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Throw rate acceleration caused by dip-linkage on normal faults
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Abstract
Areas of crustal extension often contain pre-existing structures that can reactivate or influence the geometry and growth of new, overlying faults. As strain accumulates, it is well know that new faults may link down-dip with pre-existing faults. Such linkage invariably leads to an increase in fault surface area, which is empirically linked to increasing seismic hazard. However, the timescales over which this linkage may occur, and its effects on throw-rate evolution and related seismic hazard, are poorly constrained. We use high-resolution 3D seismic reflection and borehole data from offshore NW Australia to investigate the growth and throw-rate evolution of two normal faults. By mapping age-constrained seismic horizons and constructing throw-length and -distance plots we show evidence of growth via dip-linkage, along all or part of their mapped length. We find that linkage did not occur simultaneously along the fault, but over a protracted period especially near fault tips. The absolute timing of fault linkage is influenced by the total throw on the pre-existing fault, throw accumulation rates during subsequent rifting, position along the fault, and the intervening stratigraphic thickness. Progressive dip-linkage increases fault surface area and is associated with an increase in throw-rate on linked segments. Given these effects on fault geometry and displacement patterns, we argue that dip-linkage should be integrated into fault growth models and considered in seismic hazard assessments in rifted regions with inherited structures.
DOI
https://doi.org/10.31223/X59J2G
Subjects
Tectonics and Structure
Keywords
normal fault, rifting, Structural inheritance, fault reactivation, throw-rate
Dates
Published: 2025-11-28 06:47
Last Updated: 2025-11-28 06:47
License
CC BY Attribution 4.0 International
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Conflict of interest statement:
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The authors further declare that no generative artificial intelligence (AI) tools were used in the preparation, writing, analysis, or editing of this manuscript. All work is entirely the authors’ own.
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