Full Waveform Inversion of Crosshole Data in Tilted Transversely Isotropic Media
Bibliographic record
Abstract
Summary We apply the joint approach of traveltime tomography and Full Waveform Inversion (FWI) to a synthetic experiment in media exhibiting Tilted Transverse Isotropy (TTI) Symmetry. We adopt a Finite-Difference Frequency-Domain (FDFD) approach for modeling acoustic waves within the seismic modeling framework, Zephyr. The synthetic crosshole experiment consists of a tilted layer sequence chosen to simulate a realistic TTI environment. Models of seismic velocity and the anisotropic parameters were obtained from anisotropic traveltime inversion and used as the starting models for monoparameter FWI to update the velocity model only. The effects of parameter crosstalk are evident within the traveltime results and are mitigated by the application of a Gaussian smoothing operator before FWI. The final FWI model contains all of the prominent features from the true model, although there are some artefacts present in these results. Steeply dipping artefacts are introduced due to mismatches between the velocity and background anisotropy models at larger offsets. We mitigate the presence of these artefacts by stringent offset weighting of the data at lower frequencies. The successful application of FWI to this synthetic experiment suggests that this approach is a suitable candidate for field data which display TTI symmetry.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".