Exploration of the East Greenland Margin A project proposal to evaluate and model Palaeogene source rocks
Bibliographic record
Abstract
The critical part for future success in exploration in the Arctic is the access to first-class geophysical and geological data and their proper interpretation. As a consequence of the almost permanent sea ice coverage only limited access to qualitatively satisfactory 2D/3D seismic data and wells exists off the coast of eastern Greenland. However, to get a quantitative estimate on the petroleum potential of this region an integrated approach using new seismic reflection, aeromagnetic, gravity, and borehole data from Ocean Drilling Program (ODP) Leg 151, Site 913 (Fig. 1) applied to basin modeling might be an economic, environment friendly and save contribution. Our main goal is to work out an integrated study on Paleogene source rocks with particular focus on the Azolla freshwater fern event during the early middle Eocene. Source rocks from this time interval from the circum Arctic areas have been suggested by several authors (Mann et al. 2009). Based on the scientific drilling results and source rock modeling in the central Arctic Ocean (IODP-ACEX 2004, Mann et al. 2009), organic-rich sediments deposited under anoxic conditions during Eocene times raised the interest towards a basin-wide prolific Tertiary source rock north of the Arctic Circle. From the few data available along the north-eastern Greenland margin, an analogue to the anoxic environment in the central Arctic can be assumed for the isolated Greenland basins too. This is inferred from the contemporary occurrence of Azolla freshwater fern and organic-rich deposits (> 5 % TOC) in early Eocene sediments of ODP Hole 913B. By integrating geophysical and geological data from the East Greenland margin into state-of-the-art basin modeling tools, we will quantitatively evaluate the potential of this early Eocene source rock, i.e. we will provide a 3D-view on the distribution, thickness and quality of this material. In addition, processes of formation and cracking of petroleum fractions in the Eocene source rock and their expulsion will be investigated. The results from these latter activities combined with a simple thermal burial history modeling will provide unique additional information on hydrocarbon generation products and potential charge from the Eocene source 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".