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Improved methods for detection and arrival picking of microseismic events with low signal-to-noise ratios

机译:具有低信噪比的微地震事件检测和到达拾取的改进方法

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Detection and arrival picking of microseismic events with low signal-to-noise ratios (S/N) are problematic because these events are usually obscured by ambient noise. We have developed an intraevent coherence-based event detection method to address this problem. The innovations of this method include the adaptation of a crosscorrelation, least-squares-based algorithm to achieve better moveout correction for successive record segments and the use of a multichannel semblance coefficient to identify the microseismic events. After finding the events, we adopted a new picker to determine their P- and S-wave arrival times. This picker was developed by combining three aspects of the distinction between seismic signal and ambient noise, namely, the (1) amplitude, (2) polarization, and (3) statistic property differences. We evaluated the performance of the proposed methods using a real data set recorded during an 11-stage hydraulic fracture stimulation. We have determined that, for microseismic event detection, the proposed method has an overall false trigger rate of 12%. As for arrival picking, the average picking error of the new picker is 1.33 x 103 s and its standard deviation is 1.79 x 103 s. Comparison of the results of different event detection and arrival picking methods versus the S/N of the data demonstrates that the proposed methods are more applicable for detection and arrival picking of low S/N microseismic events.
机译:具有低信噪比(S / N)的微地震事件的检测和到达选择是有问题的,因为这些事件通常会被环境噪声所掩盖。我们已经开发了一种基于事件内一致性的事件检测方法来解决此问题。该方法的创新之处在于:采用互相关,基于最小二乘的算法,以对连续的记录段实现更好的时差校正,并使用多通道相似系数来识别微地震事件。找到事件之后,我们采用了一个新的选择器来确定它们的P波和S波到达时间。通过结合地震信号和环境噪声之间的区别的三个方面(即(1)幅度,(2)极化和(3)统计特性差异)开发了该选择器。我们使用在11级水力压裂增产过程中记录的真实数据集评估了所提出方法的性能。我们已经确定,对于微地震事件检测,所提出的方法的总体误触发率为12%。至于进货拣货,新拣货机的平均拣货误差为1.33 x 103 s,其标准偏差为1.79 x 103 s。比较不同事件检测和到达拾取方法的结果与数据的信噪比,表明所提出的方法更适用于低信噪比微地震事件的检测和到达拾取。

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