Abstract
The Eastern United States (EUS) has a complex geological history and hosts several seismic active regions. We investigate the subsurface structure beneath the broader EUS. To produce reliable images of the subsurface, we simultaneously invert smoothed P-wave receiver functions, Rayleigh-wave phase and group velocity measurements, and Bouguer gravity observations for the 3D shear-wave speed. Using surface-wave observations (3–250 s) and spatially smoothed receiver functions, our velocity models are robust, reliable, and rich in detail. The shear-wave velocity models fit all three types of observations well. The resulting velocity model for the eastern U.S. shows thinner crust beneath New England, the east coast, and the Mississippi Embayment (ME). A relatively thicker crust was found beneath the stable North America craton. A relatively slower upper mantle was imaged beneath New England, the east coast, and western ME. A comparison of crust thickness derived from our model against four recent published models shows first-order consistency. A relatively small upper mantle low-speed region correlates with a published P-wave analysis that has associated the anomaly with a 75 Ma kimberlite volcanic site in Kentucky. We also explored the relationship between the subsurface structure and seismicity in the eastern U.S. We found that earthquakes often locate near regions with seismic velocity variations, but not universally. Not all regions of significant subsurface wave speed changes are loci of seismicity. A weak correlation between upper mantle shear velocity and earthquake focal mechanism has been observed.
| Original language | English |
|---|---|
| Article number | e2021GC010233 |
| Journal | Geochemistry, Geophysics, Geosystems |
| Volume | 23 |
| Issue number | 3 |
| DOIs | |
| State | Published - Mar 2022 |
Funding
Initial analyses for this work were performed at the Pennsylvania State University. This work was supported by the U.S. National Science Foundation (grants EAR-1053484 and EAR-1053363) and the U.S. Department of Energy (DOE), Office of Fossil Energy, Carbon Storage Program through the Science-informed Machine Learning for Accelerating Real-Time Decisions in Subsurface Applications (SMART) Initiative. The facilities of IRIS Data Services, and specifically the IRIS Data Management Center, were used for access the waveforms, related metadata, and/or derived products used in this study. See Table S1 for a full list of seismic networks used in this study. IRIS Data Services are funded through the Seismological Facilities for the Advancement of Geoscience and EarthScope (SAGE) Proposal of the National Science Foundation under Cooperative Agreement EAR-1261681. Earthquake catalogs from U.S. Geological Survey (https://earthquake.usgs.gov/earthquakes/search/, last accessed July 2021) and Saint Louis Univeristy Earthquake Center (Herrmann et al., 2011) were used in this study. The authors acknowledge developers of Generic Mapping Tools version 5.4.4 (Wessel et al., 2013) and version 6.1.1 (P. Wessel et al., 2019), Obspy version 1.2.2 (Beyreuther et al., 2010; Krischer et al., 2015; Megies et al., 2011), Numpy version 1.20.1 (Van Der Walt et al., 2011), Matplotlib version 3.3.3 (Hunter, 2007), and Scikit-learn version 0.24.2 (Pedregosa et al., 2011) for sharing their software packages. The authors thank the University of California San Diego for sharing the SRTM15 topography data that were used as background for several figures. The authors also thank National Centers for Environmental Information for making ETOPO Global Relief Model available. The boundaries of sedimentary basins were extracted from Coleman Jr. and Cahan (2012). This manuscript has been authored in part by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US Government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript or allow others to do so for US Government purposes. The authors thank Editor Maureen Long, Brian Savage, and an anonymous reviewer for their constructive comments. The views and conclusions contained in this document are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of the U.S. Government. Initial analyses for this work were performed at the Pennsylvania State University. This work was supported by the U.S. National Science Foundation (grants EAR‐1053484 and EAR‐1053363) and the U.S. Department of Energy (DOE), Office of Fossil Energy, Carbon Storage Program through the Science‐informed Machine Learning for Accelerating Real‐Time Decisions in Subsurface Applications (SMART) Initiative. The facilities of IRIS Data Services, and specifically the IRIS Data Management Center, were used for access the waveforms, related metadata, and/or derived products used in this study. See Table S1 for a full list of seismic networks used in this study. IRIS Data Services are funded through the Seismological Facilities for the Advancement of Geoscience and EarthScope (SAGE) Proposal of the National Science Foundation under Cooperative Agreement EAR‐1261681. Earthquake catalogs from U.S. Geological Survey ( https://earthquake.usgs.gov/earthquakes/search/ , last accessed July 2021) and Saint Louis Univeristy Earthquake Center (Herrmann et al., 2011 ) were used in this study. The authors acknowledge developers of Generic Mapping Tools version 5.4.4 (Wessel et al., 2013 ) and version 6.1.1 (P. Wessel et al., 2019 ), Obspy version 1.2.2 (Beyreuther et al., 2010 ; Krischer et al., 2015 ; Megies et al., 2011 ), Numpy version 1.20.1 (Van Der Walt et al., 2011 ), Matplotlib version 3.3.3 (Hunter, 2007 ), and Scikit‐learn version 0.24.2 (Pedregosa et al., 2011 ) for sharing their software packages. The authors thank the University of California San Diego for sharing the SRTM15 topography data that were used as background for several figures. The authors also thank National Centers for Environmental Information for making ETOPO Global Relief Model available. The boundaries of sedimentary basins were extracted from Coleman Jr. and Cahan ( 2012 ). This manuscript has been authored in part by UT‐Battelle, LLC, under contract DE‐AC05‐00OR22725 with the US Department of Energy (DOE). The US Government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid‐up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript or allow others to do so for US Government purposes. The authors thank Editor Maureen Long, Brian Savage, and an anonymous reviewer for their constructive comments. The views and conclusions contained in this document are those of the authors and should not be interpreted as necessarily representing the official policies, either expressed or implied, of the U.S. Government.
Keywords
- North America
- gravity
- joint inversion
- lithospheric structure
- receiver function
- surface-wave dispersion