This paper presents a method for triangular surface remeshing to obtain new faces whose edge lengths are as close as possible to a target value m. The process uses as input a 2-manifold mesh with arbitrary geometry and topology. The proposed algorithm runs iteratively, automatically adjusting the necessary amount of vertices, and applies a global relaxation process using a variation of Laplace-Beltrami discrete operator. We introduce geometry constraints in order to preserve salient features of the original model. The method results on a grid with edge lengths near to m with low standard deviation, i.e. the vertices are uniformly distributed over the original surface. The dual space of the final triangular surface results in a trivalent, mostly hexagonal mesh, suitable for several applications.
In this work we present a new method for seismic fault enhancement on volumetric grids called Minimal Similarity Accumulation (MSA). The seismic reflection data is transformed into a multi-dimensional amplitude space and a clustering procedure is applied in order to minimize the noise interference. Thereafter, we use an algorithm to compute the MSA for each voxel in the volume. This is done by applying an autoadaptable function that uses the voxel neighboring information. The MSA measurement globally highlights the fault regions presented in the original volume. To validate the proposed method we use the volume of the Netherlands offshore F3 block downloaded from the Open Seismic Repository. In order to assess the proposed method and illustrate it advantages, a set of vertical 2D slices of the seismic data are presented providing a comparison between our results and images manually interpreted by a geologist. Finally, we conclude that the proposed method is sufficiently accurate.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.