Abstract：Fractures, faults and geological body boundaries feature discontinuity in seismic data. Current boundary detection methods often lead to fuzzy boundary characteristics, poor integrity and low coherence due to noise, which increases the difficulty of geological interpretation. To tackle these problems, this paper proposes a seismic discontinuity enhancement method based on tensor voting. Firstly, the seismic geometric attributes are analyzed with eigenvalues and eigenvectors of gradient structure tensor to determine the seed points with geological structure characteristics. Then, the geo-logical structure characteristics are enhanced by the superposition of voting fields of seed points, and the discontinuous structure characteristics hidden in seismic attributes are excavated to improve the integrity of geological structure characteristics. Finally, the continuous and smooth feature skeleton is extracted by tensor decomposition. Model calculation results and field data prove that the tensor voting method can describe the fault feature information and retain the visually low-continuity fault information to the maximum extent, which makes the fault feature more complete, more continuous and clearer. The proposed method has good robustness and applicability, thus capable of being an effective tool for identifying geological body boundaries.
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