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Quantitative analysis of normal fault network evolution

Understanding how normal fault networks initiate and evolve is important for quantifying plate boundary deformation, assessing seismic hazard and finding natural resources. State-of-the-art numerical forward models treat faults as finite-width shear zones, not as discrete entities. To better understand fault system dynamics over geological scales, we develop workflows to isolate individual faults and their role in shaping the fault network.

We present 3D numerical rift models of moderately oblique extension using the ASPECT software. These models reproduce the thermo-mechanical behavior of Earth's lithosphere and simulate fault system dynamics from inception to breakup accounting for visco-plastic rheology, strain softening and surface processes. We extract surficial fault systems as a hierarchical, time-dependent 2D network of nodes, edges and components representing individual faults.

We find that the initial fault network forms through rapid fault growth and linkage, followed by competition between neighboring faults that leads to their coalescence into a stable network. At this point, modelled normal faults continue to accumulate displacement but do not grow any longer. As deformation localizes towards the center of the rift, the initial border faults shrink and disintegrate, being replaced by new faults in the center of the rift. The longevity of faulting is thereby controlled by crustal rheology and surface process efficiency. Quantitative analysis of fault evolution allows us to deduce fault growth and linkage as well as fault tip retreat and disintegration in unprecedented detail.


Sascha Brune1, Thilo Wrona2, Pauline Gayrin1, Derek Neuharth3, Anne Glerum2, John Naliboff4, Esther Heckenbach1
1Geodynamic Modelling Section, GFZ Potsdam, Germany;Institute of Geosciences, University of Potsdam, Germany; 2Geodynamic Modelling Section, GFZ Potsdam, Germany; 3Department of Earth Sciences, ETH Zürich, Switzerland; 4Department of Earth and Environmental Science, New Mexico Institute of Mining and Technology, Socorro, NM, USA
GeoBerlin 2023