Near-surface S-wave velocity models from two uphole surveys
Bibliographic record
Abstract
PreviousNext No Access12th International Congress of the Brazilian Geophysical Society & EXPOGEF, Rio de Janeiro, Brazil, 15–18 August 2011Near-surface S-wave velocity models from two uphole surveysAuthors: Saul Guevara*Gary MargraveWilliam AgudeloFausto GomezSaul Guevara*CREWES-University of Calgary, Gary MargraveCREWES-University of Calgary, William AgudeloEcopetrol-ICP, and Fausto GomezEcopetrol-ICPhttps://doi.org/10.1190/sbgf2011-255 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InReddit Abstract Two uphole surveys were carried out at the location of an on-shore 3C survey in Colombia. An S-wave velocity model was obtained from these data, based on events apparently generated by the source. High variations in the velocity model with depth were observed and related to lithological characteristics. These variations can hardly be observed using surface seismic data. This velocity model can be useful in the computation of statics correction in the processing of converted-wave (PS) or S-wave seismic data, as well as in engineering and other near surface applications. Keywords: multicomponent, near surface, velocityPermalink: https://doi.org/10.1190/sbgf2011-255FiguresReferencesRelatedDetailsCited byMethod of building three-dimensional near-surface S-wave velocity model via down-hole surveysMin Li, Miaoyu Chen, Xiaoyang Wang, Zhichao Yang, Jiangli Chen, Pandeng Liu, Xiao Fan, Chenyi Li, and Yuefeng Sun27 August 2018Low velocity layer characterization in the Niger Delta: Implications for seismic reflection data quality2 September 2017 | Journal of the Geological Society of India, Vol. 90, No. 2Near-surface S-wave velocity from an uphole experiment using explosive sourcesSaul E. Guevara, Gary F. Margrave, and William M. Agudelo19 August 2013Using converted-wave seismic data for lithology discrimination in a complex fluvial setting: Tenerife oil field, Middle Magdalena Valley, ColombiaWilliam Agudelo, Edgar Pineda, Ricardo Gómez, Jairo Guerrero, Nelson Rojas, Rob Stewart, and Norbert van de Coevering31 December 2012 | The Leading Edge, Vol. 32, No. 1Seismic lithology discrimination in complex fluvial stratigraphy: Tenerife 3D 3C Survey, Middle Magdalena Valley (Colombia).William Agudelo, Ricardo Gómez, Jairo Guerrero, Ingrid Tatiana Cabrejo, Nelson Rojas, S.A Ecopetrol, and Saul Guevara25 October 2012 12th International Congress of the Brazilian Geophysical Society & EXPOGEF, Rio de Janeiro, Brazil, 15–18 August 2011ISSN (online):2159-6832Copyright: 2011 Pages: 2223 publication data© 2011 Published in electronic format with permission by the Brazilian Geophysical SocietyPublisher:Society of Exploration Geophysicists HistoryPublished Online: 13 Mar 2014 CITATION INFORMATION Saul Guevara*, Gary Margrave, William Agudelo, and Fausto Gomez, (2011), "Near-surface S-wave velocity models from two uphole surveys," SEG Global Meeting Abstracts : 1237-1240. https://doi.org/10.1190/sbgf2011-255 Plain-Language Summary Keywordsmulticomponentnear surfacevelocityPDF DownloadLoading ...
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".