Vertical hydrophone cable acquisition and imaging on land
Bibliographic record
Abstract
Abstract We acquired seismic data using a vertical hydrophone cable in a shallow, fluid-filled borehole over the Blackfoot oil field in Alberta, Canada. The hydrophone data were recorded simultaneously with a surface seismic survey using dynamite sources. In addition, buried three-component (3-C) geophone data were acquired near the vertical cable. We observe that events on the hydrophone records are in phase with corresponding geophone data. Tube waves, which can be a problem on hydrophone data, are suppressed using a predictive deconvolution operator. Imaging, using the hydrophone data, results in a section that correlates well with a surface seismic image from vertical-component geophone data. An anomaly, interpreted to be associated with the sand reservoir in the area, is evident on the hydrophone image (as well as on the surface seismic sections). The vertical hydrophone cable promises excellent imaging potential for land applications.
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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".