فصلنامه فیزیک زمین و فضا
سال سی و ششم شماره 2 (تابستان 1389)

The central Alborz Mountains of northern Iran (Figure 1) is a zone of intense active continental deformation and is the most heavily populated region of Iran, including the mega-city of Tehran with a population of over 10 million. The region is affected by numerous active faults, some of them having great seismic potential, and documented historical seismicity. Hence, the central Alborz is a prime candidate for seismic hazard evaluation studies. The choice of ground-motion model has a significant impact on risk estimates for a distance range of 50 to 200 km within an active seismic zone such as the central Alborz.

On 26 December 2003 at 05:26LT (01:26GMT), a catastrophic earthquake Mw 6.6, seismic moment (6 – 9 ×10 Nm) struck the city of Bam in the Kerman province of southeast Iran. The intense shaking in the city caused the complete collapse of nearly every building in the central parts of the city including many of the newer buildings, killing about 40000 people officially. The city lies to the east of the Nyband – Gowk – Sarvestan fault system and on which several powerful earthquakes have occurred over the past 23 years [Berberian et al., 1984; Berberian and Qorashi, 1994; Berberian et al., 2001]. There are no recorded historical earthquakes at Bam. Most of the citadel of Arg-e-Bam, one of world heritage sites inscribed by UNESCO, which was constructed by mud brick about 2000 years ago was destroyed in this earthquake.

Linear filters are used for a wide range of magnetic science including noise attenuation, spatial derivatives, upward and downward continuation and reduction to the pole. The majority of these filters are spatially-invariant, meaning that the filter has a constant wave number response over the whole signal. In contrast, many signals which encountered real problems such as magnetic signals, typically exhibit a spatially-varying wave number content which motivates us to design filters with spatially-varying wave number responses. This leads to better preservation of anomaly gradients in the calculated derivatives than is possible using conventional Fourier or space domain smoothing techniques.

One of the most fundamental reservoir characteristics is the thickness. The analysis of thin bed tuning on seismic reflectivity has been studied extensively by Wides (1973) and Neidel and Pogiaggliomi (1977), who discussed the limits of seismic resolution. During the past decade, the industry has developed a plethora of new attributes in studying thin beds by employing spectral decomposition (Peyton et al., 1998; Partyka et al., 1999), and attributes which are obtained from it (Marfurt and Kirlin, 2001). Spectral decomposition refers to all methods that generate frequency spectrums consisting of amplitude spectrum, phase spectrum, change of phase with frequency and power spectrum in windows with the center of each time sample of a trace. These methods are used in studying geological features, thin beds, hydrocarbon reservoirs and noise attenuation. The most important of these methods are short time Fourier transform (STFT), continuous wavelet transforms, S-transform, Wigner-Ville distribution and matching pursuit decomposition. The result of a trace spectral decomposition is a time-frequency map.

The ultimate goal of the reservoir geophysicist is to determine the reservoir properties (lithology and porosity) and conditions (pore fluid and pressure) from seismic data. This goal can be achieved by applying rock physics transforms to a volume of seismically-derived elastic properties. The basis for establishing rock physics transforms are controlled experiments where the reservoir and elastic sediment properties are measured on the same sample of reservoir under the same conditions. Such experimental data come from well logs and cores. The purpose of this paper is to apply rock physics diagnostic to well log data from the Asmari reservoir in Mansuri oil field and then used to quantify porosity from acoustic impedance inversion volumes. The results show that Nur-Dvorkin (1996) model and Raymer-Greenberg-Castagna (1997) are good for predicting porosity in sandstone and the carbonate zone of the Asmari reservoir respectively.

A fluctuating electric current flowing in the Earth’s atmosphere causes corresponding electric currents to flow in the conducting Earth below the source current. The depth of penetration of the induced currents is determined by the characteristics of the source currents as well as the distribution of electrically conducting materials in the Earth. At the Earth’s surface observatories measure the composite of external (source) and internal (induced) field components from the currents. The quiet daily field variations, called Sq for 'solar quiet-time', provide a natural signal source with frequencies appropriate to upper mantle conductivity studies. This paper is concerned with the quiet-day field variations, their separation into external and internal contributions, and the use of this separation to profile the electrical conductivity of the Earth's upper mantle.

A new coupled system of the aerosol HAM model and the Weather Research and Forecasting (WRF) model is introduced and tested in this paper. Unlike the two other aerosol schemes currently coupled in the WRF model (MADE/Sorgam and MOSAIC), the HAM applies a new "pseudomodal" approach for the representation of the aerosol particles. The aerosol population in this model is represented by the superposition of seven modes based on size and solubility. The particle size is assumed to be distributed log-normally. The seven modes are categorized into four geometrical size classes, ranging from the nucleation, Aitken and accumulation modes to coarse modes. The aerosols are also divided into two types of internally mixed and water soluble particles (four modes), and externally mixed and insoluble particles (three modes). This classification makes possible the prediction of the hygroscopic properties of initially insoluble aerosol compounds which controls their atmospheric lifetimes and also their interactions with clouds. The WRF-HAM model includes the various microphysical processes of condensation of sulfuric acid, nucleation and new particle formation, coagulation of aerosol particles, and the thermodynamical equilibrium of aerosols with the water vapor. The main removal processes for the aerosol particles in the coupled WRF-HAM model are gravitational sedimentation and dry deposition. The model also considers the in-cloud scavenging of aerosol particles by precipitation within the convective cumulus clouds. The main global aerosol compounds including sulfate, black carbon, particulate organic carbon (POM), sea salt and mineral dust have been considered in this study. The emission fluxes of different aerosol compounds are based on the prescribed Emission Inventory for the Aerosol Model Inter-comparison Experiment B, AEROCOM representative for the year 2000. The simulations are carried out for a 6-day simulation period from 6 to 12 May 2006 over a domain with 30-km grid spacing, covering south-western Asia, North Africa and some parts of Europe. The diurnal variation of the simulated hourly PM10 mass concentration at Tehran is qualitatively close to the hourly observations made by the Air Quality Control Company (AQCC) of the Municipality of Tehran. The model captures diurnal cycle and the magnitude of the observed PM10 concentration during most of the simulation period. Coupling WRF model with HAM aerosol scheme improves the hourly PM10 mass concentration compared to the case where WRF was coupled with MADE scheme. A negative radiative forcing and cooling of the atmosphere are found mainly over the regions of high emission of mineral dust. The absorption of shortwave radiation by black carbon causes warming effects in some regions with positive radiative forcing. The inclusion of aerosol feedback in the shortwave radiation scheme improves the simulated daily mean shortwave radiation fluxes in Tehran. The difference between the simulated and observed mean daily downward shortwave radiation, temperature and surface pressure by the HAM model is smaller than by the aerosol MADE scheme. Compared to WRF-MADE, using the coupled WRF-HAM model improves the simulation of downward shortwave radiation by up to 40 Wm. The spatial variation in the simulated mean optical depth of aerosols at 500 nm wavelength by the WRF-HAM model is qualitatively close to the measurements by MODIS instrument. Furthermore, the comparison of the simulated aerosol optical depth by HAM and MADE aerosol schemes and the observations in Solar Village site of the global AERONET Network shows that the HAM model highly outperforms MADE.

Distinguishable amplitude phenomena on surface seismic data often resulted from contrasts in the elastic parameters of subsurface layers. Various techniques have been involved to analyze and highlight such phenomena for their potential use as "Direct Hydrocarbon Indicator (DHI)". More recently, other techniques have been developed based on the variation of reflection coefficient with angle of incidence, conventionally called Amplitude-Versus-Offset (AVO). During the last twenty years the significance of AVO analysis for studying seismic reflection in oil exploration has been considered more importantly. In this work, first, a seismic line from a gas field and also a well are selected to indicate the results of the application of AVO analysis for detection of hydrocarbon reservoir in this field. In this project, using well logs and information obtained by core analysis, a synthetic seismogram has been built applying Zoeppritz equation. And Using Hampson-Russell software, AVO attributes have been extracted from synthetic seismogram. Then anomalies of these attributes have been investigated and compared with the anomalies from AVO attributes which were extracted from real seismic data to characterize the reservoir. It has been seen that the extracted attributes of the synthetic seismogram confirm the anomalies from real seismic data. Finally according to the obtained result, observed anomalies can be interpreted as a Gas Cap for this reservoir. This study is useful to identify reservoir and nonreservoirs and the results of this study are considered as input for detailed reservoir studies. In particular, knowing the reservoir physical and saturating fluid properties is of great importance in making plans for developing the reservoir.

The deep internal structure of the crust can be determined using appropriate seismic and electromagnetic methods. The natural source magnetotelluric (MT) method is the most suitable electromagnetic technique for probing into the deep crust. A long period magnetotelluric data set obtained in the Southern Chilean Andes is investigated in this paper. Dimensionality analysis shows that the data may be regarded as with a strike 2D direction aligned to the N-S direction. Results of a joint inversion of different MT data types indicate relatively high conductive structures in the middle to deep crust beneath the volcanic arc.