Mathematical models of the distribution of geotracers during oil migration and accumulation
Bibliographic record
Abstract
Compounds which partition into water and which are adsorbed by solid phases (‘geotracers’) are lost from petroleum along migration pathways, giving important clues about the nature and length of the route from source to reservoir. Many factors influence the distribution of petroleum geotracers, including migration distance, the inherent properties of the migration systems, the chemical properties of the tracers, the volume of reservoired oil and the filling sequence. This paper constructs the mathematical models that are required to describe adequately the occurrence of geotracers in migrated and reservoired oils. The models show that for commonly used geotracers (phenol and carbazole compounds): (1) adsorption to oil-wet mineral sites is a major process removing geotracers from oil; (2) adsorption onto mineral surfaces can be treated as an equilibrium process on a geological time-scale; (3) diffusion of tracers from a migrating oil slug to the surrounding sediments can be neglected; and (4) the tracer concentration in a reservoired oil is not related uniquely to migration distance but is negatively correlated to the ratio of relative migration distance divided by the volume of reservoired oil having travelled the migration pathway. The potential applications of the models in petroleum exploration include: assessment of the route and relative distance of oil migration (with implications for the identification of undrilled prospects); estimation of the volume of lost oil by spill from a reservoir; and differentiation of migration through fractures and capillary migration through fine-grained rocks.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".