## 1 Introduction  
Imaging of geological complex structures in the subsurface can be used for geotechnical site characterization by geophysical methods. The term 'complex' is used for those subsurface earth models which cannot be easily imaged by conventional seismic imaging methods due to their complex velocity structures or geometry. Examples of complex structures can be steep dipping beds, intensive faulted or folded media, and earth models with strong velocity changes. In addition, the near-surface velocity anomalies can increase complexity of imaging problems, mostly due to the complexity in the simulation of the seismic wave propagation, or in other words, the complication caused by the propagation of the body waves through the complex near-surface layers [1]. The most realistic of such situations is the near-surface salt layers which can or cannot play a role as the caprock for petroleum reservoirs. In those cases, the fluids trapped in the layers beneath the salt have considerable effects on the elastic properties of the subsurface media. The better these properties are modeled, the more accurate an image of the subsurface will be obtained. Conventional seismic imaging methods are no more reliable in solving imaging problems raised from complex geological media. High quality seismic imaging is needed in most exploration studies such as gas storage projects, geological hazard, CO2 storage projects in target finding and monitoring, and also in geothermal resources. To obtain a high-quality seismic image, further investigation of obstacles to obtaining reasonable seismic images and developing reliable imaging methods are required. Considering the problems of seismic imaging in complex media, it was stated that poor seismic images from different regions mostly resulted from the application of inappropriate imaging algorithms [2]. The minor concerns were related to the data acquisition problems due to harsh topography, but the major issues are rooted in extreme complexity in subsurface media and poor quality in signal to noise ratio (SNR) [3]. The former could be resolved by adequate acquisition; however, the later requires deep investigation on developing proper imaging tools. In one study, it was proposed resolving obstacle partially by the common reflection surface (CRS) and the normal incidence point (NIP) tomography method [4]. However, the CRS still suffers in handling strong lateral velocity changes or geologically complicated media [5]. The reverse time migration (RTM) and the full waveform inversion (FWI) methods, as the latest introduced methods, deal with a vast majority of problems in seismic imaging [6; 7]. However, these methods are still present issues in application to large field datasets, poor quality data with shortage in frequency content, and low SNR in the low frequency part of the data [8]. Challenges for FWI land applications consist of addressing the wavefield propagation from rough topography, low SNR of the low-frequency data, and determination of an appropriate source wavelet throughout the iterations by improving the velocities and model parameters [9]. The FWI employs an iterative procedure that is based on a forward modeling and inversion procedure to find the optimal parameters [10; 11]. Some studies have been carried out to show the efficiency of FWI in the imaging of complex media [7], presented the application of the FWI method in the frequency domain on the wide-aperture onshore seismic data with a complex geological setting (thrust belt) [12], and applied the elastic frequency-domain FWI to the synthetic onshore Marmousi2 model [13]. They implemented a velocity-gradient starting model and a very low starting frequency to image the complex structure model. Reference [14] also tested the application of this strategy to the offshore versions of the synthetic Marmousi2 model. They successfully imaged the complex model using their strategy.