Joint inversion of navigation and resistivity using a fixed transmitter and a towed receiver array: a transient marine CSEM model study
Bibliographic record
Abstract
A typical marine controlled-source electromagnetic system consists of an electric dipole \ntransmitter and one or more electric dipole receivers. The objective of a survey is to determine \nthe seafloor resistivity by recording the electromagnetic transients, which diffuse through the \nearth from the transmitter to the receivers. Accurate knowledge of system geometry is crucial \nfor proper interpretation; errors in the position and orientation of the transmitter and/or the \nreceivers propagate into errors in the predicted seafloor resistivity. We show theoretically \nthat for certain multireceiver set-ups and crustal electrical profiles that the geometry and the \nseafloor resistivity may be determined independently. A specific example is an experiment \nproposed in association with NEPTUNE Canada. Here, we have already deployed an electric \ndipole transmitter with a known orientation in a known location. A cabled streamer of receivers \nmay be towed by a survey vessel in the vicinity of the transmitter on a known heading. For this \nconfiguration, an eigenparameter analysis of two seafloor models consisting of (1) a halfspace \nand (2) a resistive layer buried within a halfspace shows that the resistivity structure of the \nseafloor can be independently resolved from the cable location. Further studies of these two \nmodels also indicate that the position of the streamer must be roughly known in advance on \nthe order of a hundred metres to be used as a suitable starting model in a non-linear inversion. \nThe crucial information is contained in the parts of the pulse which travel through the seawater \nand which act as a calibration path. Such information is absent for a static DC method.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".