Elastic seismic wave scattering and imaging of massive sulfides: rock physics and implications for seismic data acquisition and processing
Bibliographic record
Abstract
We present a modeling study that considers geological and petrophysical information to evaluate the applicability of seismic methods for imaging massive sulfides. Emphasis is on three component (3C) seismic data acquisition, processing and potential pitfalls due to heterogeneities in the velocity field usually observed both at the stratigraphic/lithologic and log scales. Full 2D/3D surface seismic modeling results confirm the direct seismic detectability of the deep massive sulfide. However, modelled effects of heterogeneities on seismic wave propagation suggest these inhomogeneities can locally attenuate the seismic response that characterizes the orebody. Due to the strong P-wave velocity, S-wave velocity, and density contrast of the orebody, its seismic signature is also characterized by strong converted PS-waves. These converted waves can be processed accordingly to help in the seismic characterization of the orebody.
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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".