Aquifer heterogeneity from SH-wave seismic impedance inversion
Bibliographic record
Abstract
Abstract We collected SH-wave seismic reflection data over a shallow aquifer in southwestern British Columbia to investigate the use of such data in hydrogeologic applications. We used this data set in developing a methodology that uses cone penetrometer data as an integral part of the inversion and interpretation of the seismic data. A Bayesian inversion technique converts the seismic amplitude variations to velocity variations, honoring the probabilities of the priors and adhering to a geologically reasonable sparseness criterion. Velocity measurements acquired with the cone penetrometer provide velocity profiles and vertical seismic profiling (VSP) data, all of which are valuable in properly constraining the Bayesian inversion. The differentiation of lithologies (in this data set, sand and clay) is accomplished by first using a normalization procedure to remove the impact of effective stress, which dominates the velocity variation in the upper 10 to 20 m. The final transformation of seismic velocities to void ratio for the sand-dominated regions is made using laboratory-derived measurements; it provides an image of the heterogeneity of the near-surface aquifer.
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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) | 0.002 | 0.002 |
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; both teacher heads agree on what is shown here.
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".