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A moment tensor inversion approach based on the correlation between defined functions and waveforms
Physics of the Earth and Planetary Interiors ( IF 2.3 ) Pub Date : 2021-02-09 , DOI: 10.1016/j.pepi.2021.106674
Yue Kong , Min Li , Weimin Chen , Ning Liu , Boqi Kang

The moment tensor inversion is a commonly-used method to interpret source mechanisms of microseismicity. In the inversion for real data (e.g. microseismicity recorded during hydraulic fracturing), the waveforms recorded by sensors can be the mixtures of signals and noise, or the superposition of signals generated by multiple sources. Then the traditional approach may result in inaccurate solutions. In this article, we developed a new inversion approach based on the correlation between waveforms and correlation functions, which are defined based on the characteristics of signals. The correlation function determined by specific parameters is more sensitive to the signal generated by a specific source, and less sensitive to noise or signals generated by other sources. Then the correlation coefficient calculated by multiplying the waveform and correlation function is mainly determined by the signal. The moment-tensor solutions calculated by the correlation coefficients are more accurate. The new inversion approach was evaluated by synthetic tests. For noise filtering, compared with tradition inversion approaches, the new approach can improve the inversion accuracy by more than 50% at various noise levels. For multiple sources discrimination, the new approach can discriminate signals generated by multiple sources and provide more accurate inversion results for the sources simultaneously, but the application of the method is limited. This new inversion approach aims to provide accurate solutions in a very simple way, when the waveforms are distorted.



中文翻译:

基于已定义函数和波形之间相关性的矩张量反转方法

矩张量反演是解释微地震震源机制的常用方法。在对真实数据(例如,水力压裂过程中记录的微地震)进行反演时,传感器记录的波形可以是信号和噪声的混合,也可以是多个源生成的信号的叠加。然后,传统方法可能会导致解决方案不准确。在本文中,我们基于波形和相关函数之间的相关性开发了一种新的反演方法,这些函数是根据信号的特性定义的。由特定参数确定的相关函数对特定源生成的信号更敏感,而对噪声或其他源生成的信号更不敏感。然后,主要由信号确定通过将波形与相关函数相乘而计算出的相关系数。由相关系数计算出的矩张量解更准确。通过综合测试评估了新的反演方法。对于噪声滤波,与传统的反演方法相比,新方法可以在各种噪声水平下将反演精度提高50%以上。对于多源判别,新方法可以判别多个源产生的信号,并同时为各源提供更准确的反演结果,但该方法的应用受到限制。这种新的反演方法旨在在波形失真时以非常简单的方式提供准确的解决方案。由相关系数计算出的矩张量解更准确。通过综合测试评估了新的反演方法。对于噪声滤波,与传统的反演方法相比,新方法可以在各种噪声水平下将反演精度提高50%以上。对于多源判别,新方法可以判别多个源产生的信号,并同时为各源提供更准确的反演结果,但该方法的应用受到限制。这种新的反演方法旨在在波形失真时以非常简单的方式提供准确的解决方案。由相关系数计算出的矩张量解更准确。通过综合测试评估了新的反演方法。对于噪声滤波,与传统的反演方法相比,新方法可以在各种噪声水平下将反演精度提高50%以上。对于多源判别,新方法可以判别多个源产生的信号,并同时为各源提供更准确的反演结果,但该方法的应用受到限制。这种新的反演方法旨在在波形失真时以非常简单的方式提供准确的解决方案。与传统的反演方法相比,新方法可以在各种噪声水平下将反演精度提高50%以上。对于多源判别,新方法可以判别多个源产生的信号,并同时为各源提供更准确的反演结果,但该方法的应用受到限制。这种新的反演方法旨在在波形失真时以非常简单的方式提供准确的解决方案。与传统的反演方法相比,新方法可以在各种噪声水平下将反演精度提高50%以上。对于多源判别,新方法可以判别多个源产生的信号,并同时为各源提供更准确的反演结果,但该方法的应用受到限制。这种新的反演方法旨在在波形失真时以非常简单的方式提供准确的解决方案。

更新日期:2021-02-21
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