Electrical and electromagnetic responses over steel-cased wells
Bibliographic record
Abstract
Abstract Electrical and electromagnetic (EM) methods can be diagnostic geophysical imaging tools for monitoring applications, such as carbon capture and storage or hydraulic fracturing. In these settings, it is common that steel-cased wells and other steel infrastructure are present. Grounded source methods, which use electrodes to inject current into the earth, are of interest for casing integrity and monitoring applications. Electrostatic, or direct current (DC) resistivity, experiments form the basis of our understanding of the physics of grounded source experiments in terms of charges, currents, and electric fields. Steel-cased wells are highly conductive, and although their presence makes numerical modeling more challenging, they can help targets of interest be detected because they channel charges and currents to depth. Time-domain EM experiments use a time-varying transmitter current. Understanding the EM response requires that we consider both galvanic, or DC, currents as well as image currents that are induced in the subsurface. As compared to DC experiments, the physics of EM is more complex because of the multiple current systems as well as the need to consider magnetic permeability of steel-cased wells. However, EM experiments have the advantage that they can provide a large data set that is sensitive to a target of interest. Ultimately, this will increase the potential for being able to extract information about the target.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".