Rapid reactions between CO2, brine and silicate minerals during geological carbon storage: Modelling based on a field CO2 injection experiment
Bibliographic record
Abstract
The dissolution of CO 2 into formation brines and the subsequent reactions of the CO 2 -charged brines with reservoir minerals are two key processes likely to increase the security of geological carbon-dioxide storage. These processes will be dependent on the permeability structure and mineral compositions of the reservoirs, but there is limited observational data on their rates. In this paper we report the cation and anion concentrations and Sr, oxygen and carbon isotopic compositions of formation waters from four extraction wells sampled at surface, over ~ 6 months after commencement of CO 2 injection in a five spot pattern for enhanced oil recovery at the Salt Creek field, Wyoming. Sampled fluids, separated from the minor oil component, exhibit near-monotonic increases in alkalinity and concentrations of cations but little change in Cl and Br concentrations and oxygen and deuterium isotope ratios. The increases in alkalinity are modelled in terms of reaction with reservoir calcite and silicate minerals as the changes in fluid chemistry and Sr-isotopic compositions are inconsistent with simple addition of injected fluids sampled over the course of the experiment. The reservoir mineral chemical and isotopic compositions are characterised by sampling core as well as surface exposures of the Frontier Formation elsewhere in Wyoming. The evolution of the fluid chemistries reflects extensive dissolution of both carbonate and silicate minerals over the course of the six months sampling implying rapid dissolution of CO 2 in the formation waters and reaction of CO 2 -bearing brines with formation minerals. Rates of CO 2 diffusion into the brines and advection of CO 2 charged brines in the reservoir are sufficiently slow that, if present, calcite should react to be close to equilibrium with the fluids. This allows estimation of the CO 2 partial pressures in the sampled fluids and comparison with the thermodynamic driving force for the relatively rapid average plagioclase dissolution rates of ~ 10 − 12 mol·m − 2 ·s − 1 .
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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".