基于波动方程表面多次波预测与自适应相减方法研究

Surface-related multiples prediction based on wave equation and adaptive subtraction investigation

多次波预测与自适应相减是基于波动方程表面多次波压制的两个重要环节.文中利用具有并行计算优势的GPU加速表面多次波预测,使得预测效率大为提高.在自适应相减算法中,文中将预测的多次波道、预测多次波道的Hilbert变换道、预测多次波道的高频重建道、以及它们的平移道用作自适应相减中的多次波模型道.Hilbert变换道用以补偿预测多次波的相位信息,高频重建道用以改善预测多次波的高频信息,补偿频带能量差异.文中在预测和相减过程中均采用迭代算法,迭代预测,可较好地获得多次波的运动学特性,迭代相减,可较好地获得多次波的动力学特性,迭代预测与相减使预测的多次波与地震数据中实际的多次波更好地匹配.将该方法应用于理论模拟的SMAART模型和实际海洋数据中,测试结果表明,该方法预测多次波效率较高,在保持有效波振幅条件下可有效地压制地震数据中的表面多次波.

Multiples prediction and adaptive subtraction are two important links for waveequation-based surface-related multiples attenuation method. GPU with parallel computation advantage is exploited to accelerate surface-related multiples prediction, which improved calculation efficiency greatly. In adaptive subtraction algorithm, multiples modeling tracescontain predicted multiple trace, high-frequency reconstruction trace from predicted multiple trace, Hilbert transform trace from predicted multiple trace, and their translation trace. Hilbert transform trace will compensate phase information of multiples, and high-frequency reconstruction trace improves high-frequency information of predicted multiples, which compensate energy difference in frequency band. Iterative algorithms are used during prediction and subtraction. Iterative prediction improves kinematic properties and iterative subtraction improves dynamic properties, which make predicted multiples match actual multiples well. The proposed method is applied on theoretical SMAART model and raw marine data. The test results show that the method can predict multiples of seismic data efficiently, also suppress surfacerelated multiples without damaging primary effectively.