【摘要】 通过引入启动函数拓展传统的地层转换模型,在该模型中利用奇异性信息量化地层速度的过渡特征,并基于传统的褶积模型研究奇异性信息在波阻抗到合成地震记录之间的传递性。研究结果表明,地震记录中较好地保存了地层介质的奇异性特征,因此奇异性特征可以作为一种自然的、能够精确刻画地层边界的地震属性。基于单尺度分数高斯小波变换算法,将小波变换模极大值的消失或出现作为计算奇异性指数值的标准,追踪小波变换模极大值点,当模极大值趋于零时对应的分数高斯小波的阶数即为待求的H lder指数,据此提出了通过地震记录的奇异性信息来进行油气探测的方法。从四川盆地某气田地质模型及实际地震资料两个方面进行了论证研究,结果表明奇异性指数可作为油气检测的一个重要参考指标。图4参19更多还原

【Abstract】 The onset function is introduced to extend the traditional formation conversion model,and the singularity data is used to quantify the transit characteristics of the formation velocity.Moreover,the traditional convolution model is used to identify the transmission of the singularity data from acoustic impedance to composite seismogram.The singularity characteristics of formation medium are preserved in the seismogram and they can be considered as a natural seismic attribute that can delineate the formation boundaries accurately.With the mono-scale fractional-order Gaussian wavelet transformation algorithm,the wavelet transform modulus maximum points are traced by taking the disappearance or appearance of the maximum as the criterion for singularity index calculation.When the maximum approaches zero,the corresponding order number of fractional-order Gaussian wavelet is just the Hlder index desired.In this regard,it is proposed to detect the hydrocarbons with the singularity data of the seismogram.It is demonstrated with both the geologic model and the actual seismic data for a gas field in the Sichuan Basin,which shows that the singularity index can be considered as a key reference for hydrocarbon detection.更多还原