Improved Microseismicity Detection During Newberry EGS Stimulations

Abstract
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.
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Additional Info

DOE Project Number: FY13 AOP 25728
DOE Project Lead: Lauren Boyd
DOI: 10.15121/1148783
Last Updated: over a year ago
Nov
2013
Data from November, 2013
Submitted Feb 4, 2014

Lawrence Livermore National Laboratory

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925.422.2021

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This submission does not list any authors.

Keywords

geothermal, EGS, seismicity, microseismicity, stimulation, fracture, reservoir, NGDS Content Model, USGIN Content Model, induced seismicity, Newberry, microearthquake

Status

Publicly accessible License 

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