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Title: Improved Microseismicity Detection During Newberry EGS Stimulations

Effective enhanced geothermal systems (EGS) require optimal fracture networks for efficient heat transfer between hot rock and fluid. Microseismic mapping is a key tool used to infer the subsurface fracture geometry. Traditional earthquake detection and location techniques are often employed to identify microearthquakes in geothermal regions. However, most commonly used algorithms may miss events if the seismic signal of an earthquake is small relative to the background noise level or if a microearthquake occurs within the coda of a larger event. Consequently, we have developed a set of algorithms that provide improved microearthquake detection. Our objective is to investigate the microseismicity at the DOE Newberry EGS site to better image the active regions of the underground fracture network during and immediately after the EGS stimulation. Detection of more microearthquakes during EGS stimulations will allow for better seismic delineation of the active regions of the underground fracture system. This improved knowledge of the reservoir network will improve our understanding of subsurface conditions, and allow improvement of the stimulation strategy that will optimize heat extraction and maximize economic return.
Authors:
Publication Date:
Report Number(s):
249
DOE Contract Number:
FY13 AOP 25728
Product Type:
Dataset
Research Org(s):
DOE Geothermal Data Repository; Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Collaborations:
Lawrence Livermore National Laboratory
Sponsoring Org:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Geothermal Technologies Office (EE-4G)
Subject:
15 Geothermal Energy; geothermal; EGS; seismicity; microseismicity; stimulation; fracture; reservoir; earthquakes
OSTI Identifier:
1148810

Templeton, Dennise. Improved Microseismicity Detection During Newberry EGS Stimulations. United States: N. p., Web. doi:10.15121/1148810.
Templeton, Dennise. Improved Microseismicity Detection During Newberry EGS Stimulations. United States. doi:10.15121/1148810.
Templeton, Dennise. 2013. "Improved Microseismicity Detection During Newberry EGS Stimulations". United States. doi:10.15121/1148810. https://www.osti.gov/servlets/purl/1148810.
@misc{osti_1148810,
title = {Improved Microseismicity Detection During Newberry EGS Stimulations},
author = {Templeton, Dennise},
abstractNote = {Effective enhanced geothermal systems (EGS) require optimal fracture networks for efficient heat transfer between hot rock and fluid. Microseismic mapping is a key tool used to infer the subsurface fracture geometry. Traditional earthquake detection and location techniques are often employed to identify microearthquakes in geothermal regions. However, most commonly used algorithms may miss events if the seismic signal of an earthquake is small relative to the background noise level or if a microearthquake occurs within the coda of a larger event. Consequently, we have developed a set of algorithms that provide improved microearthquake detection. Our objective is to investigate the microseismicity at the DOE Newberry EGS site to better image the active regions of the underground fracture network during and immediately after the EGS stimulation. Detection of more microearthquakes during EGS stimulations will allow for better seismic delineation of the active regions of the underground fracture system. This improved knowledge of the reservoir network will improve our understanding of subsurface conditions, and allow improvement of the stimulation strategy that will optimize heat extraction and maximize economic return.},
doi = {10.15121/1148810},
year = {2013},
month = {10} }
  1. The Geothermal Data Repository (GDR) is the submission point for all data collected from researchers funded by the U.S. Department of Energy's Geothermal Technologies Office (DOE GTO). The DOE GTO is providing access to its geothermal project information through the GDR. The GDR is powered by OpenEI, an energy information portal sponsored by the U.S. Department of Energy and developed by the National Renewable Energy Laboratory (NREL).
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