Seismic imaging of crystalline structures: improving energy focusing and signal alignment with azimuthal binning and 2.5-D full-waveform inversion
Bibliographic record
Abstract
SUMMARY Severely crooked 2-D reflection profiles generate a swath distribution area of common midpoint (CMP) traces. These traces are scattered in all directions and no longer correspond to CMP gathers directly below the acquisition line, effectively posing a pseudo-3-D problem. Standard seismic processing techniques neglect the 3-D character of crooked seismic transects and often yield suboptimal images. The out-of-plane energy ignored in 2-D stacking techniques causes amplitude smearing effects due to anomalous reflection traveltimes. The imaging of dipping structures in geologically complex areas, such as in Larder Lake, are particularly affected because of complex energy scattering. These out-of-plane reflected wavefield components degrade energy focusing and signal alignment, worsening as the obliqueness of the profile with respect to local geology increases. To mitigate the contribution of scattered out-of-plane energy, we implement azimuthal binning. Pseudo-processing lines, parallel to the maximum geological dip, are generated by using locally optimum bin orientations. We use a priori geological information to devise optimum bin orientations in accordance to the local strike. We find that the optimized binning method significantly outperforms the standard approach in terms of in-phase amplitude stacking and reflection continuity. This is because the standard approach is based on a bin geometry always perpendicular to the seismic line traverse, ignoring 3-D effects, whereas in the optimum binning approach each individual bin may have a different orientation along the line. Moreover, we enhance the final reflectivity image by performing seismic migration with a velocity model that incorporates near-surface velocity estimations from full-waveform inversion. We demonstrate that the combination of these two innovations results in a significant impact on the imaging quality of structures at depth. In addition to imaging structures at depth, we also illustrate the significance of their continuation towards the near surface. This is especially important in the Larder Lake area where tectonic activity may have emplaced ore deposits in the first few kilometres of the subsurface.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".