A ground-motion prediction model for small-to-moderate induced earthquakes for Central and Eastern United States

Abstract

This study presents a new ground motion model (GMM) for small-to-moderate potentially induced earthquakes for Central and Eastern United States (CEUS). We used a hybrid empirical model as the base model, which was developed and calibrated for tectonic events in Central and Eastern North America (CENA) as part of the Next-generation Attenuation-East (NGA-East) project. We calibrated the base model using a comprehensive database of potentially induced ground motions with smaller magnitudes and shallower depths than tectonic earthquakes, excluding all earthquake events and stations within the Gulf Coast region. We determined the model functional form coefficients using a mixed-effect regression procedure. The proposed GMM is derived for the peak ground acceleration and response-spectral ordinates at periods ranging from 0.01 to 10.0s, moment magnitudes ranging from 3.0 to 5.8, and hypocentral distances up to 200km. The performance of the proposed GMM is evaluated through a set of comprehensive residual analyses. Furthermore, we compared the proposed GMM with recently published GMMs with the observed data for CEUS. The proposed GMM could apply in long-term and short-term US Geological Survey National Seismic Hazard Maps and for the hazard evaluation of induced seismicity.

Earthquake hazard and risk analysis for natural and induced seismicity: towards objective assessments in the face of uncertainty

“…For the Groningen gas field, we identified the need for applicationspecific GMMs given that the recorded motions-probably due to specific features of the uppermost crustal structure-displayed systematic differences even with respect to induced earthquakes in other Dutch gas fields (Bommer et al 2016). Ground-motion models for induced seismicity in other specific regions have been developed by several researchers, particularly for Oklahoma (Yenier et al 2017;Novakovic et al 2018;Zalachoris and Rathje 2019) or the Central and Eastern United States in general (Farajpour and Pezeshk 2021). Atkinson (2015) developed an empirical GMM specifically for application to induced earthquakes but using recordings from tectonic earthquakes.…”

Ground motion model for Peninsular India using an artificial neural network

“…In this study, the boundary of the GC region provided by Dreiling et al (2014) is considered to remove the records. Since the data also contain the potentially induced ground motions, no effort has been made to distinguish their records as they are fundamentally not different from the tectonic ground motions (Farajpour and Pezeshk, 2021). After following the above criteria, the GMP-1 model considers 2704 records from 74 earthquakes recorded at 790 stations.…”