Deblending random seismic sources via independent component analysis
We consider the question of deblending for seismic shot records generated from simultaneous random sources at different locations, i.e., how to decompose them into isolated records involving one source at a time. As an example, seismic-while-drilling experiments use active drill-string sources and r...
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| Format: | Article |
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Society of Exploration Geophysicists
2018
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| Online Access: | http://hdl.handle.net/1721.1/116240 https://orcid.org/0000-0001-7052-5097 https://orcid.org/0000-0002-5872-8307 |
| _version_ | 1811091816193196032 |
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| author | Pisupati, Pawan Bharadwaj Demanet, Laurent Fournier, Aime |
| author2 | Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences |
| author_facet | Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences Pisupati, Pawan Bharadwaj Demanet, Laurent Fournier, Aime |
| author_sort | Pisupati, Pawan Bharadwaj |
| collection | MIT |
| description | We consider the question of deblending for seismic shot records generated from simultaneous random sources at different locations, i.e., how to decompose them into isolated records involving one source at a time. As an example, seismic-while-drilling experiments use active drill-string sources and receivers to look around and ahead of the borehole, but these receivers also record noise from the operation of the drill bit. A conventional method for deblending is independent component analysis (ICA), which assumes a “cocktail-party” mixing model where each receiver records a linear combination of source signals assumed to be statistically independent, and where only one source can have a Gaussian distribution. In this note, we extend the applicability of ICA to seismic shot records with markedly more complex mixing models with unknown wave kinematics, provided the following assumptions are met.
1. The active source is fully controllable, which means that it can be used to input a wide range of non-Gaussian random signals into the subsurface.
2. The waves are a linear function of the source, have a finite speed of propagation, and follow finite-length paths.
The last assumption implies a scale separation, in frequency, between the mixing matrix elements (Green’s functions) and the random input signals. In this regime, we show that the key to the success of ICA is careful windowing to frequency bands over which the Green’s functions are approximately constant. |
| first_indexed | 2024-09-23T15:08:29Z |
| format | Article |
| id | mit-1721.1/116240 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T15:08:29Z |
| publishDate | 2018 |
| publisher | Society of Exploration Geophysicists |
| record_format | dspace |
| spelling | mit-1721.1/1162402022-10-02T00:51:25Z Deblending random seismic sources via independent component analysis Pisupati, Pawan Bharadwaj Demanet, Laurent Fournier, Aime Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences Massachusetts Institute of Technology. Department of Mathematics Pisupati, Pawan Bharadwaj Demanet, Laurent Fournier, Aime We consider the question of deblending for seismic shot records generated from simultaneous random sources at different locations, i.e., how to decompose them into isolated records involving one source at a time. As an example, seismic-while-drilling experiments use active drill-string sources and receivers to look around and ahead of the borehole, but these receivers also record noise from the operation of the drill bit. A conventional method for deblending is independent component analysis (ICA), which assumes a “cocktail-party” mixing model where each receiver records a linear combination of source signals assumed to be statistically independent, and where only one source can have a Gaussian distribution. In this note, we extend the applicability of ICA to seismic shot records with markedly more complex mixing models with unknown wave kinematics, provided the following assumptions are met. 1. The active source is fully controllable, which means that it can be used to input a wide range of non-Gaussian random signals into the subsurface. 2. The waves are a linear function of the source, have a finite speed of propagation, and follow finite-length paths. The last assumption implies a scale separation, in frequency, between the mixing matrix elements (Green’s functions) and the random input signals. In this regime, we show that the key to the success of ICA is careful windowing to frequency bands over which the Green’s functions are approximately constant. Statoil ASA United States. Air Force. Office of Scientific Research (Grant FA9550- 12-1-0328) United States. Air Force. Office of Scientific Research (Grant FA9550-15-1-0078) National Science Foundation (U.S.) (Grant DMS-1255203) United States. Office of Naval Research (Grant N00014-16-1- 2122) 2018-06-12T14:04:46Z 2018-06-12T14:04:46Z 2017-09 2018-05-17T17:15:12Z Article http://purl.org/eprint/type/ConferencePaper 1949-4645 http://hdl.handle.net/1721.1/116240 Bharadwaj, Pawan, et al. "Deblending Random Seismic Sources via Independent Component Analysis." SEG Technical Program Expanded Abstracts 2017, pp. 4898–902. https://orcid.org/0000-0001-7052-5097 https://orcid.org/0000-0002-5872-8307 http://dx.doi.org/10.1190/SEGAM2017-17677817.1 SEG Technical Program Expanded Abstracts 2017 Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Society of Exploration Geophysicists MIT Web Domain |
| spellingShingle | Pisupati, Pawan Bharadwaj Demanet, Laurent Fournier, Aime Deblending random seismic sources via independent component analysis |
| title | Deblending random seismic sources via independent component analysis |
| title_full | Deblending random seismic sources via independent component analysis |
| title_fullStr | Deblending random seismic sources via independent component analysis |
| title_full_unstemmed | Deblending random seismic sources via independent component analysis |
| title_short | Deblending random seismic sources via independent component analysis |
| title_sort | deblending random seismic sources via independent component analysis |
| url | http://hdl.handle.net/1721.1/116240 https://orcid.org/0000-0001-7052-5097 https://orcid.org/0000-0002-5872-8307 |
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