Estimation of ambient seismic source distributions (e.g. location and strength) can aid studies of seismic source mechanisms and subsurface structure investigations. One can invert for the ambient seismic (noise) source distribution by applying full-waveform inversion (FWI) theory to seismic (noise) crosscorrelations. This estimation method is especially applicable for seismic recordings without obvious body-wave arrivals. Data pre-processing procedures are needed before the inversion, but some pre-processing procedures commonly used in ambient noise tomography can bias the ambient (noise) source distribution estimation and should not be used in FWI. Taking this into account, we propose a complete workflow from the raw seismic noise recording through pre-processing procedures to the inversion. We present the workflow with a field data example in Hartoušov, Czech Republic, where the seismic sources are CO₂ degassing areas at Earth’s surface (i.e. a fumarole or mofette). We discuss factors in the processing and inversion that can bias the estimations, such as inaccurate velocity model, anelasticity and array sensitivity. The proposed workflow can work for multicomponent data across different scales of field data.

中文翻译：

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基于瑞利波多分量互相关的源强度分布反演。第2部分：现场地震数据的工作流程

估计周围地震源的分布（例如位置和强度）可以帮助研究地震源机制和地下结构。通过将全波形反演（FWI）理论应用于地震（噪声）互相关，可以反演周围地震（噪声）源的分布。该估计方法尤其适用于没有明显体波到达的地震记录。反演之前需要数据预处理程序，但是环境噪声层析成像中常用的一些预处理程序可能会偏向环境（噪声）源分布估计，因此不应在FWI中使用。考虑到这一点，我们提出了一个完整的工作流程，从原始地震噪声记录到预处理程序再到反演。地球表面的_2个脱气区域（即喷气孔或莫夫特膜）。我们讨论了在处理和反演中可能会使估计值产生偏差的因素，例如不正确的速度模型，无弹性和阵列灵敏度。拟议的工作流程可以适用于跨不同规模的现场数据的多组分数据。