Structural uncertainty and geophysical data fusion: A synthetic example
We attempt to address two issues in seismic data processing: 1) quantifying the various forms of error that enter into the seismic data processing work-flow and relating them to uncertainty on imaged structures; and, 2) the data fusion problem, i.e. combining different sources of information, each r...
| Main Authors: | , , , |
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| Format: | Technical Report |
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Massachusetts Institute of Technology. Earth Resources Laboratory
2011
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| Online Access: | http://hdl.handle.net/1721.1/67862 |
| _version_ | 1826201876831404032 |
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| author | Kane, Jonathan Rodi, William Nemeth, Tamas Mikhailov, Oleg |
| author2 | Massachusetts Institute of Technology. Earth Resources Laboratory |
| author_facet | Massachusetts Institute of Technology. Earth Resources Laboratory Kane, Jonathan Rodi, William Nemeth, Tamas Mikhailov, Oleg |
| author_sort | Kane, Jonathan |
| collection | MIT |
| description | We attempt to address two issues in seismic data processing: 1) quantifying the various forms of error that enter into the seismic data processing work-flow and relating them to uncertainty on imaged structures; and, 2) the data fusion problem, i.e. combining different sources of information, each related to seismic velocity. To begin addressing these issues a synthetic model was generated consisting of 4 tilted layers (3 interfaces), each with a different isotropic P-wave velocity. A synthetic well log was extracted from this model to be incorporated later. Synthetic shot gathers were also created. Following the standard seismic processing work-flow, stacking velocities were estimated. Uncertainty on these velocities was incorporated by under- and over-picking the velocities by ±10% and examining the effects on the final image. The stacking velocity information was then converted to interval velocity and fused with the well velocity information. Along with the under-, over-, and best picked velocities, realizations of the velocity field were created via geostatistical methods according to an assumed correlation structure. By further applying time migration and time to depth conversion, equiprobable realizations of the subsurface structure were generated along with upper and lower bounds on their locations. The realizations honor all the existing data sets and give a visual representation of the uncertainty on the spatial location of imaged structures. |
| first_indexed | 2024-09-23T11:58:35Z |
| format | Technical Report |
| id | mit-1721.1/67862 |
| institution | Massachusetts Institute of Technology |
| last_indexed | 2024-09-23T11:58:35Z |
| publishDate | 2011 |
| publisher | Massachusetts Institute of Technology. Earth Resources Laboratory |
| record_format | dspace |
| spelling | mit-1721.1/678622019-04-10T09:59:39Z Structural uncertainty and geophysical data fusion: A synthetic example Kane, Jonathan Rodi, William Nemeth, Tamas Mikhailov, Oleg Massachusetts Institute of Technology. Earth Resources Laboratory Kane, Jonathan Rodi, William Nemeth, Tamas Mikhailov, Oleg Modeling Imaging Migration We attempt to address two issues in seismic data processing: 1) quantifying the various forms of error that enter into the seismic data processing work-flow and relating them to uncertainty on imaged structures; and, 2) the data fusion problem, i.e. combining different sources of information, each related to seismic velocity. To begin addressing these issues a synthetic model was generated consisting of 4 tilted layers (3 interfaces), each with a different isotropic P-wave velocity. A synthetic well log was extracted from this model to be incorporated later. Synthetic shot gathers were also created. Following the standard seismic processing work-flow, stacking velocities were estimated. Uncertainty on these velocities was incorporated by under- and over-picking the velocities by ±10% and examining the effects on the final image. The stacking velocity information was then converted to interval velocity and fused with the well velocity information. Along with the under-, over-, and best picked velocities, realizations of the velocity field were created via geostatistical methods according to an assumed correlation structure. By further applying time migration and time to depth conversion, equiprobable realizations of the subsurface structure were generated along with upper and lower bounds on their locations. The realizations honor all the existing data sets and give a visual representation of the uncertainty on the spatial location of imaged structures. ChevronTexaco (Firm) 2011-12-21T22:43:33Z 2011-12-21T22:43:33Z 2003 Technical Report http://hdl.handle.net/1721.1/67862 Earth Resources Laboratory Industry Consortia Annual Report;2003-10 application/pdf Massachusetts Institute of Technology. Earth Resources Laboratory |
| spellingShingle | Modeling Imaging Migration Kane, Jonathan Rodi, William Nemeth, Tamas Mikhailov, Oleg Structural uncertainty and geophysical data fusion: A synthetic example |
| title | Structural uncertainty and geophysical data fusion: A synthetic example |
| title_full | Structural uncertainty and geophysical data fusion: A synthetic example |
| title_fullStr | Structural uncertainty and geophysical data fusion: A synthetic example |
| title_full_unstemmed | Structural uncertainty and geophysical data fusion: A synthetic example |
| title_short | Structural uncertainty and geophysical data fusion: A synthetic example |
| title_sort | structural uncertainty and geophysical data fusion a synthetic example |
| topic | Modeling Imaging Migration |
| url | http://hdl.handle.net/1721.1/67862 |
| work_keys_str_mv | AT kanejonathan structuraluncertaintyandgeophysicaldatafusionasyntheticexample AT rodiwilliam structuraluncertaintyandgeophysicaldatafusionasyntheticexample AT nemethtamas structuraluncertaintyandgeophysicaldatafusionasyntheticexample AT mikhailovoleg structuraluncertaintyandgeophysicaldatafusionasyntheticexample |