Item talk:Q304556

{

 "USGS Publications Warehouse": {
   "@context": "https://schema.org",
   "@type": "CreativeWork",
   "additionalType": "Conference Paper",
   "name": "Natural or Induced: Identifying Natural and Induced Swarms from Pre-production and Co-production Microseismic Catalogs at the Coso Geothermal Field",
   "identifier": [
     {
       "@type": "PropertyValue",
       "propertyID": "USGS Publications Warehouse IndexID",
       "value": "70138824",
       "url": "https://pubs.usgs.gov/publication/70138824"
     },
     {
       "@type": "PropertyValue",
       "propertyID": "USGS Publications Warehouse Internal ID",
       "value": 70138824
     }
   ],
   "inLanguage": "en",
   "datePublished": "2015",
   "dateModified": "2015-10-26",
   "abstract": "Increased levels of seismicity coinciding with injection of reservoir fluids have prompted interest in methods to distinguish induced from natural seismicity. Discrimination between induced and natural seismicity is especially difficult in areas that have high levels of natural seismicity, such as the geothermal fields at the Salton Sea and Coso, both in California. Both areas show swarm-like sequences that could be related to natural, deep fluid migration as part of the natural hydrothermal system. Therefore, swarms often have spatio-temporal patterns that resemble fluid-induced seismicity, and might possibly share other characteristics. The Coso Geothermal Field and its surroundings is one of the most seismically active areas in California with a large proportion of its activity occurring as seismic swarms. Here we analyze clustered seismicity in and surrounding the currently produced reservoir comparatively for pre-production and co-production periods. We perform a cluster analysis, based on the inter-event distance in a space-time-energy domain to identify notable earthquake sequences. For each event j, the closest previous event i is identified and their relationship categorized. If this nearest neighbor\u2019s distance is below a threshold based on the local minimum of the bimodal distribution of nearest neighbor distances, then the event j is included in the cluster as a child to this parent event i. If it is above the threshold, event j begins a new cluster. This process identifies subsets of events whose nearest neighbor distances and relative timing qualify as a cluster as well as a characterizing the parent-child relationships among events in the cluster. We apply this method to three different catalogs: (1) a two-year microseismic survey of the Coso geothermal area that was acquired before exploration drilling in the area began; (2) the HYS_catalog_2013 that contains 52,000 double-difference relocated events and covers the years 1981 to 2013; and (3) a catalog of 57,000 events with absolute locations from the local network recorded between 2002 and 2007. Using this method we identify 10 clusters of more than 20 events each in the pre-production survey and more than 200 distinct seismicity clusters that each contain at least 20 and up to more than 1000 earthquakes in the more extensive catalogs. The cluster identification method used yields a hierarchy of links between multiple generations of parent and offspring events. We analyze different topological parameters of this hierarchy to better characterize and thus differentiate natural swarms from induced clustered seismicity and also to identify aftershock sequences of notable mainshocks. We find that the branching characteristic given by the average number of child events per parent event is significantly different for clusters below than for clusters around the produced field.",
   "description": "11 p.",
   "publisher": {
     "@type": "Organization",
     "name": "Stanford University"
   },
   "author": [
     {
       "@type": "Person",
       "name": "Schoenball, Martin mschoenball@usgs.gov",
       "givenName": "Martin",
       "familyName": "Schoenball",
       "email": "mschoenball@usgs.gov",
       "affiliation": [
         {
           "@type": "Organization",
           "name": "Geology, Minerals, Energy, and Geophysics Science Center",
           "url": "https://www.usgs.gov/centers/gmeg"
         }
       ]
     },
     {
       "@type": "Person",
       "name": "Kaven, J. Ole okaven@usgs.gov",
       "givenName": "J. Ole",
       "familyName": "Kaven",
       "email": "okaven@usgs.gov",
       "identifier": {
         "@type": "PropertyValue",
         "propertyID": "ORCID",
         "value": "0000-0003-2625-2786",
         "url": "https://orcid.org/0000-0003-2625-2786"
       },
       "affiliation": [
         {
           "@type": "Organization",
           "name": "Earthquake Science Center",
           "url": "https://www.usgs.gov/centers/earthquake-science-center"
         }
       ]
     },
     {
       "@type": "Person",
       "name": "Glen, Jonathan M. G. jglen@usgs.gov",
       "givenName": "Jonathan M. G.",
       "familyName": "Glen",
       "email": "jglen@usgs.gov",
       "affiliation": [
         {
           "@type": "Organization",
           "name": "Geology, Minerals, Energy, and Geophysics Science Center",
           "url": "https://www.usgs.gov/centers/gmeg"
         }
       ]
     },
     {
       "@type": "Person",
       "name": "Davatzes, Nicholas C.",
       "givenName": "Nicholas C.",
       "familyName": "Davatzes",
       "affiliation": [
         {
           "@type": "Organization",
           "name": "Temple University"
         }
       ]
     }
   ],
   "funder": [
     {
       "@type": "Organization",
       "name": "Geology, Minerals, Energy, and Geophysics Science Center",
       "url": "https://www.usgs.gov/centers/gmeg"
     }
   ]
 }

}