Assessment of Storage Efficiency Factor of Deep Saline Aquifers Using Early 500 Ktonnes of Injected CO2 at the Aquistore CCS Site
Bibliographic record
Abstract
Abstract Estimation of effective storage capacity of the subsurface formations is currently one of the main technical and financial challenges for the Carbon Capture and Storage (CCS) industry. This factor indicates that not all available pore space will be accessible for CO2 storage. Even within accessible pore spaces, complete saturation with CO2 might not occur. This paper presents the evolution of storage efficiency factor during CO2 injection into a hyper-saline clastic formation. Values of storage efficiency factor were estimated based on 8 years of CO2 injection at Aquistore. Aquistore, the storage component of the Boundary Dam CCS project in Canada, aims to address the practical aspects of injecting large scale CO2 into a 3.4 km deep aquifer. The process involved analyzing CO2 injection data and employing multiple realizations of reservoir simulations that were calibrated to the time-lapse seismic surveys. We used the USDOE static storage estimation methodology for each geological layer in addition to the whole saline system and compared the results with dynamic CO2 storage efficiency from Aquistore. Multiple detailed geological and property models were derived from well logs and core analysis at Aquistore. Reservoir simulation cases were constructed for both the storage formations and the overlying caprock to explore the impacts of geology, trapping mechanisms, and injection schemes on storage efficiency. A wide range of time-dependent storage efficiency values were determined for each geological layer through history matching the flow simulation models to the Aquistore injection history in addition to the CO2 plume propagation determined from multiple 4D seismic data. The impacts of assumed degree of uncertainty in geologic and flow properties were considered on the overall storage efficiency factor. The estimation was highly affected by cutoff parameters to delineate the net thickness of the storage formations as well as the averaging technique used for petrophysical properties, especially in the case of multi-perforated zones. Lastly, the evolution of effective storage efficiency was discussed in the context of cold CO2 injection where non-isothermal localized fracturing, salt precipitation, and multiphase conditions could affect the early CO2 injectivity. Utilizing actual field data of over 500 ktonnes CO2 injection from the Aquistore CCS project is an asset to storage efficiency and capacity estimations. Our results provide a better understanding of evolution of storage efficiency factor in saline aquifers, offering valuable insights into the long-term prospects of geological CO2 storage projects.
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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 | 0.000 |
| 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) | 0.002 | 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 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".