# Seismic Exploration Methods for Structural Studies and for Active Fault Characterization: A Review
## 3 Developments in Seismic Imaging
### Full-Waveform Inversion  
Full-Waveform Inversion (FWI) has gained increasing popularity in the recent years. Differently from seismic ray tomography, FWI utilizes the entire seismic wavefield to generate high-resolution images of the subsurface, providing greater details about the physical properties of the subsurface. FWI is an iterative inversion technique that seeks to minimize the difference between observed and synthetic wavefields by iteratively updating the model parameters [26]. FWI typically involves several key steps which are similar to those of seismic ray tomography. First, an initial model of the subsurface is created based on existing data and geological knowledge. Next, synthetic wavefields are modeled into the initial model, and the resulting waveforms are compared with the recorded data. The differences between the observed and synthetic data are then minimized by updating the initial model parameters. Steps two and three are applied iteratively until an optimal match between synthetic and recorded waveforms is achieved [26]. When the method works, it provides high-resolution images of the subsurface, higher than those from seismic ray tomography, therefore adding valuable insights for the interpretation. One of the challenges of FWI lies in its computational intensity, as the method involves the inversion of the entire seismic wavefield. To overcome this challenge, various techniques have been proposed, such as using gradient-based optimization methods [26]. In addition, constructing a reliable initial model for FWI continues to be a pressing concern, as controlled-source experiments cannot yet capture very low frequencies, which are  
Figure 2: Short-wavelength FAT of a profile crossing Paganica Fault, source of the Mw 6.1 Aquila in central Italy with interpretation (from [PERSON] et al. [42]). The white dashed line indicates the top of the inferred pre-Quaternary basement. The main fault zones are represented with dashed lines. Red arrows indicate the projection of the main outcropping faults. Black arrows indicate the coseismic surface breaks. Faults are identified by imaging the associated alluvial wedges, which are seen as low-velocity zones in the tomogram. needed to provide a reliable estimate of the initial model [44]. The accuracy of results is heavily influenced by the initial model, as they depend on inversion non-uniqueness and local-search optimization techniques. In the case of near-surface FWI, the starting model's dependence can be especially problematic due to the complicated nature of the recorded seismic wavefield (i.e., a combination of surface waves and body waves) and the possibility of significant heterogeneity over short distances, see [PERSON] et al. [45]. In the quest for developing a suitable starting model for FWI, various approaches have been explored. One such approach, commonly employed in the oil and gas exploration industry, involves the integration of reflection tomography and migration-based velocity analysis, as described by [PERSON] et al. [46]. An alternative method, which offers a more automated and FWI-oriented approach to constructing accurate starting models, uses first-arrival traveltime tomography [30]. Additionally, another promising option to tackle this challenge in near-surface environments involves the use of neural networks to build initial models specifically fitted for 2D elastic FWI (e.g., [28; 47; 48]). Due to the complexity of the near-surface, FWI has primarily been utilized to study subsurface structures on a larger scale. For instance, in a study by [PERSON] et al. [49], FWI was implemented for a seismic investigation of the eastern Nankai subduction system (Japan) at a crustal scale, using dense ocean bottom seismic data. By adopting this method, [PERSON] et al. [49] were able to accurately quantify seismic velocities to an unprecedented degree of resolution (Figure 3). Their findings indicate the presence of compressive tectonic features within both the subducting oceanic crust and the backstop. Furthermore, [PERSON] et al.