Drainage and Imbibition CO2/Brine Relative Permeability Curves at Reservoir Conditions for Carbonate Formations
Bibliographic record
Abstract
Abstract Proper modeling of the multiphase flow of supercritical CO2 in deep saline aquifers for CO2 sequestration (both cycles of drainage during injection and imbibition during CO2 migration) is critical in being able to understand and predict both the short and long term fate of the injected CO2 over extended time periods (hundreds to thousands of years). Current numerical models require the use of accurate two-phase CO2/brine relative permeability data at representative in-situ conditions in order to be able to accurately conduct these calculations. However, there are virtually no published data in the literature on the high temperature and pressure displacement character of CO2/brine systems in actual reservoir rocks, except for the data published by the authors in the June 2008 issue of the SPE Reservoir Evaluation and Engineering Journal. That data set, although it included a few carbonate cases, contained mostly measurements on clastic rocks. This paper presents a new set of nine relative permeability measurements (both drainage and imbibition) for carbonate rocks (limestone and dolomite) of higher permeability values than those in the initial work (which are thus more likely to be representative for candidates for CO2 sequestration in deep saline aquifers). The new data set to be presented includes also pre and post-test CAT-scan imaging of selected samples to illustrate potential effects of CO2 contact on potentially soluble carbonate matrices. The paper compares the new data set of measurements for carbonate rocks with the limited set of data available for carbonates from the previous work, and attempts to determine if specific relative permeability and residual saturation trends can be defined based on other rock characteristics that are easier to measure in routine core analyses, to allow extension of the data set to other carbonate facies elsewhere which have not been tested.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".