JOURNAL OF RESEARCH ON APPLIED GEOPHYSICS
Year:2017 | Volume:2 | Issue:2 |Papers Count:6

Geophysical methods can effectively be used for delineation and maintenance of man-made subsurface installations. These installations are suitable targets for detection by ground penetrating radar (GPR) method. In this non-invasive method, high frequency electromagnetic (EM) waves in the frequency range 10 to 1000 MHz are used for detection, demonstration and investigation of shallow subsurface structures. The most important advantage of this method over other geophysical methods its high resolution, high speed of survey and nondestructiveness. In urban areas where the ground surface is covered by asphalt and also noise level is high, it not possible to use other geophysical methods while obtain high resolution data without destruction of the asphalt. However, the GPR method with shielded antenna acts well in urban areas. This method can present a three-dimensional (3-D) picture from the subsurface in which an accurate estimation of the subsurface structures can be made. In this method, EM waves, generated by the GPR transmitter, are sent into the ground and the reflections from the subsurface structures are received by the GPR receiver. The GPR waves are intensively attenuated in high conductive subsurface media and hence, the depth of penetration of GPR waves in this method is limited. In this research work, the depth of penetration of the GPR waves in the study area decreases to less than 2 meters. In this research, an urban survey area where various metallic and non-metallic pipes have been buried is selected, and then, GPR survey is performed on a grid in the area. As a result of processing and interpretation of the acquired GPR data, the subsurface targets at different depths are detected with relatively good accuracy and resolution....

The conventional velocity analysis sums the amplitudes of events along hyperbolic trajectories and converges the energy in the corresponding intercept time and slowness or velocity. This makes the velocity analysis as one of the most time consuming seismic data processing steps. On the other hand, this algorithm suffers from low resolution due to several reasons. In this paper, we use the Butterfly algorithm to calculate the forward and adjoint operators of the hyperbolic Radon transform in a much faster way, compared to the conventional integration in the time domain. Moreover, by applying it to fast iterative shrinkage-thresholding algorithm (FISTA), a high-resolution velocity panel is obtained.

In this study, crustal velocity structure beneath two broadband seismic stations of Iran National Seismic Network (INSN), Ashtian-Arak (ASAO) and Naein (NASN) located in northwest of the Central Iran seimotectonic zone near the Ashtian and Nain cities have been investigated by joint inversion of P receiver function and of Rayleigh wave phase and group velocity dispersion curves. To determine the receiver functions, we have used iterative deconvolution in time domain proposed by Ligorria and Ammon (1999). which is more stable with noisy data in comparison to frequency domain. The fundamental mode Rayleigh wave group and phase velocities dispersion curves have been provided by the study of Rahimi et al. (2014) on the structure of crust and upper mantle of the Iranian Plateau for the period interval of 10-100 sec. The result of this study suggests that Moho discontinuity depth beneath Ashtian-Arak station (ASAO is 50 ± 2 km and beneath Naein station (NASN), it is 56 ± 2 km. Relative high crustal thickness beneath NASN station in comparison to other regions of central Iran can be attributed to abut the region to the Sanandaj– Sirjan zone (SSZ) and Urumieh– Dokhtar magmatic assemblage (UDMA). It can also attributed to the existence of thick Magma masses in Urumieh– Dokhtar magmatic assemblage and increase of the density and relative thickness of the area based on the isostasy theory. The average Moho depth in northwest edge of Central Iran is 53 ± 2 km.

We present a formula for computing the horizontal and vertical gravitational anomalies due to an arbitrary n-sided polygon in a two-dimensional (2D) space with a linear density variation in horizontal and vertical directions. In the analysis of gravity data over thick sedimentary basins or lithospheric scale studies, density contrast can sometimes be approximated by a continuous function decreasing or increasing linearly with depth. We developed a MATLAB code to calculate the gravitational anomaly of an n-sided polygon having linear density variation and compare the anomaly with that of a same n-sided polygon having mean constant density. There is a significant difference in the amount of anomalies that cannot be ignored.

Magnetic and gravity geophysical survey methods are mainly used in preliminary stages of exploration activities to achieve a general structural image of the area, and consequently, to obtain information as a basis for future exploratory stages. One of the most important issues in the interpretation of gravity and magnetic data is to use modeling methods in order to accurately identify subsurface structures. One of the procedures in modeling process is the inversion of gravity and magnetic data. In general, the inversion of geophysical data reveals two sets of parameters, namely physical and geometric parameters, for each of the subsurface structures. Inverse modeling of the acquired gravity and magnetic data have been used to identify the mass of salt in Garmsar area. In this regard, first, the results of inverse modeling of both sets of gravity and magnetic data have been compared, and then, combined inverse modeling of the data has been made. Based on the results of this study, a combination of magnetic and gravity data inversion using appropriate weighted coefficients is recommended....

In seismic data processing, the processing steps are completely affected by the data quality. Reflection seismic data are often affected by various noises including random and coherent noises. Low signal to noise ratio can produce problems for stacking and migration steps, which ultimately leads to poor interpretation. There are many methods that can be used for noise removal or attenuation of seismic data. The basic assumption of the Fourier transform is that it considers stationary signal, thus, for non-stationary signals, it is not always applicable. Based on this fact that the wavelet transform decomposes a function by translation and stretching, it can provide time-scale representation of a signal. In this paper, we have used SURE-LET method for noise removal in the wavelet transform domain. In the SURE-LET method, any assumptions of noise free signals are avoided.