The use of quad–quad resistivity in helicopter electromagnetic mapping
Bibliographic record
Abstract
Abstract The apparent resistivity from a helicopter-borne frequency-domain electromagnetic (EM) system is typically obtained from the in-phase and quadrature responses arising from the flow of conduction currents in the earth. The most commonly used resistivity algorithms, derived from half-space models and using single-frequency data, do not account for magnetic polarization and consequently do not yield a reliable value for apparent resistivity in highly magnetic areas. This is because magnetic polarization modifies the EM response, causing the computed resistivity to be erroneously high. The impact of magnetic permeability on the EM response is much greater for the in-phase component than for the quadrature component. If magnetic polarization is to be ignored, the calculation of the apparent resistivity using the quadrature component at two frequencies (the quad-quad algorithm) is less subject to error from magnetic polarization than if the in-phase and quadrature responses at a single frequency are used (the in-phase–quad algorithm). The quad-quad algorithm, however, can display undesirable behavior for large induction numbers, i.e., when conductivities and frequencies are large. Determining which algorithm is optimum is a data-dependent choice, which, of course, is area dependent. We have studied the behavior of the quad–quad (apparent) resistivity and its comparison to in-phase–quad resistivity to determine the conditions under which the use of quad-quad resistivity is appropriate. For a two-layer earth, the behavior of the quad-quad resistivity depends mainly upon the ratio of the lower frequency fL to the upper-layer resistivity ρ1. If this ratio is low, the quad–quad resistivity will behave well. In areas yielding a high value of the ratio fL/ρ1, the quad–quad resistivity may lie outside of the range of the true resistivities of the earth and therefore provide misleading information. Our studies therefore suggest that the quad–quad resistivity algorithm should be avoided in areas where the ratio is large, i.e., when using high frequencies in conductive areas. The term large is relative. For a two-layer case, for example, the use of quad–quad resistivity is only recommended for magnetic areas where fL/ρ1 < 500 Hz/ohm-m, when conductive cover exists, and where fL/ρ1 <50 Hz/ohm-m when a conductive basement underlies resistive cover. In spite of these limitations, quad-quad resistivity is often preferable to in-phase-quad resistivity in highly magnetic areas.
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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) | 0.000 | 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".