Based on the existing materials of fault segmentation,characteristic earthquakes,and their empirical relationships,we calculated the parameters of the fault segments,such as length,width,magnitudes of characteristic e...Based on the existing materials of fault segmentation,characteristic earthquakes,and their empirical relationships,we calculated the parameters of the fault segments,such as length,width,magnitudes of characteristic earthquakes,etc.Constrained by GPS velocity field,the slip rates of these fault segments in depth were inversed using the 3-D half-space elastic dislocation model.As not all of the recurrence periods and co-seismic displacements of characteristic earthquakes are known,we selected the fault segments with these two parameters known and calculated the accumulation rate of average co-seismic displacement,which shows the faults' slip rate in seismogenic layer.Then,the slip rate in depth was compared with that in seismogenic layer,the relationship between them was obtained,and this relationship was used to get the recurrence periods and co-seismic displacements of all fault segments.After the studies above,we calculated the co-seismic deformation field of all the earthquakes larger than M s 6.8 from AD 1700 one by one and inversed the potential displacement in the co-seismic deformation field.Then,we divided the potential displacement by the slip rate from GPS inversion to get the influences of these fault segments,added the influences into the elapsed time of the characteristic earthquakes,and obtained the earthquake hazard degree of all the segments we studied in the form of the ratio of elapsed time to recurrence period;so,we name the ratio as the Impending Earthquake Risk (IER).Historical earthquake cases show that the fault segment is in safety when the IER is less than 1 but in danger after the IER becomes larger than 1.In 2009,the IER is larger than 1 on the following segments,1.35 on the Tagong segment of Xianshuihe fault,1 on the Menggu-Dongchuan segment,1.04 on the Dongchuan-Xundian segment,and 1.09 on the Yiliang-Chengjiang segment of Xiaojiang fault.展开更多
Anthropogenic induced seismicity has been widely reported and investigated in many regions,including the shale gas fields in the Sichuan basin,where the frequency of earthquakes has increased substantially since the c...Anthropogenic induced seismicity has been widely reported and investigated in many regions,including the shale gas fields in the Sichuan basin,where the frequency of earthquakes has increased substantially since the commencement of fracking in late 2014.However,the details of how earthquakes are induced remain poorly understood,partly due to lack of high-resolution spatial-temporal data documenting the evolution of such seismic events.Most previous studies have been based on a diffusive earthquake catalog constructed by routine methods.Here,however,we have constructed a high resolution catalog using a machine learning detector and waveform cross-correlation.Despite limited data,this new approach has detected one-third more earthquakes and improves the magnitude completeness of the catalog,illuminating the comprehensive spatial-temporal migration of the emerging seismicity in the target area.One of the clusters clearly delineates a potential unmapped fault trace that may have led to the Mw 5.2 in September 2019,by far the largest earthquake recorded in the region.The migration of the seismicity also demonstrates a pore-pressure diffusion front,suggesting additional constraints on the inducing mechanism of the region.The patterns of the highly clustered seismicity reconcile the causal link between the emerging seismicity and the activity of hydraulic fracturing in the region,facilitating continued investigation of the mechanisms of seismic induction and their associated risks.展开更多
基金supported by the National Basic Research Program of China (Grant No. 2008CB425704)the Open Foundation of State Key Laboratory of Earthquake Dynamics (Grant No. LED2009B02)
文摘Based on the existing materials of fault segmentation,characteristic earthquakes,and their empirical relationships,we calculated the parameters of the fault segments,such as length,width,magnitudes of characteristic earthquakes,etc.Constrained by GPS velocity field,the slip rates of these fault segments in depth were inversed using the 3-D half-space elastic dislocation model.As not all of the recurrence periods and co-seismic displacements of characteristic earthquakes are known,we selected the fault segments with these two parameters known and calculated the accumulation rate of average co-seismic displacement,which shows the faults' slip rate in seismogenic layer.Then,the slip rate in depth was compared with that in seismogenic layer,the relationship between them was obtained,and this relationship was used to get the recurrence periods and co-seismic displacements of all fault segments.After the studies above,we calculated the co-seismic deformation field of all the earthquakes larger than M s 6.8 from AD 1700 one by one and inversed the potential displacement in the co-seismic deformation field.Then,we divided the potential displacement by the slip rate from GPS inversion to get the influences of these fault segments,added the influences into the elapsed time of the characteristic earthquakes,and obtained the earthquake hazard degree of all the segments we studied in the form of the ratio of elapsed time to recurrence period;so,we name the ratio as the Impending Earthquake Risk (IER).Historical earthquake cases show that the fault segment is in safety when the IER is less than 1 but in danger after the IER becomes larger than 1.In 2009,the IER is larger than 1 on the following segments,1.35 on the Tagong segment of Xianshuihe fault,1 on the Menggu-Dongchuan segment,1.04 on the Dongchuan-Xundian segment,and 1.09 on the Yiliang-Chengjiang segment of Xiaojiang fault.
基金supported by the National Key R&D Program of China(2018YFC1504501)the Hong Kong Research Grants Council(No.14303721 and N_CUHK430/16)the Faculty of Science,CUHK。
文摘Anthropogenic induced seismicity has been widely reported and investigated in many regions,including the shale gas fields in the Sichuan basin,where the frequency of earthquakes has increased substantially since the commencement of fracking in late 2014.However,the details of how earthquakes are induced remain poorly understood,partly due to lack of high-resolution spatial-temporal data documenting the evolution of such seismic events.Most previous studies have been based on a diffusive earthquake catalog constructed by routine methods.Here,however,we have constructed a high resolution catalog using a machine learning detector and waveform cross-correlation.Despite limited data,this new approach has detected one-third more earthquakes and improves the magnitude completeness of the catalog,illuminating the comprehensive spatial-temporal migration of the emerging seismicity in the target area.One of the clusters clearly delineates a potential unmapped fault trace that may have led to the Mw 5.2 in September 2019,by far the largest earthquake recorded in the region.The migration of the seismicity also demonstrates a pore-pressure diffusion front,suggesting additional constraints on the inducing mechanism of the region.The patterns of the highly clustered seismicity reconcile the causal link between the emerging seismicity and the activity of hydraulic fracturing in the region,facilitating continued investigation of the mechanisms of seismic induction and their associated risks.
