Bibliographic record
Abstract
Seismic Unwired David Monk said Apache Corp. uses wireless seismic receivers when it cites advantages over traditional systems connected together by cables. Examples offered by Apache’s worldwide director of geophysics include a prospect that straddled the border of Argentina and Chile where equipment and radio signals were not allowed to cross; a survey in the shallow waters of the Gulf of Mexico where production platforms would get in the way of streamers used to pick up seismic signals; onshore areas where the cost of crews is high, which is the case in much of the US and Canada; and the Cook Inlet where the extreme environment offshore and onshore made wireless the choice for a number of reasons. “These things are more efficient systems over more difficult terrain,” Monk said. At the time of the interview nearly all the seismic exploration projects for Apache were wireless. Eliminating the bright orange or yellow cables reduces the weight of the system, can make it easier to work around obstacles or in difficult waters, and can significantly reduce the profile of seismic exploration in areas where that activity may not be welcome. A case study by Geospace, a maker of wireless receivers, of a seismic shoot done on the plains of Colombia by Pacific Rubiales Energy Corp., concluded a crew of 21 could lay down the wireless seismic receivers that would have required workers if it had been wired. And a side-by-side comparison by Apache in the Cook Inlet showed the quality of the seismic data gathered on land was similar for wired and unwired receivers, but wireless performed far better offshore in an area known for its difficult tides and currents. Apache is a wireless pioneer and is far from the norm in an industry where the largest seismic receiver provider, Sercel, estimates 90% of the seismic channels in use are wired. But the rapid takeoff of wireless receiver sales suggests that is changing. In most cases one channel, with a geophone that detects the echoes used for underground mapping, is equal to one wireless unit. Wireless multichannel units, though, are a growing part of the market.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.088 | 0.032 |
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".