Fatbox v2.0 - the Fault Analysis Toolbox: a python library for identification and geometric analysis of fault networks from numerical analogue, and digital elevation models

Résumé fourni par la source

Faults and fractures can be observed across vast spatial (nm to km) and temporal scales (years to Myrs), often evolving into highly complex networks. Once established, they fundamentally alter the rheological behavior and transportative properties of the host rock. This makes them a critical focus for applications such as seismic hazard assessment, geothermal reservoirs, and carbon storage. The architecture and evolution of fault networks can be studied using recent advances in remote sensing and modelling. Numerical models provide insight into both the top-view and depth expression of faults, while analogue models simulate geodynamic processes to shed light on their mechanics. Furthermore, the topography of natural faults can now be captured with unprecedented accuracy using Tandem-X radar satellites for example. However, the sheer data volume and the continued reliance on manual fault mapping remain major obstacles in fault network analysis. Here we present Fatbox v2.0, the Fault Analysis Toolbox. This python-based, open-source library is able to extract and characterize individual faults as well as entire fault networks from diverse datasets. Fatbox contains a large number of functions to map and analyze faults and fractures automatically from different types of observational data, geodynamic models and analogue models. Fault systems are described as 2D networks (graphs) using the coupling of nodes, defined by their position, and edges that connect the nodes. This allows us to capture the full complexity of natural fault and fracture systems. It is then possible to analyse features such as fault splays, intersections, and relay ramps, from topography, strain, strain rate, or model cross sections. In addition, the toolbox contains a number of functions to track faults through time, which is particularly useful for modelling data. This library is complemented by a wide range of functions that allow the geometry of the fault network to be filtered and analysed with high spatial resolution.

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