Geochemical Impact of Oxygen Impurity on Siliciclastic and Carbonate Reservoir Rocks for Carbon Storage
Bibliographic record
Abstract
Geochemical effects of gas impurities in the CO 2 stream are not fully investigated. Co-injection of reactive impurities (such as O2, CO, H2, NOx, and SOx) may cause detrimental effects on storage reservoirs and seals. In this study, a series of autoclave experiments are conducted to investigate the potential impacts of O2 as an impurity on selected siliciclastic and carbonate reservoir rocks. Eight reaction experiments on three sandstones have been conducted at 200 bar and 70 °C and100 °C: Miocene sandstone (Texas offshore, U.S.A.), lower Tuscaloosa sandstone (Cranfield field, Mississippi, U.S.A.) and Cardium sandstone (Pembina field, Alberta, Canada). Six experiments have been conducted on two carbonate rocks so far (Redwater Leduc limestone, Canada; Cisco limestone, SACROC Unit, Texas, USA). The study shows that rocks lacking reducing minerals show limited geochemical changes with co-injection of a small volume of O2 in supercritical CO 2 . The presence of O2 does not accelerate the dissolution of carbonate and feldspar minerals, nor does it lead to new reactions. However, the addition of oxygen causes pronounced geochemical impacts when a small amount of the reducing mineral-pyrite is present in rock. As pyrite is oxidized, H+ ions are produced, resulting in pH reduction that increases dissolution of carbonate minerals. When there is a lack of pH buffering carbonate minerals, the effect of further pH drop is manifest as feldspar dissolution accelerates. Aqueous ferrous iron derived from pyrite oxidation is largely converted to iron oxyhydroxides which precipitate on mineral surfaces. The results suggest that addition of small volume fractions of O2 is unlikely to result in significant effects on carbonate rocks. Dissolution of calcite and/or dolomite is the dominant reactions to take place when CO 2 is added.
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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 | 0.000 |
| 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) | 0.001 | 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".