Seismic feature extraction using steiner tree methods
Author(s)Schmidt, Ludwig; Hegde, Chinmay; Indyk, Piotr; Lu, Ligang; Chi, Xingang; Hohl, Detlef; ... Show more Show less
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Identifying “interesting” features, such as faults, unconformities, and other events in subsurface images is a challenging task in seismic data processing. Existing state-of-the-art methods usually involve manual intervention in the form of a visual inspection by an expert, but this is time-consuming, expensive, and error-prone. In this paper, we propose an efficient, automatic approach for seismic feature extraction. The core idea of our approach involves interpreting a given 2D seismic image as a function defined over the vertices of a specially chosen underlying graph. This enables us to formulate the feature extraction task as an instance of the Prize-Collecting Steiner Tree problem encountered in combinatorial optimization. We develop an efficient algorithm to solve this problem, and demonstrate the utility of our method on a number of synthetic and real examples.
DepartmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Institute of Electrical and Electronics Engineers (IEEE)
Schmidt, Ludwig, et al. "Seismic Feature Extraction Using Steiner Tree Methods." 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 19-24 April, Brisbane, Australia, 2015, IEEE, 2015, pp. 1647–51.