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.
Citation Formats
TY - DATA
AB - 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.
AU - Templeton, Dennise
DB - Open Energy Data Initiative (OEDI)
DP - Open EI | National Renewable Energy Laboratory
DO - 10.15121/1148783
KW - geothermal
KW - EGS
KW - seismicity
KW - microseismicity
KW - stimulation
KW - fracture
KW - reservoir
KW - NGDS Content Model
KW - USGIN Content Model
KW - induced seismicity
KW - Newberry
KW - microearthquake
KW - monitoring
KW - measurement
KW - detection
KW - hydrualic
LA - English
DA - 2013/11/01
PY - 2013
PB - Lawrence Livermore National Laboratory
T1 - Improved Microseismicity Detection During Newberry EGS Stimulations
UR - https://doi.org/10.15121/1148783
ER -
Templeton, Dennise. Improved Microseismicity Detection During Newberry EGS Stimulations. Lawrence Livermore National Laboratory, 1 November, 2013, GDR. https://doi.org/10.15121/1148783.
Templeton, D. (2013). Improved Microseismicity Detection During Newberry EGS Stimulations. [Data set]. GDR. Lawrence Livermore National Laboratory. https://doi.org/10.15121/1148783
Templeton, Dennise. Improved Microseismicity Detection During Newberry EGS Stimulations. Lawrence Livermore National Laboratory, November, 1, 2013. Distributed by GDR. https://doi.org/10.15121/1148783
@misc{OEDI_Dataset_6619,
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.},
url = {https://gdr.openei.org/submissions/281},
year = {2013},
howpublished = {GDR, Lawrence Livermore National Laboratory, https://doi.org/10.15121/1148783},
note = {Accessed: 2025-05-03},
doi = {10.15121/1148783}
}
https://dx.doi.org/10.15121/1148783
Details
Data from Nov 1, 2013
Last updated Nov 14, 2019
Submitted Feb 5, 2014
Organization
Lawrence Livermore National Laboratory
Contact
Dennise Templeton
925.422.2021
Authors
Original Source
https://gdr.openei.org/submissions/281Research Areas
Keywords
geothermal, EGS, seismicity, microseismicity, stimulation, fracture, reservoir, NGDS Content Model, USGIN Content Model, induced seismicity, Newberry, microearthquake, monitoring, measurement, detection, hydrualicDOE Project Details
Project Lead Lauren Boyd
Project Number FY13 AOP 25728