Interpreting 3D seismic volumes can be an intensive and time-consuming endeavor. Algorithms that provide additional information and expedite this process can therefore be useful tools for the interpreter. To further this goal, an algorithm that gives a topographic perspective of seismic data is described. After applying the continuous wavelet transform to the data, templates having a directional orientation are constructed locally in the complex wavelet domain for a number of scales. For each scale, a complex matrix is formed having real and imaginary parts, which are independently designed for a specific purpose and then combined to produce the final result. Whereas the composition of the real matrix is not well suited for dealing with the topographic aspect of the data, the imaginary matrix is. Using basic concepts from graph theory, the imaginary matrix is constructed to reveal the topographic nature of the underlying data. To a limited extent, dip scans provide similar results. Nonetheless, comparisons with dip scans reveal significant differences in the final results and computational efficiency. Although the general features seem to be similar, detailed features appear to be missing from the dip scan results. For the dip scans, semblance is measured over a number of dips and the highest value is used to determine the dip. The computational cost can vary, depending on factors such as the number of dips tested and implementation, but a comparison indicates that dip scans can be computationally more costly. In contrast, the algorithm to be described uses a single suite of wavelets convolved with the data to produce a number of scale-dependent complex matrices that are summed in a specific way. Furthermore, convolutions may be performed in the frequency domain. This reduces the computational cost, making this algorithm an effective and relatively fast interpretation tool.