(The Eurographics Association, 2006) Jeong, Won-Ki; Whitaker, Ross; Dobin, Mark; Raghu Machiraju and Torsten Moeller
This paper presents a 3D, volumetric, seismic fault detection system that relies on a novel set of nonlinear filters combined with a GPU (Graphics Processing Unit) implementation, which makes interactive nonlinear, volumetric processing feasible. The method uses a 3D structure tensor to robustly measure seismic orientations. These tensors guide an anisotropic diffusion, which reduces noise in the data while enhancing the fault discontinuity and coherency along seismic strata. A fault-likelihood volume is computed using a directional variance measure, and 3D fault voxels are then extracted through a non-maximal-suppression method. We also show how the proposed algorithms are efficiently implemented with a GPU programming model, and compare this to a CPU implementation to show the benefits of using the GPU for this computationally demanding problem.