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In recent decades, geological modeling has significantly evolved, relying on the growing potential of hardware and software to manage and integrate vast datasets of 2D-3D geophysical underground data. Therefore, digitization and integration with other forms of data can often improve understanding of geological systems, even when using so-called vintage or historical data. Seismic reflection data have been extensively acquired mainly for hydrocarbon exploration since the 60s generating large volumes of data. Typically, these data have been for private commercial use and are relatively unavailable for research. However, with time, large volumes of vintage seismic reflection data in many countries worldwide are now becoming publicly available through time-based de-classification schemes. Such data have a great potential for modern-day geo-research, unleashing opportunities to improve geological understanding through re-interpretation with modern methods. However, a downside of these vintage data is that they are often only available in analog (paper, raster) format. The vectorization of these data then constitutes an essential step for unlocking their research potential. In 2018 INGV established the SISMOLAB-3D infrastructure, which is mainly devoted to analyzing digital subsurface data, such as seismic reflection profiles and well-logs, to build 2D-3D geological models, principally for seismotectonics, seismic hazard assessment, and geo-resources applications. In this contribution, we discuss the robustness of the WIGGLE2SEGY code, firstly published by Sopher in 2018, focusing on examples from different tectonic and geodynamic …