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Imaging the Subsurface with Ambient Noise Autocorrelations

Clayton, Robert W. (2020) Imaging the Subsurface with Ambient Noise Autocorrelations. Seismological Research Letters, 91 (2A). pp. 930-935. ISSN 0895-0695. https://resolver.caltech.edu/CaltechAUTHORS:20200506-132126128

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Abstract

Autocorrelations created by stacks of near‐offset traces from virtual source gathers are used to form an image of the deeper subsurface. We minimize the masking effects of the effective source time function by subtracting the survey‐wide average autocorrelation from each trace. The result is a zero‐offset reflection image of the subsurface generated by ambient noise correlation. The technique can be particularly useful for imaging the mid and lower crust, in which traditional seismic methods have penetration problems. We show examples from a one‐component 3D survey and a three‐component 2D profile. The 3D example shows the crust in the transition zone between the continent and the Inner Borderland in the Los Angeles, California, area, and for the first time, shows an image of the lower crust. The 2D profile provides both a P image and an S image of the basement interface in the San Bernardino basin in southern California.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1785/0220190272DOIArticle
ORCID:
AuthorORCID
Clayton, Robert W.0000-0003-3323-3508
Additional Information:© 2020 Seismological Society of America. Manuscript received 24 September 2019; Published online 29 January 2020. The author thanks Signal Hill Petroleum for permission to use the Long Beach and Extended Long Beach surveys in this study. The author also thanks Dan Hollis for facilitating the use of these data. Reviewers Charles Langston and Nori Nakata improved this study with their comments. This work was supported by National Science Foundation and U.S. Geological Survey Grant Numbers NSF/EAR‐1520081 and USGS/G17AP0000, respectively. Data and Resources: The data associated with the Long Beach example are owned by Signal Hill Petroleum and requires permission from them to use. The data associated with the San Bernardino example will be placed in the public domain in 2021 and will be available from the Incorporated Research Institutions for Seismology Data Management Center (IRIS‐DMC). The supplemental material has images with different choices of the stacking parameters. The unpublished manuscript by R. Clayton (2020), “A detailed image of the continent‐borderland transition beneath Long Beach,” submitted to Geophys. Res. Lett.
Group:Seismological Laboratory
Funders:
Funding AgencyGrant Number
NSFEAR‐1520081
USGSG17AP0000
Issue or Number:2A
Record Number:CaltechAUTHORS:20200506-132126128
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20200506-132126128
Official Citation:Robert W. Clayton; Imaging the Subsurface with Ambient Noise Autocorrelations. Seismological Research Letters ; 91 (2A): 930–935. doi: https://doi.org/10.1785/0220190272
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:103040
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:06 May 2020 20:40
Last Modified:06 May 2020 20:40

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