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Preseismic velocity changes observed from active source monitoring at the Parkfield SAFOD drill site

Author

Listed:
  • Fenglin Niu

    (MS-126, Rice University, 6100 Main Street, Houston, Texas 77005, USA)

  • Paul G. Silver

    (Carnegie Institution of Washington, 5241 Broad Branch Road, NW, Washington DC 20015, USA)

  • Thomas M. Daley

    (Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, California 94720, USA)

  • Xin Cheng

    (MS-126, Rice University, 6100 Main Street, Houston, Texas 77005, USA)

  • Ernest L. Majer

    (Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, California 94720, USA)

Abstract

Stress in a fault zone The time-varying stress field at seismogenic depth is a critical parameter for understanding earthquake triggering. As a result, measuring stress changes within seismically active fault zones has been a long-sought goal of seismology. By continuously measuring in situ seismic velocity changes along a base-line between the SAFOD (San Andreas Fault Observatory at Depth) pilot and main drill holes in Parkfield at 1 km depth for two months, Niu et al. find that stress changes induced by variations in barometric pressure are indeed detectable. They also found velocity changes coincident with two earthquakes that were predicted to produce large coseismic stress changes. The two excursions started about 10 and 2 hours before the events, respectively, suggesting that they may be related to pre-rupture dilatancy similar to that observed in early laboratory studies.

Suggested Citation

  • Fenglin Niu & Paul G. Silver & Thomas M. Daley & Xin Cheng & Ernest L. Majer, 2008. "Preseismic velocity changes observed from active source monitoring at the Parkfield SAFOD drill site," Nature, Nature, vol. 454(7201), pages 204-208, July.
    • Handle: RePEc:nat:nature:v:454:y:2008:i:7201:d:10.1038_nature07111
    DOI: 10.1038/nature07111
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    Cited by:

    1. Prabhav Borate & Jacques Rivière & Chris Marone & Ankur Mali & Daniel Kifer & Parisa Shokouhi, 2023. "Using a physics-informed neural network and fault zone acoustic monitoring to predict lab earthquakes," Nature Communications, Nature, vol. 14(1), pages 1-12, December.

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