The Impact of Interfacial Tension and Pore-Size Distribution/Capillary Pressure Character on CO2 Relative Permeability at Reservoir Conditions in CO2-Brine Systems
Bibliographic record
Abstract
Abstract Injection of CO2 has been used for enhanced oil recovery (EOR) in many light and medium gravity reservoirs. Consequently, sequestration of CO2 in oil reservoirs in conjunction with CO2-EOR is a method that is under consideration for reducing CO2 emissions into the atmosphere. Many oil reservoirs are underlain by an aquifer, and EOR processes often involve water-alternating-gas (WAG) processes. Proper understanding of the relative permeability character of such systems is essential in ascertaining CO2 injectivity and migration, and in assessing the suitability and safety of prospective CO2 injection and sequestration sites. While many measurements exist for CO2-oil systems, very few data, if any, exist for CO2-brine systems. This paper provides an analysis of brine-CO2 interfacial tension (IFT) measurements that were conducted for equilibrium brines and CO2 at reservoir conditions, and the detailed 700 MPa mercury-injection capillary pressure tests conducted on all rock samples to determine specific pore size distributions. Three sandstone and three carbonate potential sequestration zones in the Wabamun Lake area in Alberta, Canada, were evaluated, together with a caprock shale. This data set has specific application to the study of the behavior of injected CO2 in contact with bottom water or water-saturated zones that may be encountered in CO2-EOR projects, as well as for CO2 sequestration in deep saline aquifers. The analysis shows some correlation between the CO2-brine IFT, pore size distribution of the intergranular porous media and CO2-brine relative permeability. However, due to the high degree of variability in the pore system character of the different sandstone and carbonate facies tested, additional, better-controlled comparative tests are required to validate these trends. The hope is that, ultimately, compilation of more extensive datasets will allow appropriate selection of proper CO2-brine relative permeability relationships at reservoir conditions for intergranular sandstone and carbonate formations on the basis of relatively simple measurements of pore system geometry and IFT. These data will also provide a valuable tool for the estimation of CO2-brine relative permeability for the simulation and evaluation of intergranular sandstone and carbonate formations on a worldwide basis.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".