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地震数据体中非正常地震道的识别一直是由人工进行分析的,如何快速而有效地识别和评价非正常地震道已经成为地震采集质量监控面临的重要问题。通过对地震道时窗能量特征和数据分数维的研究,提出了初至前是否起跳、极性反转、最大振幅异常、平均振幅异常、工业干扰道和主频异常等6种非正常地震道的自动识别方法和整体采集质量区域分布属性的评价方法,并开发了相应的软件系统。济阳坳陷纯化地区三维地震数据非正常地震道的自动识别和评价应用,提高了评价质量和工作效率,避免了一些人为感觉误差等因素的影响,同时展示了非正常地震道的分布情况,从而实现了地震采集数据由人工定性主观评价向自动定量客观评价的转变。
The identification of abnormal seismic traces in seismic data has always been manually analyzed. How to identify and evaluate abnormal seismic traces quickly and effectively has become an important issue for seismic acquisition quality monitoring. Based on the research on the energy characteristics and data fractal dimension of time windows of seismic traces, six kinds of unusual seismic traces, such as whether to take off before the first arrival, polarity reversal, maximum amplitude anomaly, average amplitude anomaly, industrial disturbance channel and dominant frequency anomaly Automatic identification method and the overall collection quality of the regional distribution of the evaluation method, and the development of the corresponding software system. The automatic identification and evaluation of abnormal seismic traces of 3D seismic data in the purified area of Jiyang Depression improve the evaluation quality and work efficiency and avoid some human factors such as the perception error and the distribution of abnormal seismic traces. Thus, the seismic data collection can be changed from artificial qualitative subjective evaluation to automatic quantitative objective evaluation.