Up-Scaling Geochemical Reaction Rates for Carbon Dioxide (CO2) in Deep Saline Aquifers
Bibliographic record
Abstract
Geochemical reactions in deep subsurface environments are complicated by the consolidated nature and mineralogical complexity of sedimentary rocks. Understanding the kinetics of these reactions is critical to our ability to make long-term predictions about subsurface processes such as pH buffering, alteration in rock structure, permeability changes, and formation of secondary precipitates. In this project, we used a combination of experiments and numerical simulation to bridge the gap between our knowledge of these reactions at the lab scale and rates that are meaningful for modeling reactive transport at core scales. The focus is on acid-driven mineral dissolution, which is specifically relevant in the context of CO2-water-rock interactions in geological sequestration of carbon dioxide. The project led to major findings in three areas. First, we modeled reactive transport in pore-network systems to investigate scaling effects in geochemical reaction rates. We found significant scaling effects when CO2 concentrations are high and reaction rates are fast. These findings indicate that the increased acidity associated with geological sequestration can generate conditions for which proper scaling tools are yet to be developed. Second, we used mathematical modeling to investigate the extent to which SO2, if co-injected with CO2, would acidify formation brines. We found that there exist realistic conditions in which the impact on brine acidity will be limited due to diffusion rate-limited SO2 dissolution from the CO2 phase, and the subsequent pH shift may also be limited by the lack of availability of oxidants to produce sulfuric acid. Third, for three Viking sandstones (Alberta sedimentary basin, Canada), we employed backscattered electron microscopy and energy dispersive X-ray spectroscopy to statistically characterize mineral contact with pore space. We determined that for reactive minerals in sedimentary consolidated rocks, abundance alone is not a good predictor of mineral accessible surface area, and should not be used in reactive transport modeling. Our work showed that reaction rates would be overestimated by three to five times.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".