On method-of-moments modelling of electromagnetic sources connected to metallic well casings
Bibliographic record
Abstract
SUMMARY Metallic well casings strongly impact electromagnetic fields due to their high electrical conductivity. We can take advantage of their presence and increase the sensitivity of EM signals to deeper subsurface structure by driving electric currents down through existing casings, or using the metal as a wave guide for EM telemetry. Interpretation of such well-casing-enhanced measurements requires accurate simulation of these setups. The Method of Moments (MoM) can be used for modelling well casings without having to discretize them finely as part of the subsurface model. Extending the MoM for EM sources directly connected to well casings is straightforward in principle. However, we find that the accuracy of MoM results for such configurations depends strongly on details of the computational model definition, such as the exact position of the connection point and the discretization of the source wire. We explain those important details and provide strategies for the most accurate MoM modelling of electric currents injected into well casings.
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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 | 0.001 |
| 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) | 0.001 | 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 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".