Monte Carlo Method for Probabilistic Hazard Assessment of Induced Seismicity due to Conventional Natural Gas Production
File(s)
Accepted version
Author(s)
Type
Journal Article
Abstract
A Monte Carlo approach to probabilistic seismic‐hazard analysis is developed for a case of induced seismicity associated with a compacting gas reservoir. The geomechanical foundation for the method is the work of Kostrov (1974) and McGarr (1976) linking total strain to summed seismic moment in an earthquake catalog. Our Monte Carlo method simulates future seismic hazard consistent with historical seismic and compaction datasets by sampling probability distributions for total seismic moment, event locations and magnitudes, and resulting ground motions. Ground motions are aggregated over an ensemble of simulated catalogs to give a probabilistic representation of the ground‐motion hazard. This approach is particularly well suited to the specific nature of the time‐dependent induced seismicity considered.
We demonstrate the method by applying it to seismicity induced by reservoir compaction following gas production from the Groningen gas field. A new ground‐motion prediction equation (GMPE) tailored to the Groningen field has been derived by calibrating an existing GMPE with local strong‐motion data. For 2013–2023, we find a 2% chance of exceeding a peak ground acceleration of 0.57g and a 2% chance of exceeding a peak ground velocity of 22 cm/s above the area of maximum compaction. Disaggregation shows that earthquakes of Mw 4–5, at the shortest hypocentral distances of 3 km, and ground motions two standard deviations above the median make the largest contributions to this hazard. Uncertainty in the hazard is primarily due to uncertainty about the future fraction of induced strains that will be seismogenic and how ground motion and its variability will scale to larger magnitudes.
We demonstrate the method by applying it to seismicity induced by reservoir compaction following gas production from the Groningen gas field. A new ground‐motion prediction equation (GMPE) tailored to the Groningen field has been derived by calibrating an existing GMPE with local strong‐motion data. For 2013–2023, we find a 2% chance of exceeding a peak ground acceleration of 0.57g and a 2% chance of exceeding a peak ground velocity of 22 cm/s above the area of maximum compaction. Disaggregation shows that earthquakes of Mw 4–5, at the shortest hypocentral distances of 3 km, and ground motions two standard deviations above the median make the largest contributions to this hazard. Uncertainty in the hazard is primarily due to uncertainty about the future fraction of induced strains that will be seismogenic and how ground motion and its variability will scale to larger magnitudes.
Date Issued
2015-05-19
Date Acceptance
2015-02-28
Citation
Bulletin of the Seismological Society of America, 2015, 105 (3), pp.1721-1738
ISSN
0037-1106
Publisher
Seismological Society of America
Start Page
1721
End Page
1738
Journal / Book Title
Bulletin of the Seismological Society of America
Volume
105
Issue
3
Copyright Statement
Copyright © 2015 Seismological Society of America
Subjects
Science & Technology
Physical Sciences
Geochemistry & Geophysics
GROUND-MOTION PREDICTION
AVERAGE HORIZONTAL COMPONENT
EASTERN UNITED-STATES
INDUCED EARTHQUAKES
MODELS
EQUATIONS
DEAGGREGATION
PERFORMANCE
CALIFORNIA
INJECTION
Publication Status
Published