Abstract
To investigate the subsurface geometry of a recently discovered, seismically active fault in the Ventura basin, southern California, USA, we present a series of cross sections and a new three-dimensional fault model across the Southern San Cayetano fault (SSCF) based on integration of surface data with petroleum industry well log data. Additionally, the fault model for the SSCF, along with models of other regional faults extracted from the Southern California Earthquake Center three-dimensional Community Fault Model, are incorporated in static Coulomb stress modeling to investigate static Coulomb stress transfer between thrust faults with complex geometry and to further our understanding of stress transfer in the Ventura basin. The results of the subsurface well investigation provide evidence for a low-angle SSCF that dips ~15° north and connects with the western section of the San Cayetano fault around 1.5–3.5 km depth. We interpret the results of static Coulomb stress models to partly explain contrasting geomorphic expression between different sections of the San Cayetano fault and a potential mismatch in timings between large-magnitude uplift events suggested by paleoseismic studies on the Pitas Point, Ventura, and San Cayetano faults. In addition to new insights into the structure and potential rupture hazard of a recently discovered active reverse fault in a highly populated area of southern California, this study provides a simple method to model static Coulomb stress transfer on complex geometry faults in fold and thrust belts.
Original language | English (US) |
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Article number | e2020JB019539 |
Journal | Journal of Geophysical Research: Solid Earth |
Volume | 125 |
Issue number | 7 |
DOIs | |
State | Published - Jul 1 2020 |
Keywords
- Southern San Cayetano fault
- Ventura basin
- multifault ruptures
- seismic hazard
- static Coulomb stress transfer
- thrust faults
ASJC Scopus subject areas
- Geophysics
- Geochemistry and Petrology
- Earth and Planetary Sciences (miscellaneous)
- Space and Planetary Science