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Inicio  /  Geosciences  /  Vol: 8 Núm: 5 Par: May (2018)  /  Artículo
ARTÍCULO
TITULO

A Hybrid Empirical Green?s Function Technique for Predicting Ground Motion from Induced Seismicity: Application to the Basel Enhanced Geothermal System

Benjamin Edwards    
Nadine Staudenmaier    
Carlo Cauzzi and Stefan Wiemer    

Resumen

A method is described for the prediction of site-specific surface ground motion due to induced earthquakes occurring in predictable and well-defined source zones. The method is based on empirical Green?s functions (EGFs), determined using micro-earthquakes at sites where seismicity is being induced (e.g., hydraulic fracturing and wastewater injection during shale oil and gas extraction, CO2 sequestration, and conventional and enhanced geothermal injection). Using the EGF approach, a ground-motion field (e.g., an intensity map) can be calculated for a potentially felt induced event originating within the seismic zone. The approach allows site- and path-specific effects to be mapped into the ground-motion field, providing a local ground-motion model that accounts for wave-propagation effects without the requirement of 3D velocity models or extensive computational resources. As a test case, the ground-motion field for the mainshock (ML = 3.4, M = 3.2) resulting from the Basel Enhanced Geothermal System (EGS) was simulated using only seismicity recorded prior to the event. We focussed on peak ground velocity (PGV), as this is a measure of ground motion on which Swiss norms for vibration disturbances are based. The performance of the method was significantly better than a previously developed generic ground-motion prediction equation (GMPE) for induced earthquakes and showed improved performance through intrinsic inclusion of site-specific effects relative to predictions for a local GMPE. Both median motions and the site-to-site ground-motion variability were captured, leading to significantly reduced misfit relative to the generic GMPE. It was shown, however, that extrapolation beyond units of a couple of magnitude leads to significant uncertainty. The method is well suited to a real-time predictive hazard framework, for which shaking estimates are dynamically updated in light of newly recorded seismicity.

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