Worldwide Comparison of CO₂-EOR Conditions: Comparison of fiscal and industrial conditions in seven global regions where CO₂-EOR is active or under consideration
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Previous work within the Scottish Carbon Capture & Storage (SCCS) joint industry project (JIP) on carbon dioxide enhanced oil recovery (CO2-EOR) which looked at financial incentives for CO2-EOR in the United Kingdom (UK) suggested that development of an EOR project in the UK continental shelf area was most likely only to be considered by a super-major or multinational oil company (Durusut and Pershad, 2014). For such a project to be initiated the overall conditions for CO2-EOR - financial, policy, industrial - would need to be equivalent or favourable compared to other oil-producing regions, otherwise investments would likely be made elsewhere. The purpose of this work package was to compare such conditions between seven major oil- producing regions that either are already, or are considering using CO2-EOR to increase oil outputs. The regions chosen were: • United States of America (USA) onshore • USA Gulf of Mexico • Canada • Malaysia • China • Norway • UK This report covers initial, desk-based research to compare regional conditions for CO2-EOR developments focussing in particular on tax regimes and also covering CO2 supply availability and CO2 transport infrastructure. Other areas of comparison - energy policies, regulatory conditions and government support - are not covered in this report but may be included in further studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it