Prestack nonstationary deconvolution based on variable-step sampling in the radial trace domain

径向道域变步长采样叠前非稳态反褶积处理方法研究(英文)

The conventional nonstationary convolutional model assumes that the seismic signal is recorded at normal incidence. Raw shot gathers are far from this assumption because of the effects of offsets. Because of such problems, we propose a novel prestack nonstationary deconvolution approach. We introduce the radial trace （RT） transform to the nonstationary deconvolution, we estimate the nonstationary deconvolution factor with hyperbolic smoothing based on variable-step sampling （VSS） in the RT domain, and we obtain the high-resolution prestack nonstationary deconvolution data. The RT transform maps the shot record from the offset and traveltime coordinates to those of apparent velocity and traveltime. The ray paths of the traces in the RT better satisfy the assumptions of the convolutional model. The proposed method combines the advantages of stationary deconvolution and inverse Q filtering, without prior information for Q. The nonstationary deconvolution in the RT domain is more suitable than that in the space-time （XT） domain for prestack data because it is the generalized extension of normal incidence. Tests with synthetic and real data demonstrate that the proposed method is more effective in compensating for large-offset and deep data.

传统的非稳态褶积模型假设地震波是垂直入射的,而实际接收到的XT域地震数据不能满足这一假设条件。针对该问题,本文采用径向道变换技术,使地震数据在RT域能够广义上满足该假设条件;同时采用变步长采样双曲光滑法求取了考虑地层吸收衰减影响的非稳态反褶积因子,从而使径向道域变步长采样叠前非稳态反褶积综合了常规反褶积和反Q滤波的优点,实现了高精度、高分辨叠前非稳态反褶积。理论模型和实际资料处理结果表明,与常规非稳态反褶积方法相比,径向道域变步长采样叠前非稳态反褶积结果具有更高的分辨率,同相轴具有更好的横向连续性,更能有效恢复远炮检距和深层的地震数据。