Accelerating Curvature Attributes on GPUs

Curvature attributes have been widely used for visualization of folds, flexures, faults, collapse features, among others interesting features in seismic data. This work presents a parallel approach to compute volumetric curvature attributes for seismic data on GPU and CPU (sequential and parallel). We compare the results using different derivative operator size for sequential and the parallel approaches. The results show that for high derivative operator size the parallel approach performed on GPU can achieve further speed up than the other approaches. Also, using the proposed GPU approach, it is possible to visualize volume sections in interaction time.