Modelling electromagnetic problems in the presence of cased wells
Bibliographic record
Abstract
Summary Electrical conductivity can be a diagnostic physical property for distinguishing geologic units and delineating the distribution of fluids such as hydrocarbons and saline water within these units. Electromagnetic (EM) methods are sensitive to conductivity contrasts and can be used to characterize them. They are increasingly being applied in settings where cased wells are present. Most commonly-used casing materials, such as steel, are highly conductive, have a significant, often variable, magnetic permeability, and therefore significantly impact the behavior of the EM fields and fluxes. The aim of this paper is to revisit numerical modelling strategies to investigate the role of various properties and complexities due to the casing, and present a modelling and inversion strategy, using a primary-secondary approach, for capturing the impacts of both the variable casing and three dimensional geologic structures on EM data.
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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".