Method 1 seems to be the most elegant and efficient. For all methods, the biggest problem is posed by large gaps in the data coverage which would still need to be filled in with interpolated traces. A minimum trace density, related to the minimum spatial wavelength present in the data, must be maintained. The recent advances in interpolation methods of nonuniformly sampled data () can be instrumental in this respect. Even with interpolation, the number of fill-in traces required will be smaller for an unconstrained mesh than that in the case of a Cartesian mesh. This is due to the Cartesian lattices not being the best at filling space; the same area can be covered by fewer traces placed on a quasi-regular triangular mesh. This at least should offset the burden of node number bookkeeping for an unstructured mesh. Large coverage gaps can be covered using the boundary element method. This method was created with the specific goal of not having to deal with very large numbers of elements inside a domain - its elements are only on the border of the domain. Another solution may be presented by the finite element method (), which naturally handles unstructured meshes.