The mixture of natural and artificial seismic sources with random distributions cause diffuse wave field with random amplitudes and phases called noise. When noise is analyzed in a long-term process, it contains surface waves which are spread in all directions. Thus, ambient noise contains data relevant to the surface waves. In recent years, as broadband seismic networks have been distributed vastly around the world, diffuse wave fields are utilized to obtain surface waves. The data of the fields are recorded in the forms of seismic ambient noise and waveforms. Seismic waveform is created as a result of multiple diffuse seismic waves of heterogeneous areas, while seismic ambient noise is caused by many types of sources such as ocean microseisms , atmospheric turbulences (Tanimoto, 1999), storms, volcano erroptions and so on. Recent studies suggest that surface waves extracted from diffuse wave fields and seismic waveforms are according to the Green function (Wapenaar, 2004) .Although, the horizontal to vertical spectral ratio technique of microtremor measurement is widely applied in microzonation and site response studies during past two dacays. but the goal of this kind of geotchnical studies is different from seismologcal noise investigations.
For the first time, Campillo and Paul (2003) have calculated group velocity of Rayleigh and Love surface waves from waveforms of 101 teleseismic earthquakes recorded in the national Mexican seismic network. After that investigation of ambient noise for Green function analysis have been continued by means of Shapiro and Campillo (2004; 2005) ؛ Schuster et al., (2004) ؛ Snieder (2004)؛ Bensen et al.(2007) ; Wapenaar et al.(2013)؛ Javan and Movaghari (1392). They showed it is possible to get the Green function between stations through calculating Cross Correlation Function of recorded noise. Characteristics of seismic ambient noise are independent of occurring earthquake. That’s why ambient noise is used widely and provides the opportunity to do imaging without a source, or passive imaging in order to study crustal structure between two stations. More applications include terrestrial and solar seismology, underwater acoustics, and structural health monitoring (Larose et al., 2008).
In this article, we are going to compare velocity structure created by surface waves of ambient noise and earthquake surface waves based on waveforms from IIEES broadband seismic stations. Braod band seismic stations are usually installed in quiet locations some distance from significant sources of cultural noise, such as roads, railroads, and machinery. We analyze seismic noise using continuous 50 sample/s from one year data. Using recorded ambient noise in Tabas, Sharakht (Qaenat), Zahedan, Chabahar, and Bandar Abbas broadband seismic stations, the Green function of surface waves between each pair station was obtained by cross correlation technique and dispersion curve was calculated through frequency-time analysis. According to this curve, a 1-D model of velocity structure between two stations was presented. There has been a comparison between this model and the one acquired from May 11, 2013 earthquake occurred in the north of Jask at the south of Iran. The results show that we can use the ambient noise to study crustal velocity structure and upper mantle as well. Therefore, it is necessary to record ambient noise continuously in seismic stations so as to prepare fundamental research in seismology.