Storage Capacity and Regional Implications for Large-Scale Storage in the Basal Cambrian System
Bibliographic record
Abstract
A binational effort, between the United States and Canada, characterized the lowermost saline system in the Williston and Alberta Basins of the northern Great Plains–Prairie region of North America in the United States and Canada. This 3-year project was conducted with the goal of determining the potential for geologic storage of carbon dioxide (CO2 ) in rock formations of the 517,000 sq mi Cambro-Ordovician Saline System (COSS). This project was led on the U.S. side by the Energy & Environmental Research Center (EERC) through the Plains CO2 Reduction (PCOR) Partnership and on the Canadian side by Alberta Innovates Technology Futures (AITF). The project characterized the COSS using well log and core data from three states and three provinces and determined its storage potential by creating a heterogeneous 3-D model and determined the effects of CO2 storage in this system using dynamic simulation. The area underlain by the COSS includes several large CO2 sources that each emits more than 1 Mt CO2 /year. Assuming that each of these sources will target the COSS for the storage of their CO2, the primary questions addressed by this study are 1) what is the CO2 storage resource of the COSS, 2) how many years of current CO2 emissions will it be capable of storing, and 3) what will be required and what will be the effect of injecting 104 Mt/yr of CO2 into the COSS?
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".