Simultaneous least squares deconvolution and kriging using conjugate gradients
Least squares deconvolution is a method used to sharpen tomographic images of the earth by undoing the bandlimiting effects imposed by a seismic wavelet. Kriging is a method used by geoscientists to extrapolate and interpolate sparse data sets. These two methodologies have traditionally been kept se...
| Main Authors: | , , |
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| Format: | Technical Report |
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Massachusetts Institute of Technology. Earth Resources Laboratory
2012
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| Online Access: | http://hdl.handle.net/1721.1/68600 |
| _version_ | 1811080476095414272 |
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| author | Kane, Jonathan Rodi, William Toksoz, M. Nafi |
| author2 | Massachusetts Institute of Technology. Earth Resources Laboratory |
| author_facet | Massachusetts Institute of Technology. Earth Resources Laboratory Kane, Jonathan Rodi, William Toksoz, M. Nafi |
| author_sort | Kane, Jonathan |
| collection | MIT |
| description | Least squares deconvolution is a method used to sharpen tomographic images of the earth by undoing the bandlimiting effects imposed by a seismic wavelet. Kriging is a method used by geoscientists to extrapolate and interpolate sparse data sets. These two methodologies have traditionally been kept separate and viewed as unrelated fields of research. We demonstrate the connection between these methods by deriving them both as examples of linear inversion. By posing the methods in this way we can define a joint inverse problem in which observed values of reflectivity in wells are used to improve deconvolution, and, conversely, seismic data is used to help extrapolate well data.
Solving this joint problem involves the solution of large sparse sets of linear equations. Due to the structure of the problem, the conjugate gradients method is ideal to perform the solution. Preliminary results show that convergence to a solution for a 3-D problem is fast and accurate, requiring only a few iterations.
This methodology can be of great use to interpreters by sharpening the post stack image as well as helping to tie seismic data to wells. |
| first_indexed | 2024-09-23T11:32:17Z |
| format | Technical Report |
| id | mit-1721.1/68600 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T11:32:17Z |
| publishDate | 2012 |
| publisher | Massachusetts Institute of Technology. Earth Resources Laboratory |
| record_format | dspace |
| spelling | mit-1721.1/686002019-04-11T06:24:53Z Simultaneous least squares deconvolution and kriging using conjugate gradients Kane, Jonathan Rodi, William Toksoz, M. Nafi Massachusetts Institute of Technology. Earth Resources Laboratory Kane, Jonathan Rodi, William Toksoz, M. Nafi Inversion Least squares deconvolution is a method used to sharpen tomographic images of the earth by undoing the bandlimiting effects imposed by a seismic wavelet. Kriging is a method used by geoscientists to extrapolate and interpolate sparse data sets. These two methodologies have traditionally been kept separate and viewed as unrelated fields of research. We demonstrate the connection between these methods by deriving them both as examples of linear inversion. By posing the methods in this way we can define a joint inverse problem in which observed values of reflectivity in wells are used to improve deconvolution, and, conversely, seismic data is used to help extrapolate well data. Solving this joint problem involves the solution of large sparse sets of linear equations. Due to the structure of the problem, the conjugate gradients method is ideal to perform the solution. Preliminary results show that convergence to a solution for a 3-D problem is fast and accurate, requiring only a few iterations. This methodology can be of great use to interpreters by sharpening the post stack image as well as helping to tie seismic data to wells. 2012-01-17T17:53:15Z 2012-01-17T17:53:15Z 2001 Technical Report http://hdl.handle.net/1721.1/68600 Earth Resources Laboratory Industry Consortia Annual Report;2001-04 application/pdf Massachusetts Institute of Technology. Earth Resources Laboratory |
| spellingShingle | Inversion Kane, Jonathan Rodi, William Toksoz, M. Nafi Simultaneous least squares deconvolution and kriging using conjugate gradients |
| title | Simultaneous least squares deconvolution and kriging using conjugate gradients |
| title_full | Simultaneous least squares deconvolution and kriging using conjugate gradients |
| title_fullStr | Simultaneous least squares deconvolution and kriging using conjugate gradients |
| title_full_unstemmed | Simultaneous least squares deconvolution and kriging using conjugate gradients |
| title_short | Simultaneous least squares deconvolution and kriging using conjugate gradients |
| title_sort | simultaneous least squares deconvolution and kriging using conjugate gradients |
| topic | Inversion |
| url | http://hdl.handle.net/1721.1/68600 |
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