نوع مقاله : مقاله تحقیقی (پژوهشی)
1 موسسه ژئوفیزیک دانشگاه تهران، گروه ژئوفیزیک، تهران، ایران گروه ژئوفیزیک، دانشگاه صنعتی دلفت، دلفت، هلند
2 استادیار گروه زلزله شناسی، مؤسسه ژئوفیزیک، دانشگاه تهران، تهران، ایران
3 گروه ژئوفیزیک، دانشگاه صنعتی دلفت، دلفت، هلند
عنوان مقاله [English]
Seismic interferometry is a method that allows the retrieval of the seismic response at one receiver from a virtual source at the position of another receiver. In recent years, seismic interferometry has become a common tool in seismological studies. With continuous recording data in seismic stations, new opportunities are available to seismologists to present new hypotheses and studies. Continuous data contains ambient noise which has random amplitudes and phases and can propagate in all possible directions, so by using ambient noise, it is possible to retrieve responses between two seismic stations.
In most applications, long-duration vertical and horizontal components of continuous time series recorded at two stations are cross-correlated to approximate the Green’s function between the two stations. After stacking all available data for each station’s pairs, group velocity dispersion curves are measured using multiple-filter analysis for each EGF signal.
In our research, group velocity dispersion measurements are used for tomography. The radial anisotropy can be inferred from the Love–Rayleigh (L–R) discrepancy, that is, from the difference between the travelling speeds of horizontally and vertically polarized surface waves. Seismic anisotropy in the Earth’s crust is the signature of past and ongoing crustal deformation. Thus, observation of this anisotropy reflects the nature and distribution of the deformation bearing on the crustal rock. In conventional seismic tomography techniques, it is necessary to determine the dimensions of grids or other parameters such as smoothing and damping. A two-step inversion algorithm is employed to solve the tomographic inverse problem. In this study, transdimensional tomography is applied, which adapts to a non-uniform data coverage without requiring any arbitrary regularization such as damping or smoothing. It is a one-step non-linear tomographic algorithm. The algorithm is rooted in a Bayesian framework using Markov chains with reversible jumps. The study area in this research is the Central Alborz area (latitude 34.5-38 N degrees and longitude 48.5-54.5 E degrees). We process all available contentious vertical and horizontal seismic data from the Iranian Seismological Center (IRSC) and the International Institute of Earthquake Engineering and Seismology (IIEES) in this region for the three years from 2013 through 2016. Also, we use data from earthquakes with magnitude above 3.5, which were recorded on these stations between 2006 and 2016.
The results obtained from seismic tomography and radial anisotropy show the possibility of separation between different tectonic seismic regions based on the velocity anomalies and radial anisotropy. Moreover, radial anisotropy shows the cooled Damavand magma at a depth of about 20 km.