首页|Slip distribution inversion of seismic sub-fault dip iteration using gradient based optimizer algorithm
Slip distribution inversion of seismic sub-fault dip iteration using gradient based optimizer algorithm
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国家科技期刊平台
NETL
NSTL
万方数据
This paper considers setting different dips for different sub-faults to fit the actual rupture situation based on the fault rupture of the 2013 Lushan MS7.0 earthquake.Meanwhile,combined with the coseismic GNSS data of the Lushan earthquake,the source parameters and sliding distribution of the Lushan earthquake fault are inversed.Firstly,we use the gradient based optimizer(GBO)in nonlinear inversion to obtain the source parameters of this seismic fault.The inversion results indicate that the strike of the fault is 206.52°,the dip is 44.10°,the length is 21.92 km,and the depth is 12.79 km.To refine the sliding distribution of the seismic fault,the seismic fault is divided into 3x3 sub-faults.Then,we fix the central sub-fault dip of 44.10°;the dip of other sub-faults is obtained by iteration.After that,the model is further divided into a fault layer model composed of 23 x 19 sub fault slices,and using the Matlab fitting function is used to fit the dip of the 23 x 19 sub faults.Finally,the Lushan seismic fault plane is established as a shovel structure with steep upper and gentle lower,steep south and gentle north.The slip distribution inversion results indicate that the depth of the slip peak is 13 km,the corresponding maximum slip momentum is 0.67 m,the seismic moment is 1.10 × 1019 N·m and the corresponding moment magnitude is Mw6.66.The results above are consistent with the research results of seismology.
Gradient based optimizer(GBO)Lushan earthquakeNon-plane fault modelSlid distribution
Leyang Wang、Han Li、Ming Pang
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Key Laboratory of Mine Environmental Monitoring and Improving Around Poyang Lake of Ministry of Natural Resources,East China University of Technology,Nanchang 330013,China
School of Surveying and Geoinformation Engineering,East China University of Technology,Nanchang 330013,China
College of Resources and Environment,Shandong Agricultural University,Taian 271018,China
国家科技期刊平台
NSTL
万方数据
