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Refinement of arrival-time picks using a cross-correlation based workflow

机译:使用基于互相关的工作流程优化到达时间选择

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We propose a new iterative workflow based on cross-correlation for improved arrival-time picking on microseismic data. In this workflow, signal-to-noise ratio (S/N) and polarity weighted stacking are used to minimize the effect of S/N and polarity fluctuations on the pilot waveform computation. We use an exhaustive search technique for polarity estimation through stack power maximization. We use pseudo-synthetic and real microseismic data from western Canada in order to demonstrate the effectiveness of proposed workflow relative to Akaike information criterion (AIC) and a previously published cross-correlation based method. The pseudo-synthetic microseismic waveforms are obtained by introducing Gaussian noise and polarity fluctuations into waveforms from a high S/N microseismic event. We find that the cross-correlation based approaches yield more accurate arrival time picks as compared to AIC for low S/N waveforms. AIC is not affected by waveform polarities as it works on individual receiver levels whereas the accuracy of existing cross-correlation method decreases in spite of using envelope correlation. We show that our proposed workflow yields better and consistent arrival-time picks regardless of waveform amplitude and polarity variations within the receiver array. After refinement, the initial arrival-time picks are located closer to the best estimated manual picks. (C) 2016 Elsevier B.V. All rights reserved.
机译:我们提出了一种基于互相关的新的迭代工作流程,以改进微地震数据的到达时间选择。在此工作流程中,使用信噪比(S / N)和极性加权叠加来最小化S / N和极性波动对导频波形计算的影响。我们使用穷举搜索技术通过堆栈功率最大化进行极性估计。我们使用来自加拿大西部的伪合成和真实微地震数据,以证明相对于Akaike信息标准(AIC)和先前发布的基于互相关方法的拟议工作流程的有效性。伪合成微地震波形是通过将高斯噪声和极性波动引入来自高S / N微地震事件的波形中而获得的。我们发现,对于低S / N波形,与AIC相比,基于互相关的方法可产生更准确的到达时间选择。 AIC在单个接收器电平上工作时不受波形极性的影响,而尽管使用包络相关,但现有互相关方法的准确性下降。我们证明,无论接收器阵列中的波形幅度和极性如何变化,我们提出的工作流程都能产生更好且一致的到达时间选择。经过优化后,初始到达时间选择会更接近最佳估计的手动选择。 (C)2016 Elsevier B.V.保留所有权利。

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