3D Full Tensor Gradiometry: a high resolution gravity measuring instrument resolving ambiguous geological interpretations
Bibliographic record
Abstract
The high-resolution, high-precision gravity gradient measuring technology, Bell Geospace’s 3D FTG (Full Tensor Gradiometry), is presented as an exploration tool to enhance and solve ambiguous geological interpretations from conventional methods. Its high frequency character produces a Total Gravity Field that identifies subtle density contrasts within section, allowing it to be used in detailed hydrocarbon and mineral exploration projects, both offshore and onshore.This paper presents two case histories describing the results from an airborne and a marine survey. Both studies demonstrate the technology’s ability not only in determining target shape but also in mapping target prospects across large sedimentary basins. The first example presented in this paper images a salt dome onshore Louisiana, USA, making inferences about its emplacement through direct mapping of controlling structure. The second identifies and maps a series of low-density sedimentary deposits on the flanks of the Judd Basin offshore NW Europe.The implications for exploration initiatives are significant as FTG data reduce risk in geological interpretation, thus facilitating a rapid decision making process.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".