Microseismic monitoring provides important information on the locations and moment tensors of microseismic events, and this information can be used to understand the behaviour of the fractures more completely. Characterisations of fractures are used to investigate flow paths and for noninvasive investigation of shale gas sites, geothermal developments, and radioactive waste storage/disposal sites. The locations of microseismic events can be used to estimate the geometry and distribution of fractures and faults, and the moment tensors provide information on the orientations of fracture planes and event magnitudes. We propose an effective fracture network imaging method using microseismic event locations and their moment tensors. For this purpose, the conventional Random Sample Consensus (RANSAC) method was improved so that fracture planes could be extracted quickly and efficiently from point cloud data. In addition, through the application of Density-Based Spatial Clustering of Applications with Noise (DBSCAN) to the microseismic event location data and moment tensor information, the accuracies of the locations and the orientations of fracture planes were improved. The developed algorithm was applied to synthetic data, including event locations and noise errors. The results showed that the developed method could extract the fracture planes reliably. Furthermore, the input parameters used in the proposed algorithm were examined, and the results of the conventional RANSAC method and the developed algorithm were compared. Finally, our method was applied to microseismic field data obtained from a shale gas/oil play, and the result accurately depicted the dominant strike of fracture planes.

中文翻译：

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使用微地震事件的位置和矩张量对离散裂缝网络进行成像

微震监测提供了微震事件发生的位置和矩张量的重要信息，利用这些信息可以更全面地了解裂缝的行为。裂缝的特征用于研究流动路径和页岩气场地、地热开发和放射性废物储存/处置场地的无创调查。微震事件的位置可用于估计裂缝和断层的几何形状和分布，而矩张量提供有关裂缝平面方向和事件震级的信息。我们提出了一种使用微震事件位置及其矩张量的有效裂缝网络成像方法。以此目的，改进了传统的随机样本一致性（RANSAC）方法，以便可以从点云数据中快速有效地提取断裂面。此外，通过将基于密度的噪声应用空间聚类（DBSCAN）应用于微震事件位置数据和矩张量信息，提高了位置和断裂面方向的准确性。开发的算法应用于合成数据，包括事件位置和噪声错误。结果表明，所开发的方法能够可靠地提取断裂面。此外，还检查了所提出算法中使用的输入参数，并比较了传统 RANSAC 方法和开发算法的结果。最后，