Using Pressure and Volumetric Approaches to Estimate CO2 Storage Capacity in Deep Saline Aquifers
Bibliographic record
Abstract
Various approaches are used to evaluate the capacity of saline aquifers to store CO 2 , resulting in a wide range of capacity estimates for a given aquifer. The two approaches most used are the volumetric “open aquifer” and “closed aquifer” approaches. We present four full-scale aquifer cases, where CO 2 storage capacity is evaluated both volumetrically (with “open” and/or “closed” approaches) and through flow modeling. These examples show that the “open aquifer” CO 2 storage capacity estimation can strongly exceed the cumulative CO 2 injection from the flow model, whereas the “closed aquifer” estimates are a closer approximation to the flow-model derived capacity. An analogy to oil recovery mechanisms is presented, where the primary oil recovery mechanism is compared to CO 2 aquifer storage without producing formation water; and the secondary oil recovery mechanism (water flooding) is compared to CO 2 aquifer storage performed simultaneously with extraction of water for pressure maintenance. This analogy supports the finding that the “closed aquifer” approach produces a better estimate of CO 2 storage without water extraction, and highlights the need for any CO 2 storage estimate to specify whether it is intended to represent CO 2 storage capacity with or without water extraction.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".