基于梯度平方结构张量算法的高密度二维立体层析反演

射线参数水平分量是立体层析数据空间中最为重要的参数信息,梯度平方结构张量算法是一种针对图像的边缘检测快速算法.本文将叠前地震数据集视为图像,将梯度平方结构张量算法用于射线参数水平分量的提取,提高了立体层析数据空间的准备效率.高效率的数据空间提取使得高密度立体层析反演成为可能,数据空间加密后的立体层析反演精度以及叠前深度成像质量相比常规流程得到明显提高.基于二维理论数据与南海某二维深水数据的严格测试证实了该方法的有效性与稳健性.

A high-density stereo-tomography method based on the gradient square structure tensors algorithm

The efficiency and effectiveness of the stereotomography is highly dependent on the quality of its data space, the so-called kinematic invariant. The structure tensor is a very robust tool for the slope estimation. In this paper, we present a highly efficient high-density kinematic invariant extraction method based on structure tensors. Compared with the conventional slope search methods, the presented technique can improve the computational efficiency by one or two orders of magnitudes which will greatly enhance the applicability of the stereomography.