Pungky Megasari Suroyo, Jaleena Sunny, Benjamin Edwards
{"title":"Physically adjusted ground motion prediction equations for induced seismicity at Preston New Road, UK","authors":"Pungky Megasari Suroyo, Jaleena Sunny, Benjamin Edwards","doi":"10.1007/s10950-024-10235-2","DOIUrl":null,"url":null,"abstract":"<div><p>Predicting ground motions due to induced seismicity is a challenging task owing to the scarcity of data and heterogeneity of the uppermost crust. Dealing with this requires a thorough understanding of the underlying physics and consideration of inter-site variability. The most common ground motion model used in practice is the parametric ground motion prediction equation (GMPE), of which hundreds exist in the literature. However, relatively few are developed with a focus on induced seismicity. Developing GMPEs that are specific to an appropriate magnitude-distance range (<span>\\(R < 30\\)</span> km; <span>\\(2 \\le M \\le 6\\)</span>) is important for induced seismicity applications. This paper proposes a framework for the development of physically-based GMPEs to provide more accurate and reliable estimates of the potential induced-seismicity ground motion hazard, allowing for better risk assessment and management strategies. To demonstrate this approach, a new set of GMPEs for the 2018-2019 induced seismicity sequence at the Preston New Road (PNR) shale gas site near Blackpool, United Kingdom, is presented. The physically-based GMPE was developed based on a pseudo-finite-fault stochastic ground motion simulation, calibrated with parameters derived from the spectral analysis of weak-motion records from induced seismic events. An optimization-based calibration technique using the area metric (AM) was subsequently performed to calibrate optimal parameters for simulating ground motion at the PNR site. Finally, using a suite of forward simulations for events with <span>\\(1 \\le M \\le 6\\)</span> recorded at distances up to 30 km, combined with empirical data, a location-specific GMPE was derived through adjustment of an existing model.</p></div>","PeriodicalId":16994,"journal":{"name":"Journal of Seismology","volume":"28 5","pages":"1147 - 1171"},"PeriodicalIF":1.6000,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10950-024-10235-2.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Seismology","FirstCategoryId":"89","ListUrlMain":"https://link.springer.com/article/10.1007/s10950-024-10235-2","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"GEOCHEMISTRY & GEOPHYSICS","Score":null,"Total":0}
引用次数: 0
Abstract
Predicting ground motions due to induced seismicity is a challenging task owing to the scarcity of data and heterogeneity of the uppermost crust. Dealing with this requires a thorough understanding of the underlying physics and consideration of inter-site variability. The most common ground motion model used in practice is the parametric ground motion prediction equation (GMPE), of which hundreds exist in the literature. However, relatively few are developed with a focus on induced seismicity. Developing GMPEs that are specific to an appropriate magnitude-distance range (\(R < 30\) km; \(2 \le M \le 6\)) is important for induced seismicity applications. This paper proposes a framework for the development of physically-based GMPEs to provide more accurate and reliable estimates of the potential induced-seismicity ground motion hazard, allowing for better risk assessment and management strategies. To demonstrate this approach, a new set of GMPEs for the 2018-2019 induced seismicity sequence at the Preston New Road (PNR) shale gas site near Blackpool, United Kingdom, is presented. The physically-based GMPE was developed based on a pseudo-finite-fault stochastic ground motion simulation, calibrated with parameters derived from the spectral analysis of weak-motion records from induced seismic events. An optimization-based calibration technique using the area metric (AM) was subsequently performed to calibrate optimal parameters for simulating ground motion at the PNR site. Finally, using a suite of forward simulations for events with \(1 \le M \le 6\) recorded at distances up to 30 km, combined with empirical data, a location-specific GMPE was derived through adjustment of an existing model.
期刊介绍:
Journal of Seismology is an international journal specialising in all observational and theoretical aspects related to earthquake occurrence.
Research topics may cover: seismotectonics, seismicity, historical seismicity, seismic source physics, strong ground motion studies, seismic hazard or risk, engineering seismology, physics of fault systems, triggered and induced seismicity, mining seismology, volcano seismology, earthquake prediction, structural investigations ranging from local to regional and global studies with a particular focus on passive experiments.