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Title: Spatio-temporal distribution of Oklahoma earthquakes: Exploring relationships using a nearest-neighbor approach: Nearest-neighbor analysis of Oklahoma

Determining the spatiotemporal characteristics of natural and induced seismic events holds the opportunity to gain new insights into why these events occur. Linking the seismicity characteristics with other geologic, geographic, natural, or anthropogenic factors could help to identify the causes and suggest mitigation strategies that reduce the risk associated with such events. The nearest-neighbor approach utilized in this work represents a practical first step toward identifying statistically correlated clusters of recorded earthquake events. Detailed study of the Oklahoma earthquake catalog’s inherent errors, empirical model parameters, and model assumptions is presented. We found that the cluster analysis results are stable with respect to empirical parameters (e.g., fractal dimension) but were sensitive to epicenter location errors and seismicity rates. Most critically, we show that the patterns in the distribution of earthquake clusters in Oklahoma are primarily defined by spatial relationships between events. This observation is a stark contrast to California (also known for induced seismicity) where a comparable cluster distribution is defined by both spatial and temporal interactions between events. These results highlight the difficulty in understanding the mechanisms and behavior of induced seismicity but provide insights for future work.
Authors:
ORCiD logo [1] ;  [2]
  1. National Energy Technology Lab. (NETL), Albany, OR (United States); Oak Ridge Inst. for Science and Education (ORISE), Oak Ridge, TN (United States)
  2. National Energy Technology Lab. (NETL), Albany, OR (United States)
Publication Date:
Report Number(s):
NETL-PUB-20788
Journal ID: ISSN 2169-9313
Type:
Accepted Manuscript
Journal Name:
Journal of Geophysical Research. Solid Earth
Additional Journal Information:
Journal Volume: 122; Journal Issue: 7; Journal ID: ISSN 2169-9313
Publisher:
American Geophysical Union
Research Org:
National Energy Technology Lab. (NETL), Albany, OR (United States). In-house Research
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English
Subject:
58 GEOSCIENCES; cluster analysis, natural and induced seismicity, nearest-neighbor approach
OSTI Identifier:
1369245
Alternate Identifier(s):
OSTI ID: 1375065

Vasylkivska, Veronika S., and Huerta, Nicolas J.. Spatio-temporal distribution of Oklahoma earthquakes: Exploring relationships using a nearest-neighbor approach: Nearest-neighbor analysis of Oklahoma. United States: N. p., Web. doi:10.1002/2016JB013918.
Vasylkivska, Veronika S., & Huerta, Nicolas J.. Spatio-temporal distribution of Oklahoma earthquakes: Exploring relationships using a nearest-neighbor approach: Nearest-neighbor analysis of Oklahoma. United States. doi:10.1002/2016JB013918.
Vasylkivska, Veronika S., and Huerta, Nicolas J.. 2017. "Spatio-temporal distribution of Oklahoma earthquakes: Exploring relationships using a nearest-neighbor approach: Nearest-neighbor analysis of Oklahoma". United States. doi:10.1002/2016JB013918. https://www.osti.gov/servlets/purl/1369245.
@article{osti_1369245,
title = {Spatio-temporal distribution of Oklahoma earthquakes: Exploring relationships using a nearest-neighbor approach: Nearest-neighbor analysis of Oklahoma},
author = {Vasylkivska, Veronika S. and Huerta, Nicolas J.},
abstractNote = {Determining the spatiotemporal characteristics of natural and induced seismic events holds the opportunity to gain new insights into why these events occur. Linking the seismicity characteristics with other geologic, geographic, natural, or anthropogenic factors could help to identify the causes and suggest mitigation strategies that reduce the risk associated with such events. The nearest-neighbor approach utilized in this work represents a practical first step toward identifying statistically correlated clusters of recorded earthquake events. Detailed study of the Oklahoma earthquake catalog’s inherent errors, empirical model parameters, and model assumptions is presented. We found that the cluster analysis results are stable with respect to empirical parameters (e.g., fractal dimension) but were sensitive to epicenter location errors and seismicity rates. Most critically, we show that the patterns in the distribution of earthquake clusters in Oklahoma are primarily defined by spatial relationships between events. This observation is a stark contrast to California (also known for induced seismicity) where a comparable cluster distribution is defined by both spatial and temporal interactions between events. These results highlight the difficulty in understanding the mechanisms and behavior of induced seismicity but provide insights for future work.},
doi = {10.1002/2016JB013918},
journal = {Journal of Geophysical Research. Solid Earth},
number = 7,
volume = 122,
place = {United States},
year = {2017},
month = {6}
}