Innovative CO2 Injection Strategies in Carbonates and Advanced Modeling for Numerical Investigation
Bibliographic record
Abstract
Carbon sequestration in deep saline aquifers was recently developed at the industrial scale. CO2 injection experiences in carbonates are quite limited, most of them coming from projects carried out in porous mediums in the USA and Canada. Hontomín (Spain) is the actual on-shore injection pilot in Europe, being a naturally fractured carbonate reservoir where innovative CO2 injection strategies are being performed within the ENOS Project. CO2 migration through the fracture network existing on site produces hydrodynamic, mechanical and geochemical effectsdifferent from those caused by the injection in mediums with a high matrix permeability. The interpretation of these effects is required to design safe and efficient injection strategies in these formations. For this, it is necessary to determine the evolution of pressure, temperature and flow rate during the injection, as well as the period of pressure recovery during the fall-off phase. The first results from the not-continuous injections (8–24 h) conducted at Hontomín reveal the injection of liquid CO2 (density value of 0.828 t/m3) and the fluid transmissivity through the fractures. Taking into account the evolution of the pressure and flow rate showed variations of up to 23% and 30% respectively, which means that the relevant changes of injectivity took place. The results were modeled with a compositional dual media model which accounts for both temperature effects and multiphase flow hysteresis because alternative brine and CO2 injections were conducted. Advanced modeling shows the lateral extension of CO2 and the temperature disturbance away from the well.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".