Marine Vibrator Milestone: A Pilot Seismic Survey
Bibliographic record
Abstract
Abstract The Marine Vibrator Joint Industry Project (MVJIP), sponsored by TotalEnergies, Shell and ExxonMobil, completed a successful pilot survey in Q3 2022 using two Integrated Project Node (IPN) Marine Vibrators in an offshore European open water setting. The IPNs were deployed in two configurations: one under tow, and the other stationary at each shot point. Various sweep types and duty cycles were also tested. An airgun source of equivalent energy size was also used for comparison. Throughout the pilot the IPNs demonstrated exemplary performance. There were no HSE incidents during the project, nor was there any technical downtime related to the IPNs. Moreover, real time quality control results were able to show the IPNs high fidelity with respect to the pilot sweep and excellent sweep-to-sweep repeatability. A fast-track processing sequence was completed, which showed that the IPNs have been able to image the subsurface very well including steeply dipping reflectors. This demonstrates the progress that has been achieved by the MVJIP over the last 10 years and gives a real impetus to continue the development of the marine vibrators into a commercial source. The next steps will be to complete a more comprehensive full processing sequence on all the lines to extract the best possible images.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".