Quantifying temporally-varying induced seismicity hazard and regional risk : statistical approaches, and application in Oklahoma
Abstract/Contents
- Abstract
- We describe a Bayesian change-point model to estimate time-varying seismicity rates, develop a mixture of mixtures model to associate wastewater injection volumes with seismicity, propose a regional ground-motion prediction equation and describe a framework to quantify temporally-varying seismic hazard and regional risk, with application to induced seismicity in Oklahoma. We describe a Bayesian change-point model that detects if the seismicity rate has changed using a time series of observed earthquake occurrences. We show that for steep changes in seismicity rates, such as those that have been observed for induced seismicity in Oklahoma, change can be detected within 3 months of its occurrence. The Bayesian model yields posterior probability distributions for the date of change, and the rates before and after the change. We compile a database of ground motions from the central and eastern United States for magnitude ≥ 3 earthquakes from 2001 through 2016. We observe that ground motions from tectonic earthquakes attenuate faster within the first 20 km. This results in slightly higher ground shaking from induced earthquakes. We propose a ground-motion prediction equation (GMPE) for induced earthquakes in the central US, by scaling an existing GMPE. We use a logistic regression model to show that high wastewater injection volumes are correlated with regions of seismicity change. We propose a statistical model to establish functional relationships between injection volumes and seismicity. We use a mixture of mixtures model to find these functional relationships. We also describe a generalized mixture of mixtures model that can be used to find temporal or spatial trends in the mixing proportions and parameters of mixture distributions. We extend the Probabilistic Seismic Hazard Assessment (PSHA) framework to account for temporally-changing seismicity rates due to induced seismicity. Seismicity rates can be obtained from multiple methods, like the change-point model or the mixture of mixtures model. For the latter model, injection volumes can be used directly for hazard estimation without first obtaining the seismicity rates. We implement a stochastic Monte-Carlo approach using OpenQuake to estimate temporally-varying induced seismicity hazard in Oklahoma City and estimate the regional risk for the complete portfolio of buildings in Oklahoma obtained using HAZUS. Our goal with this dissertation is to provide stakeholders, regulators and community members with the necessary tools to quantify impacts from induced seismicity. We believe that the tools developed in this dissertation will result in developing effective risk mitigation strategies for regions of induced seismicity.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2017 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Gupta, Abhineet |
|---|---|
| Associated with | Stanford University, Civil & Environmental Engineering Department. |
| Primary advisor | Baker, Jack W |
| Thesis advisor | Baker, Jack W |
| Thesis advisor | Deierlein, Gregory G. (Gregory Gerard), 1959- |
| Thesis advisor | Zoback, Mark D |
| Advisor | Deierlein, Gregory G. (Gregory Gerard), 1959- |
| Advisor | Zoback, Mark D |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Abhineet Gupta. |
|---|---|
| Note | Submitted to the Department of Civil and Environmental Engineering. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2017. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2017 by Abhineet Gupta
- License
- This work is licensed under a Creative Commons Attribution Share Alike 3.0 Unported license (CC BY-SA).
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