# The First Seismic Imaging of the Holy Cross Fault in the Lysogory Region, Poland
## 4 Seismic Data Analysis
Amplitude recovery is then applied to mitigate the effects of geometric spreading, ensuring that different types of noise across deeper sections of the seismic data are fully visible (as illustrated in Figure 4) prior to noise attenuation [34]. Manual picking of the first refraction arrivals for all 155 shot gathers resulted in over 9000 travel times. Refractions were clearly visible for all offsets (see Figure 4) reaching 300 m. A simple one layer starting model with 1D velocity gradient and precise differential GPS-based elevation was created using an average refraction velocity from picked travel times. Tomography was calculated using a JIVE3D code [35; 36], resulting in good convergence without losing any data. This tomography code uses a ray-tracing approximation for seismic energy propagation and linearized iterative inversion to optimize the travel time difference between calculated and observed times. To stabilize the inversion, a typical regularization factor is used that is balancing the smoothness of the model and data misfit. The whole calculation took about 2 h on a standard PC. The final P-wave velocity field is presented in (Figure 5 top), where the result is masked with an area not covered with any seismic rays. The results with small uncertainty resulting from a large number of crossing seismic rays, thus well-documented velocities, are visible down to 70 m below the surface. The deeper areas with larger uncertainties are recognized to the maximum depth of 150 m. Most details are visible in the shallow subsurface. To visualize them, a perturbation model (see Figure 5 bottom) was calculated as a difference between the final tomography model and its smoothed version. The largest variation is observed at the distance of the first 150 m, in the middle of the profile at 350 m, and further North at 650 m. Those areas mark strong horizontal variations that indicate fractured and diversified zones. The vertical resolution of tomographic models is not good enough to estimate the dip of the faults, nor to estimate the structures deeper than 70 m.  
No single method can eliminate all noise types in seismic data; the effectiveness of noise suppression depends significantly on the choice of suppression technique and the domain in which it is applied. Initially, an FK filter was used to attenuate linearly correlated noise, including linear direct and ground roll noise. This was followed by Tau-P muting as a secondary noise attenuation step to eliminate remaining linear noise, such as refractions and guided waves [37]. Velocity analysis, a critical component of seismic processing, is essential for accurately identifying rock types, amplitude compensation, stacking, migration, and depth conversion. Post-stack migration was applied to horizontally align dipping events, and depth conversion ensured accurate vertical positioning of seismic events [38]. Figure 4: Shot gathers illustrating various recorded waveform types with red lines indicating geometry integrity. The first breaks are easily visible at all offsets. Rich wavefield including S waves and surface waves is visible for the whole record. Notably, the applied seismic processing workflow involves a series of optimized steps (as described in Table 1), leading to a substantial enhancement in the amplitude spectrum, contributing to improved data clarity and interpretability for the subsurface image. Quality control (QC) procedures were conducted after each processing step to assess process effectiveness and detect potential errors. Seismic processing is a fundamental aspect of geophysical investigations, enabling the transformation of raw seismic data into high-resolution subsurface images essential for fault and structural analysis. Key methodologies, including multi noise attenuation techniques, velocity analysis, static corrections, deconvolution, and migration, are applied to achieve precise spatial and temporal positioning of geological structures and ensure accurate delineation of subsurface features.