stratapy: a Novel Tool for Automated Stratigraphic Log Visualisation

Stratigraphic logs are the fundamental interface between geological observation and scientific interpretation. They are a crucial tool which enables scientists to transform field observations of outcrops or boreholes into a graphical representation. Despite their importance, the creation of these logs is a significant bottleneck in geological workflows and lack reproducibility. Manual digitisation of logs can be an extremely time-consuming and tedious process, and often results in highly specialised outputs that are not easily understood between different geoscience communities. The limited range of existing tools for digitisation of stratigraphic logs are typically tailored to specific fields and applications, with many unable to provide core functions such as automatic legend creation, and commonly involve a steep learning curve for the user.

We present stratapy: a new Python package which we have developed to be an accessible tool for rapid, high-quality log digitisation. The package enables scientists across a range of disciplines within the geosciences (e.g., sedimentology, geology and volcanology) to efficiently generate publication-quality stratigraphic logs with basic text- or spreadsheet-based inputs, from three lines of code. The package caters to non-programmers while being highly customisable in both style and function, incorporating standardised lithological patterns and curated geological features and symbols. Easy to change parameters (e.g. grain-size axes, legend configuration) enable more tailored visualisation of logs for a multidisciplinary audience. Furthermore, automatic correlation with the chronostratigraphic column and precise sample location markers, as well as built-in multi-panel visualisation and stratigraphically correlated logs provides enhanced functionality for more complex figures.

With applications in research, industry and education & outreach, stratapy creates a standardised framework for log illustration and digitisation, streamlining scientific workflows, improving the quality of stratigraphic logs, and contributing towards improved uptake of digital practices in the geosciences.