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结合传统台网反演方法和反投影方法的各自优点,本文提出了一种通过近场全波形数据的迭代反褶积与叠加(IDS)方法来反演地震破裂过程。这种新方法不需要引入或调整反演限制性条件,如给定破裂时间、持续时间以及光滑约束权重等,因此能够对复杂破裂过程进行自动成像。在2008年汶川地震和2011年日本东北地区地震的应用研究中,迭代反褶积与叠加方法显示了相对于传统反演方法在稳定性和效率方面的优势。此外,合成数据测试也证实了迭代反褶积与叠加方法的稳健性和高效性,表明其对海啸早期预警及地震应急响应有重要价值。迭代反褶积与叠加方法还可以用于远震波形反演。对上述两个大地震的应用研究证实,采用迭代反褶积与叠加方法,可以在无需物理和经验约束的前提下,自动反演远震数据,并得到与近场全球定位系统(GPS)资料和强震数据反演结果相一致的破裂模型。
Combining the advantages of traditional stationarray inversion methods and backprojection methods, this paper presents a method of inversion of seismic rupture by iterative deconvolution and overlay (IDS) methods of near-field and full-wave data. This new method can automatically image the complex rupture process without introducing or adjusting the inversion restrictive conditions, such as the given rupture time, the duration and the smooth constraint weight. In the application of the 2008 Wenchuan earthquake and the 2011 northeast earthquake in Japan, the iterative deconvolution and superposition methods show the advantages of stability and efficiency over traditional inversion methods. In addition, the synthetic data test also confirmed the robustness and high efficiency of iterative deconvolution and superposition methods, indicating that it is of great value to early warning of tsunami and earthquake emergency response. Iteration deconvolution and stacking methods can also be used for teleseismic waveform inversion. The application of the above-mentioned two large earthquakes confirms that using the method of iterative deconvolution and stacking can automatically retrieve teleseismic data without the need of physical and empirical constraints, and obtain the data of near-field global positioning system (GPS) And the strong earthquake data inversion results consistent with the rupture model.