August to 3rd September in 2005) in 2007. Such intense tropical cyclones have happened rarely over the Oman Sea since most storms in the Arabian Sea tend to be small and disappear quickly or making landfall on the Arabian Peninsula and/or the Indian subcontinent. According to the historical records of severe cyclonic storms formed over the Arabian Sea، severe cyclonic storms were not reported in the Arabian Sea during 1970 to 2007 but Algeria broadcast and old people of Hormozgan believed that first time، it happened in 1977. However، there is no information about it. The Saffir Simpson scale separates hurricanes (with winds of 74 mph or greater) into five ascending categories based on the maximum sustained wind speeds، the potential height of its dangerous storm surge، and the hurricane’s central barometric pressure. The super cyclone Gonu was a Category Five tropical storm (Saffir-Simpson Scale) which occurred over the Northern Arabian Sea in June 2007. The minimum pressure of this tropical cyclone reached 920 hPa on June 4th. The meteorological phenomena which occurred during the storm activity in Iran have been announced by Iranian Meteorological Organization as “cloudy sky with heavy rain and thunderstorms;”، a raging sea that the height of its waves reached to 5. 8 meters. This research surveys the characteristics of tropical storms، synoptic and dynamic factors which affect the formation of Gonu cyclone and its impact on the South and Southeast of Iran. For this purpose، charts of NCEP/NCAR reanalysis data set have been studied in this research. The region which we considered in this research was 0° to 90°E longitudes and 0° to 70°N latitudes. A survey of surface charts and upper level atmospheric charts such as 850، 700، 500 and 300 hPa from the 1st to 8th June 2007 showed that the trajectory of the tropical depression was at first toward the Indian subcontinent، which gradually became stronger، and formed a tropical storm on 3rd June. However، an extending high pressure ridge in the south of Indian subcontinent caused the storm’s path to change from the Northeast (toward the Bay of Bengal) to the Northwest (toward the Persian Gulf). As a result، the storm moved toward the Northwest and finally it made a landfall over the Southern region of the Oman Sea. On the sixth day، the Scandinavian high pressure ridge weakened; the core axis of storm was from the South to the North direction at that time، and had drawn it to the Southern part of Iran. In this case، the storm carried its obtained moisture from the Arabian Sea and Oman Sea to the South and Southeast of Iran by its easterly flank flows. Falling cold air behind the storm by the Scandinavian anticyclone ridge on White Russia (the north of Black Sea)، which is associated with the further strengthening storm. The European anticyclone on the seventh day was weaker than the previous day; as a result، the core of the storm had taken the southeast-northwest direction، then imported into the southeast of Iran by meridional speed of 8 ms-1. Colliding with the southern part of Zagros Mountains، the storm Gonu caused convective (potential) instability and formation of cumulonimbus clouds and thunderstorms which synoptic reports of Iranian meteorological stations confirmed it. After crossing the Southern coast of Iran، entered to the country from south، and the intensity of storm activity decreased during moving on the rugged parts of Hormozgan، Sistan and Baluchestan and Kerman provinces (the Southern Zagros Mountains)، and then disappeared with moving toward Pakistan. The highest rainfall recorded during the storm activity in the Southeast Iran were received on the sixth day of June by the ports of Konarak and Jask، for which the amounts were 90 mm and 78 mm، respectively. The greatest amount of precipitation on the seventh day was reported by Nikshahr to be 120 mm; Jask also received 59 mm of rainfall during the eighth day. Nikshahr is located in the extreme Southwest of the province of Sistan and Baluchestan. The area is mountainous and 98% of its tissue consists of highlands and mountains and the remainder is covered by plains and deserts.