Techno-economic assessment of supercritical, cold liquid, and dissolved CO2 injection into sub-seafloor basalt
Bibliographic record
Abstract
Injecting CO 2 into subsea basalt can provide permanent storage via multiple trapping mechanisms, including mineralization reactions which convert the CO 2 into solid carbonates over time. Injecting CO 2 together with water can accelerate the process of mineralization, but presents additional challenges, such as high energy and water requirements. A techno-economic model of CO 2 transport and injection into ocean basalt was developed to compare injection strategies using pure supercritical CO 2 , pure liquid CO 2 , and CO 2 dissolved in seawater. The model was applied to a representative injection site off the coast of British Columbia, Canada. Injection of CO 2 dissolved into seawater was found to be more energy and cost intensive than injection of supercritical or liquid CO 2 ; this is primarily due to the reduced quantities of CO 2 that can be injected into each well, and additional pumping energy required for the accompanying seawater. For the base assumptions, transport and storage costs for supercritical, liquid, and dissolved injection were estimated as $43/t, $38/t, and $250/t respectively. Their energy requirements were estimated as 93 kWh/t, 90 kWh/t, and 213 kWh/t respectively. The current best estimates of geological parameters for ocean basalt suggest good injectivity and very large storage capacities per well. This may help to compensate for the additional project expenses incurred by deep water, allowing cost-effective liquid and supercritical injection. However, this result is sensitive to high uncertainties in both geological parameters and component cost data.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| 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".