Monitoring CO2 injection for carbon capture and storage using time-lapse 3D VSPs
Bibliographic record
Abstract
Carbon capture and storage (CCS) is the process through which a nearly pure carbon dioxide (CO2) stream is captured, separated from flue gas or other industrial processes, compressed, transported to an appropriate storage site, and injected deep underground into a geological formation where it can be safely stored for long-term geologic storage (Benson, 2005). Large sedimentary basins, such as the Illinois, Michigan, and Western Canadian sedimentary basins are good targets for CCS, as they are in close proximity to large CO2 emitters and are composed of the appropriate saline formations and overlying nonpermeable formations. In 2003, the U.S. Department of Energy's National Energy Technology Laboratory (DOE-NETL) created a nationwide network of federal, state, and private sector partnerships to determine the most suitable technologies, regulations, and infrastructure for future CCS in different areas of the North America (Office of Fossil Energy, 2013).
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.
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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".