Seismic feature extraction using steiner tree methods
Name
Seismic feature.pdf
Size
1.73 MB
Format
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Checksum (MD5)
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Author(s)
Schmidt, Ludwig
Hegde, Chinmay
Indyk, Piotr
Lu, Ligang
Chi, Xingang
Hohl, Detlef
Date Issued
August 2015
Journal
2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
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.
Version
Original manuscript
Abstract
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.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/ICASSP.2015.7178250
