Research Article| June 26, 2018 A New Automated Approach to Detecting and Locating Seismic Events Using Data from a Large Network Catherine D. de Groot‐Hedlin; Catherine D. de Groot‐Hedlin aInstitute of Geophysics and Planetary Physics, Scripps Institution of Oceanography, University of California, San Diego, 9500 Gilman Drive, La Jolla, California 92093‐0225, chedlin@ucsd.eduhedlin@ucsd.edu Search for other works by this author on: GSW Google Scholar Michael A. H. Hedlin Michael A. H. Hedlin aInstitute of Geophysics and Planetary Physics, Scripps Institution of Oceanography, University of California, San Diego, 9500 Gilman Drive, La Jolla, California 92093‐0225, chedlin@ucsd.eduhedlin@ucsd.edu Search for other works by this author on: GSW Google Scholar Author and Article Information Catherine D. de Groot‐Hedlin aInstitute of Geophysics and Planetary Physics, Scripps Institution of Oceanography, University of California, San Diego, 9500 Gilman Drive, La Jolla, California 92093‐0225, chedlin@ucsd.eduhedlin@ucsd.edu Michael A. H. Hedlin aInstitute of Geophysics and Planetary Physics, Scripps Institution of Oceanography, University of California, San Diego, 9500 Gilman Drive, La Jolla, California 92093‐0225, chedlin@ucsd.eduhedlin@ucsd.edu Publisher: Seismological Society of America First Online: 26 Jun 2018 Online Issn: 1943-3573 Print Issn: 0037-1106 © Seismological Society of America Bulletin of the Seismological Society of America (2018) 108 (4): 2032–2045. https://doi.org/10.1785/0120180072 Article history First Online: 26 Jun 2018 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation Catherine D. de Groot‐Hedlin, Michael A. H. Hedlin; A New Automated Approach to Detecting and Locating Seismic Events Using Data from a Large Network. Bulletin of the Seismological Society of America 2018;; 108 (4): 2032–2045. doi: https://doi.org/10.1785/0120180072 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietyBulletin of the Seismological Society of America Search Advanced Search Abstract The Automated Event Location Using a Mesh of Arrays (AELUMA) method, originally developed for detection of atmospheric sources using infrasonic data, is modified here to detect and locate seismic events. A key feature of AELUMA is that it does not require a detailed velocity model to locate events. The new method was applied to vertical‐component seismic data recorded by the USArray Transportable Array to (1) test its efficacy when applied to a very large dataset, (2) test its ability to detect and accurately locate distinct event types across a geologically diverse region without analyst oversight, and (3) assess the sensitivity and accuracy of the method. Using data filtered from 1 to 8 Hz, 9996 events were detected in clusters within the central United States—with most events located near areas known for anthropogenic activity. The method was compared with three catalogs in Oklahoma—a region known for small anthropogenic events. In comparison with accurate locations from a template study, AELUMA detected all events from ML≥1.9 but none below ML 1.3. The median absolute origin time and location offset were 9.5 s and 6.0 km, respectively. Comparisons of AELUMA’s catalog in Oklahoma with two others (produced by Oklahoma Geological Survey [OGS] and the Array Network Facility) showed that AELUMA found more events than either catalog, including clusters of emergent events that were largely missed by the other methods. However, most of the smaller magnitude events detected by OGS were missed by AELUMA, mainly due to the sparser network used by AELUMA. You do not have access to this content, please speak to your institutional administrator if you feel you should have access.