1,2,- 1Utrecht University, Faculty of Geosciences, Department of Earth Sciences, Utrecht, Netherlands (r.e.rizzo@uu.nl)
- 2University of Edinburgh, School of GeoSciences, Edinburgh, United Kingdom
- 3University of Aberdeen, School of Geosciences, Aberdeen, United Kingdom
- 4VRGeoscience Ltd, Manchester, United Kingdom
- 5INTERA Geosciences UK Ltd, London, United Kingdom
- 6University of Leeds, School of Earth, Environment & Sustainability, Geosolutions Leeds, Leeds, United Kingdom
Accurate quantification of the subsurface stress state, and of its resolved components on faults and fractures, is critical for de-risking applications ranging from geothermal energy and subsurface storage to nuclear waste disposal. While the governing mechanics are well established—reactivation depends on resolved normal and shear stresses, pore-fluid pressure, and frictional resistance—practical barriers remain to accessible, reproducible tools for 3D stress-state visualisation and systematic evaluation of stress–structure interactions.
We present PyFracTend, an open-source Python implementation of the MATLAB-based workflow developed by Stephens et al. (2018), packaged with a cross-platform graphical user interface (GUI) to support reproducible analysis in both research and applied workflows. PyFracTend takes as input principal stress magnitudes and orientations (3D), pore-fluid pressure, and fault/fracture orientation datasets (azimuth and dip), together with user-defined mechanical parameters (e.g., coefficient of friction and cohesion, where applicable). The toolbox computes commonly used stability indicators—including slip tendency, dilation tendency, and related measures—and visualises results on stereonets and Mohr diagrams. All inputs and outputs are exported as analysis-ready tables, enabling straightforward integration with third-party software and downstream modelling.
To ensure consistency with established practice, we benchmark PyFracTend against the original MATLAB implementation, demonstrating agreement across representative stress states and discontinuity datasets. Finally, responding to the growing need for uncertainty-aware stress characterisation, PyFracTend integrates seamlessly with the pfs Python code (Healy & Hicks, 2022) for uncertainty quantification (e.g., Monte Carlo sampling of stress tensor parameters), thereby propagating stress uncertainties into probabilistic fault/fracture stability metrics.
References:
Stephens, T. L., Walker, R. J., Healy, D., Bubeck, A., & England, R. W. (2018). Solid Earth, 9, 847–858.
Healy, D. and Hicks, S. P. (2022). Solid Earth, 13, 15–39.
How to cite: Rizzo, R. E., Burnham, B., Benitez Cunha, G., and Healy, D.: PyFracTend: an Accessible Tool for 3D Stress-State Visualisation and Fault/Fracture Stability Assessment, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19338, https://doi.org/10.5194/egusphere-egu26-19338, 2026.
