The feasibility and value of low-frequency data collected using colocated 2-Hz and 10-Hz geophones
Bibliographic record
Abstract
ConocoPhillips acquired a production 3D surface seismic survey in 2010. The survey size was about 410 square miles recorded by 10-Hz geophones with INOVA 364 vibrators that are capable of sweeping from 1 to 150 Hz. In addition, we carried out a field experiment recording a swath of 3D surface seismic data with colocated 2-Hz and 10-Hz geophones. The cost of acquiring the 2-Hz geophone data was negligible when compared with the cost of the entire 3D survey. Because the vibrators can produce energy down to 2 Hz, the use of the 2-Hz geophone is crucial in capturing this energy. To our knowledge, this was the first field experiment employing the 2-Hz geophones and vibrators that could transmit enough low-frequency signals into the ground. The questions we investigate in this field experiment are: (1) how much low-frequency signal can be recorded using 2-Hz geophones, (2) how much degradation of low-frequency signal results from the 10-Hz geophones when compared to the 2-Hz geophones, and (3) the possibility of using the colocated data sets to enhance the low-frequency signal of 10-Hz geophone data that include both experimental and production data. The analyses of the 10-Hz and 2-Hz geophone data in prestack and poststack domains concluded that 2-Hz geophone data clearly exhibited more low-frequency signal than the 10-Hz geophone data. The 2-Hz geophone stack had low-frequency signal down to 2 Hz, and a spiking deconvolution further extended the amplitude spectrum down to 1 Hz. In addition, we develop a novel technique to derive a deterministic match filter from the colocated data sets. The application of this filter on the 10-Hz geophone data recovers the low-frequency signal below 10 Hz.
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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 | 0.001 | 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".