Seismic feature extraction using steiner tree methods
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-consumin...
| Main Authors: | , , , , , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
Institute of Electrical and Electronics Engineers (IEEE)
2018
|
| Online Access: | http://hdl.handle.net/1721.1/113869 https://orcid.org/0000-0002-9603-7056 https://orcid.org/0000-0002-7983-9524 |
| _version_ | 1826205275226374144 |
|---|---|
| author | Schmidt, Ludwig Hegde, Chinmay Indyk, Piotr Lu, Ligang Chi, Xingang Hohl, Detlef |
| author2 | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science |
| author_facet | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Schmidt, Ludwig Hegde, Chinmay Indyk, Piotr Lu, Ligang Chi, Xingang Hohl, Detlef |
| author_sort | Schmidt, Ludwig |
| collection | MIT |
| description | 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. |
| first_indexed | 2024-09-23T13:10:07Z |
| format | Article |
| id | mit-1721.1/113869 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T13:10:07Z |
| publishDate | 2018 |
| publisher | Institute of Electrical and Electronics Engineers (IEEE) |
| record_format | dspace |
| spelling | mit-1721.1/1138692022-10-01T13:30:49Z Seismic feature extraction using steiner tree methods Schmidt, Ludwig Hegde, Chinmay Indyk, Piotr Lu, Ligang Chi, Xingang Hohl, Detlef Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Schmidt, Ludwig Hegde, Chinmay Indyk, Piotr 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. 2018-02-22T19:02:47Z 2018-02-22T19:02:47Z 2015-08 2015-04 Article http://purl.org/eprint/type/ConferencePaper 978-1-4673-6997-8 http://hdl.handle.net/1721.1/113869 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. https://orcid.org/0000-0002-9603-7056 https://orcid.org/0000-0002-7983-9524 en_US http://dx.doi.org/10.1109/ICASSP.2015.7178250 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Institute of Electrical and Electronics Engineers (IEEE) MIT Web Domain |
| spellingShingle | Schmidt, Ludwig Hegde, Chinmay Indyk, Piotr Lu, Ligang Chi, Xingang Hohl, Detlef Seismic feature extraction using steiner tree methods |
| title | Seismic feature extraction using steiner tree methods |
| title_full | Seismic feature extraction using steiner tree methods |
| title_fullStr | Seismic feature extraction using steiner tree methods |
| title_full_unstemmed | Seismic feature extraction using steiner tree methods |
| title_short | Seismic feature extraction using steiner tree methods |
| title_sort | seismic feature extraction using steiner tree methods |
| url | http://hdl.handle.net/1721.1/113869 https://orcid.org/0000-0002-9603-7056 https://orcid.org/0000-0002-7983-9524 |
| work_keys_str_mv | AT schmidtludwig seismicfeatureextractionusingsteinertreemethods AT hegdechinmay seismicfeatureextractionusingsteinertreemethods AT indykpiotr seismicfeatureextractionusingsteinertreemethods AT luligang seismicfeatureextractionusingsteinertreemethods AT chixingang seismicfeatureextractionusingsteinertreemethods AT hohldetlef seismicfeatureextractionusingsteinertreemethods |