On the ability to store and recover hydrogen in post-SAGD reservoirs
Bibliographic record
Abstract
In typical steam-assisted gravity drainage (SAGD) operations, after commercial operations are complete, over 60% of the oil within the reservoir is produced. This means that after commercial operations, there is a steam-filled gas porous rock zone with small amounts residual water and oil referred to as the depletion zone. Given the dimensions of a SAGD depletion zone is of order of 1,000 long, 100 m wide, and between 20 and 30 m tall, this represents a large pore volume that could be used for storage. For underground options, there have been suggestions of using salt caverns and produced gas or oil reservoirs. One novel option that has not yet been examined is hydrogen storage in post-SAGD depletion chambers. The research described here an evaluation of post-SAGD chambers for injection and production of hydrogen. The results show that hundreds of tonnes of hydrogen can be stored within post-SAGD chambers and the purity of the hydrogen that is produced varies from 98% at start to 96% after 5 years of production during co-production of methane originated from the original solution gas that is the oil. The purity of produced hydrogen improved with increased hydrogen storage capacity after multiple cycle storage reaching its highest recovery factor of 99.2 % after 4 cycles.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".