The relationship between kh and achievable rates of injection, and repercussions for large scale storage
Bibliographic record
Abstract
Geologic CO 2 storage (GCS) can provide meaningful reduction of CO 2 emissions if implemented with large injection rates. The traditional paradigm for GCS entails injection of supercritical CO 2 into a brine-filled formation with an implicit assumption that resident brine can be displaced through boundaries of the formation without adverse effects. In this paradigm, kh , the product of permeability and formation thickness, is the first order control on achievable injection rates, and the gradual buildup of pressure in the formation during the storage operation will reduce those rates. These two factors impose serious constraints on the overall storage rate. In contrast, examination of field-aggregated injection and production volumes during waterflooding operations in oil reservoirs reveals a notable lack of correlation between kh and achieved injection rates. This suggests that if CO 2 storage projects are operated in the same manner as waterflooded oil reservoirs, i.e. with both injection and extraction wells, located and operated to maximize rates, then material rates of storage can be achieved regardless of reservoir kh . When applied to a large set of storage formations, this mode of operation provides an otherwise unattainable overall rate of storage while greatly reducing risks associated with elevated pressure in storage regions.
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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 | 0.000 |
| 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".