Conditioning surface-based models to well and thickness data
Abstract/Contents
- Abstract
- Surface-based models imitate a sequence of depositional events in time. By considering sedimentation processes, these algorithms produce highly realistic subsurface structures from a variety of environments. However, since depositional events are forward-modeled, they cannot be directly conditioned to data. Therefore, conditioning requires solving a possibly expensive inverse problem. In this study, an optimization scheme is developed that allows conditioning turbidite simulation to thickness information and well data. The methodology is applied to three real data sets.
Description
| Type of resource | text |
|---|---|
| Form | electronic; electronic resource; remote |
| Extent | 1 online resource. |
| Publication date | 2011 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Associated with | Bertoncello, Antoine |
|---|---|
| Associated with | Stanford University, Department of Energy Resources Engineering |
| Primary advisor | Caers, Jef |
| Thesis advisor | Caers, Jef |
| Thesis advisor | Durlofsky, Louis |
| Thesis advisor | Tchelepi, Hamdi |
| Advisor | Durlofsky, Louis |
| Advisor | Tchelepi, Hamdi |
Subjects
| Genre | Theses |
|---|
Bibliographic information
| Statement of responsibility | Antoine Bertoncello. |
|---|---|
| Note | Submitted to the Department of Energy Resources Engineering. |
| Thesis | Thesis (Ph.D.)--Stanford University, 2011. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2011 by Antoine Bertoncello
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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