Salt domes, an important geological structure, are closely related to the formation of petroleum reservoirs. In many cases, no explicit strong reflector exists between a salt dome and neighboring geological structures. Therefore, interpreters commonly delineate the boundaries of salt domes by observing a change in texture content. To stimulate the visual interpretation process, we propose a novel seismic attribute, the gradient of textures, which can quantify texture variations in three-dimensional (3D) space. On the basis of the attribute volume, we apply a global threshold to highlight regions containing salt-dome boundaries. In addition, with region growing and morphological operations, we can remove noisy boundaries and detect the boundary surfaces of salt domes effectively and efficiently. Experimental results show that by utilizing the strong coherence between neighboring seismic sections, the proposed method can delineate the surfaces of saltdome boundaries more accurately than the state-of-the-art detection methods that label salt-dome boundaries only in twodimensional (2D) seismic sections.

We propose a texture-based interpretation workflow and apply it to delineate salt domes in 3D migrated seismic volumes. First, we compute an attribute map using a novel seismic attribute, 3D gradient of textures (3D-GoT), which measures the dissimilarity between neighboring cubes around each voxel in a seismic volume across the time or depth, crossline, and inline directions. To evaluate the texture dissimilarity, we introduce five 3D perceptual and nonperceptual dissimilarity functions. Second, we apply a global threshold on the 3D-GoT volume to yield a binary volume and demonstrate its effects on salt-dome delineation using objective evaluation measures such as receiver operating characteristic curves and the areas under the curves. Third, with an initial seed point selected inside the binary volume, we use a 3D region growing method to capture a salt body. For an automated 3D region growing, we adopt a tensor-based automatic seed point selection method. Finally, we apply morphological postprocessing to delineate the salt dome within the seismic volume. Furthermore, we also develop an objective evaluation measure based on the curvature and shape to compute the similarity between detected salt-dome boundaries and the reference interpreted by the geophysicist. Experimental results on a real data set from the North Sea show that the proposed method outperforms the state-of-the-art methods for salt-dome delineation.

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