Investigating the relationship between magnetisation and oil geochemistry
Bibliographic record
Abstract
A relationship between hydrocarbons and their magnetic signatures has previously been alluded to but this is the first study to combine extensive geochemical and magnetic data of hydrocarbon-associated samples. A detailed study is reported that identifies a definitive connection between magnetic mineralogy and oil biodegradation within samples from Colombia, Canada, Indonesia and the UK. Geochemical data revealed that all the oil samples were derived from mature type-II kerogen deposited in oxygen-poor environments allowing for an investigation into biodegradation. Biodegradation is the decrease of oil quality through the conversion of aliphatic hydrocarbons to polar constituents through the activity of bacteria. The percentage of oil components and the biodegradation state of the samples were compared to the magnetic susceptibility and magnetic mineralogy. A distinct decrease in magnetic susceptibility was correlated to decreasing oil quality as well as extractable organic matter percentages, which cannot be rejected at 99% confidence. Further magnetic characterisation revealed that the high quality oils were dominated by pseudo-single domain grains of magnetite and the lower quality oils by larger pseudo-single domain to multi domain grains of magnetite and hematite; with decreasing oil quality there is a progressive dominance of multi domain magnetite as well as the appearance of hematite. It is concluded that biodegradation is a dual process, firstly, removing aliphatic hydrocarbons reducing oil quality and secondly, both creating and destroying magnetic signatures. This complex relationship may explain why controversy existed in the past when studying hydrocarbon associated anomalies. Remagnetisation due to hydrocarbon infiltration is also reported within the Wessex Basin, UK. Palaeodirectional data from Mupe Bay revealed oil migration was initiated in the Early Cretaceous and a two-phase staining model is correct. These findings reinforce the importance of bacteria within petroleum systems as well as providing a platform for the use of magnetisation as a hydrocarbon proxy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".