Induced Earthquake Hazard by Geothermal Power Plants: Statistical Evaluation and Probabilistic Modeling

Abstract

This 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.

Improving recognition accuracy for facial expressions using scattering wavelet

“…It represents the structure of facial changes as a linear combination of local basis functions whose coefficients are proportional to the brightness intensity of the pixels. This research showed that a linear model with Gabor fuzzy shift could calculate the linear functions based on the framework [22,23]. The proposed method uses video images as training and test data.…”