4.5 Article

On the Viability of Using Autonomous Three-Component Nodal Geophones to Calculate Teleseismic Ps Receiver Functions with an Application to Old Faithful, Yellowstone

Journal

SEISMOLOGICAL RESEARCH LETTERS
Volume 88, Issue 5, Pages 1268-1278

Publisher

SEISMOLOGICAL SOC AMER
DOI: 10.1785/0220170051

Keywords

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Funding

  1. National Science Foundation (NSF) [CyberSEES-1442665]
  2. King Abdullah University of Science and Technology (KAUST) [OCRF-2014-CRG3-2300]
  3. U.S. Department of Energy, Geothermal Technologies Office [DE-EE0007080]
  4. Brinson Foundation
  5. Carrico Fund
  6. NSF [EAR-0350028, EAR-0732947]
  7. University of Utah
  8. Division of Computing and Communication Foundations
  9. Direct For Computer & Info Scie & Enginr [1442665] Funding Source: National Science Foundation

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Recent advances in seismic data-acquisition technology paired with an increasing interest from the academic passive source seismological community have opened up new scientific targets and imaging possibilities, often referred to as Large-N experiments (large number of instruments). The success of these and other deployments has motivated individual researchers, as well as the larger seismological community, to invest in the next generation of nodal geophones. Although the new instruments have battery life and bandwidth limitations compared to broadband instruments, the relatively low deployment and procurement cost of these new nodal geophones provides an additional novel tool for researchers. Here, we explore the viability of using autonomous three-component nodal geophones to calculate teleseismic Ps receiver functions by comparison of co-located broadband stations and highlight some potential advantages with a dense nodal array deployed around the Upper Geyser basin in Yellowstone National Park. Two key findings from this example include (1) very dense nodal arrays can be used to image small-scale features in the shallow crust that typical broadband station spacing would alias, and (2) nodal arrays with a larger footprint could be used to image deeper features with greater or equal detail as typical broadband deployments but at a reduced deployment cost.

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