N Afsari; F Taghizadeh-Farahmand; M.R Ghassemi
Abstract
The AlborzMountains are part of the Alpine-Himalayan orogenic belt, situated to the south of the Caspian Sea and north of the Central Iran. . The region is undergoing extensive crustal deformation and shortening between the north-central Iran and the rigid SouthCaspianBasin crust. In this study, we used ...
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The AlborzMountains are part of the Alpine-Himalayan orogenic belt, situated to the south of the Caspian Sea and north of the Central Iran. . The region is undergoing extensive crustal deformation and shortening between the north-central Iran and the rigid SouthCaspianBasin crust. In this study, we used the P-wave receiver function modeling to investigate the crustal structure beneath the eastern part of the AlborzMountains from data recorded between 2004-2010 in Sari and Semnan seismic networks of short-period seismographs, permanently deployed across the area. We observed clear conversions (Ps) from the Moho boundary, and we used them to define a model for the crust of the eastern Alborz. Our analysis indicates a thickening of the crust from ~51±2 km beneath the northern part of the eastern Alborz to ~62±2 km beneath the central part of the region, then a thinning of the crust to ~52±2 km towards south of the eastern Alborz Mountains.
A.R. Arab-Amiri; A. Moradzadeh; D. Rajabi; N. Fathianpour; B. Siemon
Abstract
Today Helicopter-borne electromagnetic (HEM) data survey play important role for high resolution and fast 3D mapping of resistivity structures within the vast area. The standard method of interpretation of these data is to inverse them frequently. As surveying system is not fixed during the survey, hence ...
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Today Helicopter-borne electromagnetic (HEM) data survey play important role for high resolution and fast 3D mapping of resistivity structures within the vast area. The standard method of interpretation of these data is to inverse them frequently. As surveying system is not fixed during the survey, hence noise is accompanying the measured data. To process the measured noisy data they are fed into the several filters to get better data to be used for modeling. During the filtering stage some of signals are also lost. Therefore, it is required to choose modeling techniques that has minimum error and provide accurate subsurface model. In this paper, first the response of the three synthetic layered earth models were calculated by using three different Hankel transform forward modeling methods. Then with adding different percents of random noise to the synthetic data, they were modeled inversely by different methods. The obtained results indicate that the so-called improved Guptasarma-Singh inverse modeling method could provide better responses for all three synthetic models.