地震数据倾角约束的多道谱反演算法

Multichannel spectral inversion with dip regularization

反射系数反演是联结地下储层和地震数据的桥梁,奇偶分解算法的出现使得子波间调谐效应减弱,这使得基于压缩感知的谱反演得到进一步应用.由于谱反演算法的不稳定性,所得到的反射系数横向连续性较差.因此,提出叠后地震数据倾角约束的多道谱反演算法,算法认为地震数据沿倾角方向具有一定连续性,在常规单道谱反演的基础上,推导了多道谱反演算法,基于局部倾角增加沿地层倾向的平滑约束,解决大角度地层反演横向连续性差的问题.算法继承了谱反演的高分辨率特性,并且有效增强了横向连续性,适用于地震数据的反射系数反演.模型和实际数据测试证明了倾角约束的多道谱反演算法得到的反演结果不仅能识别薄层,还能保持原始地层模型的横向连续性特征,并且具有一定的抗噪性,为地震地层学精细解释提供依据.

Reflectivity inversion is a bridge connecting underground reservoirs and seismic data.The odd-even decomposition algorithm has weakened the wavelet tuning effect,which makes the spectral inversion based on compressive sensing further applied.Because of the instability of the spectral inversion algorithm,the lateral continuity of the inversion reflectivity is poor.Therefore,assuming that there exists the continuity along dip direction,we propose a post-stack multichannel spectral inversion algorithm with dip constraint.Based on the conventional single-channel spectral inversion,we first derived the multichannel spectral inversion algorithm and introduced the L2 norm constraint along the dip direction,which addresses the poor lateral continuity in inversion of the large-dip stratum.The algorithm inherits the high-resolution characteristics of conventional spectral inversion and the robustness of sparse spiking deconvolution,suitable for reflectivity inversion of seismic data.The applications of synthetic and field data demonstrate that the multichannel spectral inversion algorithm with dip regularization can identify the thin-bed structure,maintain the lateral continuity of the original stratigraphic,and with noise resistance,providing a basis for precise seismic interpretation.