Strategies for reducing crosstalk in viscoacoustic full-waveform inversion
Bibliographic record
Abstract
Phenomena of seismic attenuation are both harmful to our ability to resolve elastic properties and of interest in their own right for quantitative interpretation. In applying methods of full waveform inversion on land, where low Q values are common in the near surface, and to the determination in general of suites of reservoir elastic properties, accommodation of Q is a complex and important issue. Cross-talk between velocity and Q cannot be easily avoided in full waveform inversion through achievable acquisition geometries. Much of this crosstalk can in principle be eliminated using appropriate optimization techniques in the inversion, but this can be prohibitively costly. We investigate using a multi-resolution inversion, where the number of variables inverted and optimization techniques used change with the frequencies considered, to lower the cost of reducing cross-talk, allowing for more accurate visco-acoustic full waveform inversion. Small numerical examples suggest that this may be a viable means of reducing cross-talk on long wavelength scales. Presentation Date: Wednesday, October 17, 2018 Start Time: 1:50:00 PM Location: 207C (Anaheim Convention Center) Presentation Type: Oral
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".