Using a Time-based Subarray Method to Extract and Invert Noise-derived Body Waves at Long Beach, California
Abstract
The reconstruction of body waves from the cross‐correlation of random wavefields has recently emerged as a promising approach to probe the fine‐scale structure of the Earth. However, because of the nature of the ambient noise field, the retrieval of body waves from seismic noise recordings is highly challenging and has only been successful in a few cases. Here, we use seismic noise data from a 5,200‐node oil‐company survey to reconstruct body waves and determine the velocity structure beneath Long Beach, California. To isolate the body wave energy from the ambient noise field, we divide the entire survey into small‐aperture subarrays and apply a modified double‐beamforming scheme to enhance coherent arrivals within the cross‐correlated waveforms. The resulting beamed traces allow us to identify clear refracted P waves traveling between different subarray pairs, which we then use to construct a high‐resolution 3D velocity model of the region. The inverted velocity model reveals velocity variations of the order of 3% and strong lateral discontinuities caused by the presence of sharp geologic structures such as the Newport‐Inglewood fault (NIF). Additionally, we show that the resolution that is achieved through the use of high‐frequency body waves allows us to illuminate small geometric variations of the NIF that were previously unresolved with traditional passive imaging methods.
Additional Information
© 2020 The Authors. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Received 8 OCT 2019; Accepted 25 MAR 2020; Accepted article online 6 APR 2020. The data used in this study is the property of Signal Hill Petroleum Inc., and permission from them is required to access it. We gratefully acknowledge Signal Hill Petroleum, Inc., for permitting us to use the Long Beach data. This work was supported by NSF/EAR‐15200081. We thank Dunzhu Li for providing the ambient noise cross‐correlations. We gratefully thank Nori Nakata and an anonymous reviewer for their careful and constructive suggestions. The figures presented in this paper were made using the Generic Mapping Tools v.4.5.9 (https:/soest.hawaii.edu/gmt). The final P wave velocity model can be downloaded from: https://doi.org/10.22002/D1.1293. The traveltime measurements used to generate the velocity model can also be downloaded from that site.Attached Files
Published - 2019JB018855.pdf
Supplemental Material - jgrb54121-sup-0001-2019jb018855-text_si-s01.pdf
Supplemental Material - jgrb54121-sup-0002-2019jb018855-movie_si-s01.mp4
Supplemental Material - jgrb54121-sup-0003-2019jb018855-movie_si-s02.mp4
Supplemental Material - jgrb54121-sup-0004-2019jb018855-movie_si-s03.mp4
Supplemental Material - jgrb54121-sup-0005-2019jb018855-movie_si-s04.mp4
Files
Name | Size | Download all |
---|---|---|
md5:fde61adb3bce45740420290431484e5f
|
13.7 MB | Preview Download |
md5:c8b53ce1b8fa627ee49c61c0d084029b
|
39.5 MB | Download |
md5:84e3e1625bc64447fbf41a573ebf98d4
|
26.5 MB | Preview Download |
md5:4307c7962736d2f94c26ab13f3ca56ff
|
10.9 MB | Download |
md5:0930b831633494a4333b9abbe3c9eebd
|
10.5 MB | Download |
md5:6dfd22e897c58fdab81fca58fb4f2071
|
16.4 MB | Download |
Additional details
- Eprint ID
- 102368
- Resolver ID
- CaltechAUTHORS:20200407-074554849
- NSF
- EAR-15200081
- Created
-
2020-04-07Created from EPrint's datestamp field
- Updated
-
2023-06-01Created from EPrint's last_modified field
- Caltech groups
- Seismological Laboratory, Division of Geological and Planetary Sciences (GPS)