Investigation of effect and mechanism of active water and CO2 huff-and-puff on enhanced oil recovery in tight reservoirs
Bibliographic record
Abstract
Energized huff and puff is a key technology for tight reservoirs. Active water and CO2 are two energized huff-and-puff media with great development potential, but their enhanced oil recovery (EOR) effects and the imbibition mechanism still need further experimental research. In this paper, short cores were spliced into long cores for energized huff-and-puff experiments. Combined with nuclear magnetic resonance (NMR) testing, the T2 spectra of different core sections changed with the huff-and-puff cycles, and then the EOR effects, limited effective distances, pore throat characteristics, and influencing factors of active water and CO2 energized huff-and-puff were evaluated. Meanwhile, a comparative experiment without well soaking in a specific huff-and-puff cycle was designed to quantitatively split the contribution rate of elastic displacement and imbibition displacement to EOR. The experimental results show that active water huff-and-puff mainly mobilizes crude oil in large pores, while CO2 huff-and-puff can simultaneously mobilize crude oil in small pores. The cumulative oil recovery of active water and CO2 after 4 cycles of Huff-and-Puff was 24.78% and 40.89%, respectively, and the limited effective distances were 6-8cm and 8-10cm, respectively. The stage recovery rate of active water and CO2 huff-and-puff significantly decreases with increased huff-and-puff rounds. The longer well soaking duration will result in a higher final oil recovery. Elastic displacement is the main contribution mechanism of active water and energized CO2 huff-and-puff, and imbibition displacement accounts for 20.86% and 31.52%, respectively. Due to its good diffusion and mass transfer ability, CO2 can more fully play the mechanism of imbibition displacement and further improve oil recovery. The research results of this paper can provide data support for the application of energized huff-and-puff in tight reservoirs. Document Type: Original article Cited as: Chen, X., Zhu, J., Chao, L., Trivedi, J., Liu, J., Liu, S. Investigation of effect and mechanism of active water and CO2 huff-and-puff on enhanced oil recovery in tight reservoirs. Capillarity, 2025, 14(1): 23-34. https://doi.org/10.46690/capi.2025.01.03
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.001 |
| 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".