Author:
Khansefid Ali,Yadollahi Seyed Mahmoudreza,Müller Gerhard,Taddei Francesca
Abstract
AbstractThis study statistically evaluated the characteristics of induced earthquakes by geothermal power plants (GPPs) and generated a probabilistic model for simulating stochastic seismic events. Four well-known power plant zones were selected worldwide from the United States, Germany, France, and New Zealand. The operational condition information, as well as the corresponding earthquake catalogs recorded in the vicinity of GPPs, were gathered from their commencement date. The statistical properties of events were studied elaborately. By using this proposed database, a probabilistic model was developed capable of generating the number of induced seismic events per month, their magnitude, focal depth, and distance from the epicenter to the power plant, randomly. All of these parameters are simulated as a function of power plant injection rate. Generally speaking, the model, introduced in this study, is a tool for engineers and scientists interested in the seismic risk assessment of built environments prone to induced seismicity produced by GPPs operation.
Publisher
Springer Science and Business Media LLC
Subject
Management, Monitoring, Policy and Law,Safety Research,Geography, Planning and Development,Global and Planetary Change
Reference59 articles.
1. Allis, R.G., S.A. Currie, J.D. Leaver, and S. Sherburn. 1985. Results of injection testing at Wairakei geothermal field, New Zealand. In Proceedings of Geothermal Resource Council International Symposium on Geothermal Energy, 26 August 1985, Kailua Kona, HI, USA, 289–294.
2. Bachmann, C.E., S. Wiemer, B.P. Goertz‐Allmann, and J. Woessner. 2012. Influence of pore‐pressure on the event‐size distribution of induced earthquakes. Geophysical Research Letters 39(9): Article L09302.
3. Barth, A., F. Wenzel, and C. Langenbruch. 2013. Probability of earthquake occurrence and magnitude estimation in the post shut-in phase of geothermal projects. Journal of Seismology 17(1): 5–11.
4. Bay of Plenty Regional Council. 2018. Kawerau geothermal system management plan. Whakatane, New Zealand: Bay of Plenty Regional Council.
5. Bishop, C.M. 2007. Pattern recognition and machine learning. New York: Springer.
Cited by
6 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献