论文详情
地震数据采集时受地表因素影响常常变观,使得炮检点分布不规则,影响了振幅特征的一致性,不利于后续的叠前属性分析及储层预测。为此提出了基于压缩傅里叶插值算法的数据规则化技术,在插值位置对不同空间带宽波数进行扫描,优选出满足均方根误差条件的最大空间波数,用于计算插值权系数。为了提高插值结果的振幅一致性,插值时考虑了纵向、横向、炮检距、方位角和时间等五个维度的信息,并增加了局部倾角校正处理以提高插值的抗假频能力。利用该技术对某工区不规则地震数据进行了五维插值规则化处理,处理后的地震数据不仅具有规则的炮检点分布,而且提高了覆盖次数的均匀性。对比分析了五维插值前后地震数据的振幅特征,结果表明,基于压缩傅里叶算法的五维插值技术可以很好地降低不规则炮检点分布对振幅特征的影响,提高了振幅的一致性。
Irregular distribution of sources and receivers owing to topography in seismic acquisition can cause reflection amplitude consistency,greatly impacting the follow-up pre-stack attribute analysis and reservoir prediction.Therefore,a five-dimensional interpolation technique based on the compact Fourier algorithm for seismic data regularization is proposed.The technique optimally selects a maximum spatial wavenumber with a root mean square error that meets the set minimum threshold via scanning to calculate the required interpolation weight coefficient.The technique accounts for inline,crossline,offset,azimuth,and time information to improve the consistency of the amplitude after interpolation,and introduces a local dip moveout to improve the anti-aliasing ability.Irregular seismic field data tests showed that,after regularization,the sources and receivers could distribute regularly and the uniformity of the fold and consistency of seismic amplitude were both improved,validating the proposed technique.
江苏石油勘探局科技项目“苏北盆地中浅层气藏地震处理及检测方法研究”项目(JS17005)资助。