微地震事件初至拾取SLPEA算法
发布时间：2019-06-09 22:26
【摘要】：微地震事件初至拾取是微地震数据处理的关键步骤之一.实际微地震监测资料中存在大量低信噪比事件,而传统方法对这些事件的应用效果并不理想.为了克服传统方法抗噪性弱的缺点,本文通过综合地震信号与环境噪声在振幅、偏振以及统计特征等方面的存在的差异,设计了一种针对低信噪比微地震事件的初至拾取方法——SLPEA算法.为了检验本文方法的可行性和有效性,分别对模型数据和实际资料进行了处理,并将处理结果与传统方法及手工拾取的结果进行了对比.分析表明,利用本文方法得到的初至到时与手工拾取结果的绝对误差平均值仅为1.33×10~(-3)s,小于3个采样点;方差为3.21×10~(-6)s~2;初至到时在手工拾取结果±0.005s误差范围内的个数占总数的95.8%.这些参数值均优于传统方法的同类参数,证明了本文方法的可靠性.
[Abstract]:Picking up the first arrival of microseismic events is one of the key steps in microseismic data processing. There are a large number of low signal-to-noise ratio (SNR) events in the actual microseismic monitoring data, but the application effect of traditional methods on these events is not ideal. In order to overcome the disadvantage of weak anti-noise of traditional methods, this paper synthesizes the differences between seismic signal and environmental noise in amplitude, polarization and statistical characteristics. A SLPEA algorithm is designed to pick up the first arrival of microseismic events with low signal-to-noise ratio (SNR). In order to test the feasibility and effectiveness of the proposed method, the model data and the actual data are processed respectively, and the processing results are compared with the traditional methods and the results picked up by hand. The analysis shows that the average absolute error between the first arrival and manual picking results obtained by this method is only 1.33 脳 10 ~ (- 3) s, which is less than 3 sampling points, and the variance is 3.21 脳 10 ~ (- 6) s 鈮，
本文编号：2495945
[Abstract]:Picking up the first arrival of microseismic events is one of the key steps in microseismic data processing. There are a large number of low signal-to-noise ratio (SNR) events in the actual microseismic monitoring data, but the application effect of traditional methods on these events is not ideal. In order to overcome the disadvantage of weak anti-noise of traditional methods, this paper synthesizes the differences between seismic signal and environmental noise in amplitude, polarization and statistical characteristics. A SLPEA algorithm is designed to pick up the first arrival of microseismic events with low signal-to-noise ratio (SNR). In order to test the feasibility and effectiveness of the proposed method, the model data and the actual data are processed respectively, and the processing results are compared with the traditional methods and the results picked up by hand. The analysis shows that the average absolute error between the first arrival and manual picking results obtained by this method is only 1.33 脳 10 ~ (- 3) s, which is less than 3 sampling points, and the variance is 3.21 脳 10 ~ (- 6) s 鈮，
本文编号：2495945
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