Cao, J. and Zhao, J., 2015. 3D seismic interpolation with a low redundancy, fast curvelet transform. Journal of Seismic Exploration, 24: 121-134. Seismic data interpolation is one of the main challenges encountered during pre-processing. It can provide reliable data for processes that require regular and dense sampling, like migration and multiple elimination. At present, a transform method which is based on the sparseness of signals in a transformed domain, is a commonly used strategy to get promising results. Among different transforms, the curvelet transform has optimal sparse expression for wave-fronts, thus it can be seen as a good candidate for seismic interpolation. However, the high redundancy of the 3D curvelet transform makes it computationally expensive, especially for massive data processing. Woiselle et al. (2011) proposed a new implementation of the curvelet transform, which reduces the redundancy to 10 for a 3D transform. In this paper, this new implementation is introduced to improve the computational efficiency of curvelet-based interpolation. The merits of the new implementation are discussed and the low redundancy is proven through numerical tests. Numerical results on 3D interpolation based on the new transform show that the CPU time it costs is about 1/4 of the original curvelet transform. Thus, the Woiselle’s curvelet transform is a good balance between redundancy, rapidity and performance.