Summary Passive source location estimation technology plays an extremely important role in microseismic monitoring. However, the energy of microseismic signals is generally weak and prone to be interrupted as noise, which will affect the detection and location accuracy of microseismic events. Besides, the existing wave-equation-based source location estimation methods are not suitable for strongly heterogeneous strata, such as faults, salt bodies, fractures filled with proppant and other fluids, etc. These complex geological structures often trigger scattered waves. Thus, based on scattering theory, a high-resolution microseismic source location estimation method with a new grouping imaging condition is proposed by implementing a contrast source numerical simulation method in the process of wavefield backpropagation. First, the contrast source algorithm is used to perform wavefield extrapolation by solving the Helmholtz equation in the frequency domain, which can provide more comprehensive, effective information to get high-precision locations. Moreover, an optimized grouping imaging condition is proposed, which can improve the imaging resolution and computational efficiency. The effectiveness of the method we propose is illustrated using numerical examples. Compared with traditional source location estimation methods, including with low signal-to-noise ratio or multi-source location estimation, this method results in strong energy focusing achieved in an effecient manner.

中文翻译：

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基于对比震源算法的高分辨率微震震源定位方法

总结 无源震源定位估计技术在微震监测中发挥着极其重要的作用。但是，微震信号的能量普遍较弱，容易被噪声干扰，影响微震事件的探测和定位精度。此外，现有的基于波动方程的震源定位估计方法不适用于强非均质地层，如断层、盐体、充满支撑剂等流体的裂缝等，这些复杂的地质构造往往会引发散射波。为此，基于散射理论，通过在波场反向传播过程中实施对比震源数值模拟方法，提出了一种新的分组成像条件下的高分辨率微震震源定位估计方法。第一的，对比源算法用于在频域求解亥姆霍兹方程进行波场外推，可以提供更全面、更有效的信息以获得高精度位置。此外，提出了一种优化的分组成像条件，可以提高成像分辨率和计算效率。我们提出的方法的有效性通过数值例子来说明。与传统的源位置估计方法相比，包括低信噪比或多源位置估计，该方法可以有效地实现强能量聚焦。获取高精度位置的有效信息。此外，提出了一种优化的分组成像条件，可以提高成像分辨率和计算效率。我们提出的方法的有效性通过数值例子来说明。与传统的源位置估计方法相比，包括低信噪比或多源位置估计，该方法可以有效地实现强能量聚焦。获取高精度位置的有效信息。此外，提出了一种优化的分组成像条件，可以提高成像分辨率和计算效率。我们提出的方法的有效性通过数值例子来说明。与传统的源位置估计方法相比，包括低信噪比或多源位置估计，该方法可以有效地实现强能量聚焦。