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面波是陆地地震勘探数据的主要噪声,掩盖了地震记录中的有效波信号.常用的面波压制方法根据频率或视速度的差异将面波从有效波信号中分离出来并进行压制,但当差异不很明显时,难以取得较好的压制效果.鉴于目前基于地震干涉的方法只能得到检波点间的面波,文章提出使用数据驱动的超虚干涉法预测面波,该方法可以直接得到炮检点间面波,不要求检波点附近存在真实炮点用于实现面波的自适应相减.针对非均匀近地表结构产生的强频散面波,发展了自适应加权的超虚干涉法(AWSVI),提高了对频散面波的预测精度.合成数据实例验证了AWSVI方法预测强频散面波的有效性和对复杂地表情况的适用性.AWSVI方法应用在中国东部地区的实际陆地地震资料,相比常规的面波压制方法,更好地压制了残余面波.
Surface waves are the main noise of terrestrial seismic exploration data and cover the effective wave signals in seismic records.A common surface wave suppression method separates and suppresses surface waves from effective wave signals according to the difference of frequency or apparent velocity, When the difference is not obvious, it is difficult to get a better suppression effect.While the current methods based on seismic interference can only get the surface waves between the detection points, the paper proposes to use the data-driven super-virtual interference method to predict surface waves, which can be directly obtained It is not necessary to have a real shot near the detection point for the adaptive subtraction of surface waves.For the strong SAW generated by the non-uniform near-surface structure, an adaptive weighted super-virtual interference method is developed (AWSVI) to improve the prediction accuracy of dispersion surface wave.Examples of synthetic data validate the validity of AWSVI method in predicting strong SAW and its applicability to complex surface conditions.The AWSVI method is applied to the actual land area in eastern China Seismic data, compared with the conventional surface wave suppression method, to better suppress the residual surface wave.