Image segmentation can be used to track salt boundaries when the salt boundary amplitude is greater than any other local reflections. We apply a modified version of the normalized cut image segmentation method to partition seismic images along salt boundaries. In principle our method should work even when the boundaries are not continuous, and conventional horizon tracking algorithms may fail. Our implementation of this method calculates a weight connecting each pixel in the image to each pixel in a local neighborhood. The weight is made weak where the negative amplitude of the complex trace along the shortest path between the two pixels has a minimum and is less than a threshold value. This method is demonstrated to be effective on synthetic 2D seismic sections and can easily be modified to be applied to 3D data. To overcome the formidable computational expense and storage requirements, three cost saving approaches are proposed. Firstly, pixels are sampled from windows centered at powers of 2, this greatly increases the sparseness of the weight matrix. Secondly, initial solutions are provided to subsequent segmentations for multiple segmentation passes in iterative velocity analysis. Thirdly, an iterative multi-scale approach should allow the tracking of the bright salt events in large 3D cubes.

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