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Data · dataset · 2026

Sonic Log LAS Files from offshore exploration wells in the middle and southern Adriatic Sea (Italy), derived from the ViDEPI Project

Listed in Teesside University Research Data Repository

This dataset consists of twelve Log ASCII Standard (LAS v2.0) files, one for each offshore exploration well in the middle and southern Adriatic Sea (Southeastern Italy), namely Branzino-1, Chiara-1, Cristina-1, Famoso-1, Giove-1, Giove-2, Grazia-1, Grifone-1, Medusa-1, Sabrina-1, Simona-1, and Sparviero-1bis.

Description

The files were exported from Petrel™ and are provided in a standardised ASCII format commonly used for the exchange and reuse of well-log data across geoscientific software platforms.

The compilation was motivated by the need to render legacy offshore well-log information reusable in quantitative workflows. Sonic log data for each well were originally available only as raster log images distributed through the ViDEPI project (www.videpi.com) and were digitised by Cicala et al. (2023), who released the extracted depth–interval transit time (Δt) pairs as tabulated CSV files. Building on that work, this dataset delivers LAS v2.0 files that combine well metadata with depth-referenced sonic curves.

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The curves provided in each file are: depth (Dept, m), average P-wave velocity (vav, m/s), interval transit time (Δt, μs/ft), and average interval transit time (Δtav, μs/ft). In each file, these values are stored in the Ascii data section, preceded by standard header blocks reporting key well information (e.g., name, WGS84 coordinates, depth limits, logging date, ownership) and curve definitions. The dataset is designed to support seismic velocity analysis, time–depth conversion, and subsurface interpretation, and to facilitate comparison with other well-based or regional velocity datasets derived from legacy exploration data.

Data processing and analysis were carried out with SLB Petrel © interpretation software under academic licenses to University of Bari Aldo Moro, Department of Earth and Geoenvironmental Sciences.

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